WorldWideScience

Sample records for concentrations predict mortality

  1. Increased serum concentrations of soluble ST2 predict mortality after burn injury.

    Science.gov (United States)

    Hacker, Stefan; Dieplinger, Benjamin; Werba, Gregor; Nickl, Stefanie; Roth, Georg A; Krenn, Claus G; Mueller, Thomas; Ankersmit, Hendrik J; Haider, Thomas

    2018-06-27

    Large burn injuries induce a systemic response in affected patients. Soluble ST2 (sST2) acts as a decoy receptor for interleukin-33 (IL-33) and has immunosuppressive effects. sST2 has been described previously as a prognostic serum marker. Our aim was to evaluate serum concentrations of sST2 and IL-33 after thermal injury and elucidate whether sST2 is associated with mortality in these patients. We included 32 burn patients (total body surface area [TBSA] >10%) admitted to our burn intensive care unit and compared them to eight healthy probands. Serum concentrations of sST2 and IL-33 were measured serially using an enzyme-linked immunosorbent assay (ELISA) technique. The mean TBSA was 32.5%±19.6%. Six patients (18.8%) died during the hospital stay. Serum analyses showed significantly increased concentrations of sST2 and reduced concentrations of IL-33 in burn patients compared to healthy controls. In our study cohort, higher serum concentrations of sST2 were a strong independent predictor of mortality. Burn injuries cause an increment of sST2 serum concentrations with a concomitant reduction of IL-33. Higher concentrations of sST2 are associated with increased in-hospital mortality in burn patients.

  2. Plasma concentration of asymmetric dimethylarginine (ADMA) predicts cardiovascular morbidity and mortality in type 1 diabetic patients with diabetic nephropathy

    DEFF Research Database (Denmark)

    Lajer, Maria Stenkil; Tarnow, Lise; Jorsal, Anders

    2008-01-01

    OBJECTIVE: To investigate whether circulating asymmetric dimethylarginine (ADMA) levels are predictive of cardiovascular events, decline in glomerular filtration rate (GFR), end-stage renal disease (ESRD), and all-cause mortality in type 1 diabetic patients. RESEARCH DESIGN AND METHODS: We...... performed a prospective observational follow-up study including 397 type 1 diabetic patients with overt diabetic nephropathy (243 men aged 42.1 +/- 10.5 years, GFR 76 +/- 34 ml/min per 1.73 m(2)) and a control group of 175 patients with longstanding type 1 diabetes and persistent normoalbuminuria (104 men...... aged 42.7 +/- 9.7 years, duration of diabetes 27.7 +/- 8.3 years). Patients were followed for a median 11.3 years (range 0.0-12.9) with yearly measurements of GFR ((51)Cr-EDTA plasma clearance) in patients with diabetic nephropathy. Endpoints were fatal and nonfatal cardiovascular disease (CVD...

  3. CMAQ predicted concentration files

    Data.gov (United States)

    U.S. Environmental Protection Agency — model predicted concentrations. This dataset is associated with the following publication: Muñiz-Unamunzaga, M., R. Borge, G. Sarwar, B. Gantt, D. de la Paz, C....

  4. Predicting mortality from human faces.

    Science.gov (United States)

    Dykiert, Dominika; Bates, Timothy C; Gow, Alan J; Penke, Lars; Starr, John M; Deary, Ian J

    2012-01-01

    To investigate whether and to what extent mortality is predictable from facial photographs of older people. High-quality facial photographs of 292 members of the Lothian Birth Cohort 1921, taken at the age of about 83 years, were rated in terms of apparent age, health, attractiveness, facial symmetry, intelligence, and well-being by 12 young-adult raters. Cox proportional hazards regression was used to study associations between these ratings and mortality during a 7-year follow-up period. All ratings had adequate reliability. Concurrent validity was found for facial symmetry and intelligence (as determined by correlations with actual measures of fluctuating asymmetry in the faces and Raven Standard Progressive Matrices score, respectively), but not for the other traits. Age as rated from facial photographs, adjusted for sex and chronological age, was a significant predictor of mortality (hazard ratio = 1.36, 95% confidence interval = 1.12-1.65) and remained significant even after controlling for concurrent, objectively measured health and cognitive ability, and the other ratings. Health as rated from facial photographs, adjusted for sex and chronological age, significantly predicted mortality (hazard ratio = 0.81, 95% confidence interval = 0.67-0.99) but not after adjusting for rated age or objectively measured health and cognition. Rated attractiveness, symmetry, intelligence, and well-being were not significantly associated with mortality risk. Rated age of the face is a significant predictor of mortality risk among older people, with predictive value over and above that of objective or rated health status and cognitive ability.

  5. CMAQ predicted concentration files

    Data.gov (United States)

    U.S. Environmental Protection Agency — CMAQ predicted ozone. This dataset is associated with the following publication: Gantt, B., G. Sarwar, J. Xing, H. Simon, D. Schwede, B. Hutzell, R. Mathur, and A....

  6. Vitamin D status predicts 30 day mortality in hospitalised cats.

    Directory of Open Access Journals (Sweden)

    Helen Titmarsh

    Full Text Available Vitamin D insufficiency, defined as low serum concentrations of the major circulating form of vitamin D, 25 hydroxyvitamin D (25(OHD, has been associated with the development of numerous infectious, inflammatory, and neoplastic disorders in humans. In addition, vitamin D insufficiency has been found to be predictive of mortality for many disorders. However, interpretation of human studies is difficult since vitamin D status is influenced by many factors, including diet, season, latitude, and exposure to UV radiation. In contrast, domesticated cats do not produce vitamin D cutaneously, and most cats are fed a commercial diet containing a relatively standard amount of vitamin D. Consequently, domesticated cats are an attractive model system in which to examine the relationship between serum 25(OHD and health outcomes. The hypothesis of this study was that vitamin D status would predict short term, all-cause mortality in domesticated cats. Serum concentrations of 25(OHD, together with a wide range of other clinical, hematological, and biochemical parameters, were measured in 99 consecutively hospitalised cats. Cats which died within 30 days of initial assessment had significantly lower serum 25(OHD concentrations than cats which survived. In a linear regression model including 12 clinical variables, serum 25(OHD concentration in the lower tertile was significantly predictive of mortality. The odds ratio of mortality within 30 days was 8.27 (95% confidence interval 2.54-31.52 for cats with a serum 25(OHD concentration in the lower tertile. In conclusion, this study demonstrates that low serum 25(OHD concentration status is an independent predictor of short term mortality in cats.

  7. Genetically low vitamin D concentrations and increased mortality

    DEFF Research Database (Denmark)

    Afzal, Shoaib; Brøndum-Jacobsen, Peter; Bojesen, Stig E

    2014-01-01

    adjusted hazard ratios for a 20 nmol/L lower plasma 25-hydroxyvitamin D concentration were 1.19 (95% confidence interval 1.14 to 1.25) for all cause mortality, 1.18 (1.09 to 1.28) for cardiovascular mortality, 1.12 (1.03 to 1.22) for cancer mortality, and 1.27 (1.15 to 1.40) for other mortality. Each...... increase in DHCR7/CYP2R1 allele score was associated with a 1.9 nmol/L lower plasma 25-hydroxyvitamin D concentration and with increased all cause, cancer, and other mortality but not with cardiovascular mortality. The odds ratio for a genetically determined 20 nmol/L lower plasma 25-hydroxyvitamin D...

  8. Comparison of the Nosocomial Pneumonia Mortality Prediction (NPMP) model with standard mortality prediction tools.

    Science.gov (United States)

    Srinivasan, M; Shetty, N; Gadekari, S; Thunga, G; Rao, K; Kunhikatta, V

    2017-07-01

    Severity or mortality prediction of nosocomial pneumonia could aid in the effective triage of patients and assisting physicians. To compare various severity assessment scoring systems for predicting intensive care unit (ICU) mortality in nosocomial pneumonia patients. A prospective cohort study was conducted in a tertiary care university-affiliated hospital in Manipal, India. One hundred patients with nosocomial pneumonia, admitted in the ICUs who developed pneumonia after >48h of admission, were included. The Nosocomial Pneumonia Mortality Prediction (NPMP) model, developed in our hospital, was compared with Acute Physiology and Chronic Health Evaluation II (APACHE II), Mortality Probability Model II (MPM 72  II), Simplified Acute Physiology Score II (SAPS II), Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), Clinical Pulmonary Infection Score (CPIS), Ventilator-Associated Pneumonia Predisposition, Insult, Response, Organ dysfunction (VAP-PIRO). Data and clinical variables were collected on the day of pneumonia diagnosis. The outcome for the study was ICU mortality. The sensitivity and specificity of the various scoring systems was analysed by plotting receiver operating characteristic (ROC) curves and computing the area under the curve for each of the mortality predicting tools. NPMP, APACHE II, SAPS II, MPM 72  II, SOFA, and VAP-PIRO were found to have similar and acceptable discrimination power as assessed by the area under the ROC curve. The AUC values for the above scores ranged from 0.735 to 0.762. CPIS and MODS showed least discrimination. NPMP is a specific tool to predict mortality in nosocomial pneumonia and is comparable to other standard scores. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

  9. Prediction of mortality based on facial characteristics

    Directory of Open Access Journals (Sweden)

    Arnaud Delorme

    2016-05-01

    Full Text Available Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 seconds. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail. Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance and warrants further investigation.

  10. Mortality and indoor radon daughter concentrations in 13 Canadian cities

    International Nuclear Information System (INIS)

    Letourneau, E.G.; Wigle, D.T.

    1980-01-01

    A study was carried out to determine if lung cancer and general mortality rates in 13 Canadian cities were significantly correlated with average indoor radon daughter concentrations. The radon daughter measurements were obtained from a study of 10,000 homes chosen in a statistically valid grab sample basis. Cancer deaths by year of death, sex, age, and cause were retrieved for each of the cities for the period 1957-1976. Age specific and age standardized mortality rates were calculated. The results showed no evidence of any substantial association between general or lung cancer mortality rates and indoor radon daughter concentrations. The limitations of this study and the feasibility of a common international program of epidemiology of radon daughter exposure are discussed. A proposal is made for the use of case control studies of lung cancer to assess the relative importance of smoking, occupational and domestic exposure to radon daughters

  11. Human mortality effects of future concentrations of tropospheric ozone

    International Nuclear Information System (INIS)

    West, J.; Szopa, S.; Hauglustaine, D.A.

    2007-01-01

    Here we explore the effects of projected future changes in global ozone concentrations on premature human mortality, under three scenarios for 2030. We use daily surface ozone concentrations from a global atmospheric transport and chemistry model, and ozone-mortality relationships from daily time-series studies. The population-weighted annual average 8-h daily maximum ozone is projected to increase, relative to the present, in each of ten world regions under the SRES A2 scenario and the current legislation (CLE) scenario, with the largest growth in tropical regions, while decreases are projected in each region in the maximum feasible reduction (MFR) scenario. Emission reductions in the CLE scenario, relative to A2, are estimated to reduce about 190,000 premature human mortalities globally in 2030, with the most avoided mortalities in Africa. The MFR scenario will avoid about 460,000 premature mortalities relative to A2 in 2030, and 270,000 relative to CLE, with the greatest reductions in South Asia. (authors)

  12. Validation of the mortality prediction equation for damage control ...

    African Journals Online (AJOL)

    , preoperative lowest pH and lowest core body temperature to derive an equation for the purpose of predicting mortality in damage control surgery. It was shown to reliably predict death despite damage control surgery. The equation derivation ...

  13. Review of avian mortality studies at concentrating solar power plants

    Science.gov (United States)

    Ho, Clifford K.

    2016-05-01

    This paper reviews past and current avian mortality studies at concentrating solar power (CSP) plants and facilities including Solar One in California, the Solar Energy Development Center in Israel, Ivanpah Solar Electric Generating System in California, Crescent Dunes in Nevada, and Gemasolar in Spain. Findings indicate that the leading causes of bird deaths at CSP plants are from collisions (primarily with reflective surfaces; i.e., heliostats) and singeing caused by concentrated solar flux. Safe irradiance levels for birds have been reported to range between 4 and 50 kW/m2. Above these levels, singeing and irreversible damage to the feathers can occur. Despite observations of large numbers of "streamers" in concentrated flux regions and reports that suggest these streamers indicate complete vaporization of birds, analyses in this paper show that complete vaporization of birds is highly improbable, and the observed streamers are likely due to insects flying into the concentrated flux. The levelized avian mortality rate during the first year of operation at Ivanpah was estimated to be 0.7 - 3.5 fatalities per GWh, which is less than the levelized avian mortality reported for fossil fuel plants but greater than that for nuclear and wind power plants. Mitigation measures include acoustic, visual, tactile, and chemosensory deterrents to keep birds away from the plant, and heliostat aiming strategies that reduce the solar flux during standby.

  14. Tree mortality predicted from drought-induced vascular damage

    Science.gov (United States)

    Anderegg, William R.L.; Flint, Alan L.; Huang, Cho-ying; Flint, Lorraine E.; Berry, Joseph A.; Davis, Frank W.; Sperry, John S.; Field, Christopher B.

    2015-01-01

    The projected responses of forest ecosystems to warming and drying associated with twenty-first-century climate change vary widely from resiliency to widespread tree mortality1, 2, 3. Current vegetation models lack the ability to account for mortality of overstorey trees during extreme drought owing to uncertainties in mechanisms and thresholds causing mortality4, 5. Here we assess the causes of tree mortality, using field measurements of branch hydraulic conductivity during ongoing mortality in Populus tremuloides in the southwestern United States and a detailed plant hydraulics model. We identify a lethal plant water stress threshold that corresponds with a loss of vascular transport capacity from air entry into the xylem. We then use this hydraulic-based threshold to simulate forest dieback during historical drought, and compare predictions against three independent mortality data sets. The hydraulic threshold predicted with 75% accuracy regional patterns of tree mortality as found in field plots and mortality maps derived from Landsat imagery. In a high-emissions scenario, climate models project that drought stress will exceed the observed mortality threshold in the southwestern United States by the 2050s. Our approach provides a powerful and tractable way of incorporating tree mortality into vegetation models to resolve uncertainty over the fate of forest ecosystems in a changing climate.

  15. Factors predicting mortality in elderly patients admitted to a ...

    African Journals Online (AJOL)

    The median age was 70 years (interquartile range 67 - 75 years). The overall ICU mortality was 44.7%, and 64% of deaths occurred within 5 days of admission. On univariate analysis, the factors predicting mortality were alcohol misuse (p=0.09), pneumonia (p.0.001), shock (p=0.001), dehydration (p=0.007), urine output ...

  16. New social adaptability index predicts overall mortality.

    Science.gov (United States)

    Goldfarb-Rumyantzev, Alexander; Barenbaum, Anna; Rodrigue, James; Rout, Preeti; Isaacs, Ross; Mukamal, Kenneth

    2011-08-01

    Definitions of underprivileged status based on race, gender and geographic location are neither sensitive nor specific; instead we proposed and validated a composite index of social adaptability (SAI). Index of social adaptability was calculated based on employment, education, income, marital status, and substance abuse, each factor contributing from 0 to 3 points. Index of social adaptability was validated in NHANES-3 by association with all-cause and cause-specific mortality. Weighted analysis of 19,593 subjects demonstrated mean SAI of 8.29 (95% CI 8.17-8.40). Index of social adaptability was higher in Whites, followed by Mexican-Americans and then the African-American population (ANOVA, p adaptability with a strong association with mortality, which can be used to identify underprivileged populations at risk of death.

  17. Various scoring systems for predicting mortality in Intensive Care Unit

    African Journals Online (AJOL)

    2015-12-07

    Dec 7, 2015 ... Mortality rate was higher in patients admitted from wards other than surgery ... evaluate the predictability of various severity of illness scores, and ..... Livingston BM, MacKirdy FN, Howie JC, Jones R, Norrie JD. Assessment of.

  18. Interpretable Topic Features for Post-ICU Mortality Prediction.

    Science.gov (United States)

    Luo, Yen-Fu; Rumshisky, Anna

    2016-01-01

    Electronic health records provide valuable resources for understanding the correlation between various diseases and mortality. The analysis of post-discharge mortality is critical for healthcare professionals to follow up potential causes of death after a patient is discharged from the hospital and give prompt treatment. Moreover, it may reduce the cost derived from readmissions and improve the quality of healthcare. Our work focused on post-discharge ICU mortality prediction. In addition to features derived from physiological measurements, we incorporated ICD-9-CM hierarchy into Bayesian topic model learning and extracted topic features from medical notes. We achieved highest AUCs of 0.835 and 0.829 for 30-day and 6-month post-discharge mortality prediction using baseline and topic proportions derived from Labeled-LDA. Moreover, our work emphasized the interpretability of topic features derived from topic model which may facilitates the understanding and investigation of the complexity between mortality and diseases.

  19. Osteoporosis-Related Mortality: Time-Trends and Predictive Factors

    Directory of Open Access Journals (Sweden)

    Nelly Ziadé

    2014-07-01

    Full Text Available Osteoporosis is one of the leading causes of handicap worldwide and a major contributor to the global burden of diseases. In particular, osteoporosis is associated with excess mortality. We reviewed the impact of osteoporosis on mortality in a population by defining three categories: mortality following hip fractures, mortality following other sites of fractures, and mortality associated with low bone mineral density (BMD. Hip fractures, as well as other fractures at major sites are all associated with excess mortality, except at the forearm site. This excess mortality is higher during the first 3-6 months after the fracture and then declines over time, but remains higher than the mortality of the normal population up to 22 years after the fracture. Low BMD is also associated with high mortality, with hazard ratios of around 1.3 for every decrease in 1 standard deviation of bone density at 5 years, independently of fractures, reflecting a more fragile population. Finally predictors of mortality were identified and categorised in demographic known factors (age and male gender and in factors reflecting a poor general health status such as the number of comorbidities, low mental status, or level of social dependence. Our results indicate that the management of a patient with osteoporosis should include a multivariate approach that could be based on predictive models in the future.

  20. Poor Semen Quality Predicts Increased Mortality

    DEFF Research Database (Denmark)

    Jensen, Tina Kold; Bostofte, Erik; Jacobsen, Rune

    Objective: Over recent decades a possible decrease in semen quality and an increase in the incidence of testicular cancer have been reported. In addition, men with poor semen quality have been reported to be at increased risk of developing testicular cancer whereas the risk of other cancers...... is not increased. The long-term survival of men with poor semen quality is, however, unknown. We therefore studied the associations between semen characteristics and subsequent mortality. Back to Top Material and Methods: The Copenhagen Sperm Analysis Laboratory is one of several public semen analysis laboratories...... in Denmark and examines semen samples mostly from men in the area of Copenhagen. Men are referred to the clinic by general practitioners and urologists, and the investigations are paid for through the public health system. A total of 34.442 men had a semen analysis done at the laboratory during 1963 to 1995...

  1. Anxiety Predicts Mortality in ICD Patients

    DEFF Research Database (Denmark)

    Kikkenborg Berg, Selina; Caspar Thygesen, Lau; Hastrup Svendsen, Jesper

    2014-01-01

    BACKGROUND: Although highly effective in preventing arrhythmic death, patients receiving an implantable cardioverter defibrillator (ICD) may still experience psychological difficulties such as anxiety, depression, and reduced quality of life. The objectives of this study were to describe patient...... receiving ICD between January 1, 2011 and June 30, 2011 (n = 499). The following instruments were used: SF-36, Hospital Anxiety and Depression Scale, HeartQoL, EQ-5D, and the Multidimensional Fatigue Inventory. RESULTS: The response rate was 72%. Mean age was 65.5 years and 82% patients were males. Fifty...... of perceived health, quality of life, and fatigue; for example, physical health 39.8 versus 44.3 points, compared to secondary prevention indication. Anxiety, poor perceived health, fatigue, and low quality of life were all predictors of mortality, anxiety being the strongest with an adjusted odds ratio of 4...

  2. Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities

    International Nuclear Information System (INIS)

    Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

    2016-01-01

    Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM_1_0) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM_1_0-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM_1_0-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM_1_0 concentration and green space per capita could best explain the heterogeneity in PM_1_0-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. - Highlights: • The heterogeneity was examined in PM_1_0-mortality associations among Chinese cities. • Temperature, PM_1_0 and green space could best explain the heterogeneity. • PM_1_0-mortality associations were predicted for 73 Chinese cities. - This study provides a practical way to assess exposure-response associations and evaluate the burden of mortality in areas with insufficient data.

  3. Magnitude of bacteraemia predicts one-year mortality

    DEFF Research Database (Denmark)

    Gradel, Kim Oren; Schønheyder, Henrik Carl; Søgaard, Mette

    Objectives: All hospitals in our region use the BacT/Alert® blood culture (BC) system with a 3-bottle BC set for adults. We hypothesized that the magnitude of bacteremia (i.e., number of positive bottles in the initial BC set) predicted one-year mortality. Methods In a population-based study we...... with a BC index of 1 (i.e., one positive bottle) were chosen as the reference group. We computed Kaplan-Meier curves and performed Cox regression analyses to estimate mortality rate ratios (MRRs) with 95 % confidence intervals [CIs] 30 and 365 days after the initial BC sampling date, first in crude analyses...... mortality....

  4. Prediction Methods for Blood Glucose Concentration

    DEFF Research Database (Denmark)

    “Recent Results on Glucose–Insulin Predictions by Means of a State Observer for Time-Delay Systems” by Pasquale Palumbo et al. introduces a prediction model which in real time predicts the insulin concentration in blood which in turn is used in a control system. The method is tested in simulation...... EEG signals to predict upcoming hypoglycemic situations in real-time by employing artificial neural networks. The results of a 30-day long clinical study with the implanted device and the developed algorithm are presented. The chapter “Meta-Learning Based Blood Glucose Predictor for Diabetic......, but the insulin amount is chosen using factors that account for this expectation. The increasing availability of more accurate continuous blood glucose measurement (CGM) systems is attracting much interest to the possibilities of explicit prediction of future BG values. Against this background, in 2014 a two...

  5. [Prediction of mortality in patients with acute hepatic failure].

    Science.gov (United States)

    Eremeeva, L F; Berdnikov, A P; Musaeva, T S; Zabolotskikh, I B

    2013-01-01

    The article deals with a study of 243 patients (from 18 to 65 years old) with acute hepatic failure. Purpose of the study was to evaluate the predictive capability of severity scales APACHE III, SOFA, MODS, Child-Pugh and to identify mortality predictors in patients with acute hepatic failure. Results; The best predictive ability in patients with acute hepatic failure and multiple organ failure had APACHE III and SOFA scales. The strongest mortality predictors were: serum creatinine > 132 mmol/L, fibrinogen < 1.4 g/L, Na < 129 mmol/L.

  6. Functional status and mortality prediction in community-acquired pneumonia.

    Science.gov (United States)

    Jeon, Kyeongman; Yoo, Hongseok; Jeong, Byeong-Ho; Park, Hye Yun; Koh, Won-Jung; Suh, Gee Young; Guallar, Eliseo

    2017-10-01

    Poor functional status (FS) has been suggested as a poor prognostic factor in both pneumonia and severe pneumonia in elderly patients. However, it is still unclear whether FS is associated with outcomes and improves survival prediction in community-acquired pneumonia (CAP) in the general population. Data on hospitalized patients with CAP and FS, assessed by the Eastern Cooperative Oncology Group (ECOG) scale were prospectively collected between January 2008 and December 2012. The independent association of FS with 30-day mortality in CAP patients was evaluated using multivariable logistic regression. Improvement in mortality prediction when FS was added to the CRB-65 (confusion, respiratory rate, blood pressure and age 65) score was evaluated for discrimination, reclassification and calibration. The 30-day mortality of study participants (n = 1526) was 10%. Mortality significantly increased with higher ECOG score (P for trend <0.001). In multivariable analysis, ECOG ≥3 was strongly associated with 30-day mortality (adjusted OR: 5.70; 95% CI: 3.82-8.50). Adding ECOG ≥3 significantly improved the discriminatory power of CRB-65. Reclassification indices also confirmed the improvement in discrimination ability when FS was combined with the CRB-65, with a categorized net reclassification index (NRI) of 0.561 (0.437-0.686), a continuous NRI of 0.858 (0.696-1.019) and a relative integrated discrimination improvement in the discrimination slope of 139.8 % (110.8-154.6). FS predicted 30-day mortality and improved discrimination and reclassification in consecutive CAP patients. Assessment of premorbid FS should be considered in mortality prediction in patients with CAP. © 2017 Asian Pacific Society of Respirology.

  7. Bone Marrow Pathology Predicts Mortality in Chronic Hemodialysis Patients

    Directory of Open Access Journals (Sweden)

    Cheng-Hao Weng

    2015-01-01

    Full Text Available Introduction. A bone marrow biopsy is a useful procedure for the diagnosis and staging of various hematologic and systemic diseases. The objective of this study was to investigate whether the findings of bone marrow studies can predict mortality in chronic hemodialysis patients. Methods. Seventy-eight end-stage renal disease patients on maintenance hemodialysis underwent bone marrow biopsies between 2000 and 2011, with the most common indication being unexplained anemia followed by unexplained leukocytosis and leukopenia. Results. The survivors had a higher incidence of abnormal megakaryocyte distribution P=0.001, band and segmented cells P=0.021, and lymphoid cells P=0.029 than the nonsurvivors. The overall mortality rate was 38.5% (30/78, and the most common cause of mortality was sepsis (83.3% followed by respiratory failure (10%. In multivariate Cox regression analysis, both decreased (OR 3.714, 95% CI 1.671–8.253, P=0.001 and absent (OR 9.751, 95% CI 2.030–45.115, P=0.004 megakaryocyte distribution (normal megakaryocyte distribution as the reference group, as well as myeloid/erythroid ratio (OR 1.054, CI 1.012–1.098, P=0.011, were predictive of mortality. Conclusion. The results of a bone marrow biopsy can be used to assess the pathology, and, in addition, myeloid/erythroid ratio and abnormal megakaryocyte distribution can predict mortality in chronic hemodialysis patients.

  8. Cholecystokinin in plasma predicts cardiovascular mortality in elderly females

    DEFF Research Database (Denmark)

    Gøtze, Jens P.; Rehfeld, Jens F; Alehagen, Urban

    2016-01-01

    BACKGROUND: Cholecystokinin (CCK) and gastrin are related gastrointestinal hormones with documented cardiovascular effects of exogenous administration. It is unknown whether measurement of endogenous CCK or gastrin in plasma contains information regarding cardiovascular mortality. METHODS......: Mortality risk was evaluated using Cox proportional hazard regression and Kaplan-Meier analyses. Elderly patients in a primary care setting with symptoms of cardiac disease, i.e. shortness of breath, peripheral edema, and/or fatigue, were evaluated (n=470). Primary care patients were followed for 13years...... information was obtained from 4th quartile gastrin concentrations on 5-year cardiovascular mortality risk. CONCLUSIONS: CCK in plasma is an independent marker of cardiovascular mortality in elderly female patients. The study thus introduces measurement of plasma CCK in gender-specific cardiovascular risk...

  9. A Modified APACHE II Score for Predicting Mortality of Variceal ...

    African Journals Online (AJOL)

    Conclusion: Modified APACHE II score is effective in predicting outcome of patients with variceal bleeding. Score of L 15 points and long ICU stay are associated with high mortality. Keywords: liver cirrhosis, periportal fibrosis, portal hypertension, schistosomiasis udan Journal of Medical Sciences Vol. 2 (2) 2007: pp. 105- ...

  10. Probabilistic fuzzy prediction of mortality in intensive care units

    NARCIS (Netherlands)

    Fialho, A.T.S.; Kaymak, U.; Almeida, R.J.; Cismondi, F.; Vieira, S.M.; Reti, S.R.; Costa Sousa, da J.M.; Finkelstein, S.N.; Bouchon-Meunier, B.

    2012-01-01

    In the present work, we propose the application of probabilistic fuzzy systems (PFS) to model the prediction of mortality in septic shock patients. This technique is characterized by the combination of the linguistic description of the system with the statistical properties of data. Preliminary

  11. Predicting mortality for five California conifers following wildfire

    Science.gov (United States)

    Sharon M. Hood; Sheri L. Smith; Daniel R. Cluck

    2010-01-01

    Fire injury was characterized and survival monitored for 5677 trees >25cm DBH from five wildfires in California that occurred between 2000 and 2004. Logistic regression models for predicting the probability of mortality 5-years after fire were developed for incense cedar (Calocedrus decurrens (Torr.) Florin), white fir (Abies concolor (Gord. & Glend.) Lindl. ex...

  12. Predictive indications of operation and mortality following renal trauma

    Directory of Open Access Journals (Sweden)

    Chia-Shen Yang

    2012-01-01

    Conclusion: In conclusion, ISS ≥ 16 and RIS ≥ 4 are predictive factors for necessitating an operation, and higher injury severity (ISS ≥ 16 and lower consciousness level (GCS < 8 scores are significantly associated with mortality after renal trauma.

  13. Predicting mortality in patients with heart failure : a pragmatic approach

    NARCIS (Netherlands)

    Bouvy, ML; Heerdink, ER; Leufkens, HGM; Hoes, AW

    Objective: To develop a comprehensive and easily applicable prognostic model predicting mortality risk in patients with moderate to severe heart failure. Design: Prospective follow up study. Setting: Seven general hospitals in the Netherlands. Patients: 152 outpatients with heart failure or patients

  14. Predicting the mortality in geriatric patients with dengue fever

    Science.gov (United States)

    Huang, Hung-Sheng; Hsu, Chien-Chin; Ye, Je-Chiuan; Su, Shih-Bin; Huang, Chien-Cheng; Lin, Hung-Jung

    2017-01-01

    Abstract Geriatric patients have high mortality for dengue fever (DF); however, there is no adequate method to predict mortality in geriatric patients. Therefore, we conducted this study to develop a tool in an attempt to address this issue. We conducted a retrospective case–control study in a tertiary medical center during the DF outbreak in Taiwan in 2015. All the geriatric patients (aged ≥65 years) who visited the study hospital between September 1, 2015, and December 31, 2015, were recruited into this study. Variables included demographic data, vital signs, symptoms and signs, comorbidities, living status, laboratory data, and 30-day mortality. We investigated independent mortality predictors by univariate analysis and multivariate logistic regression analysis and then combined these predictors to predict the mortality. A total of 627 geriatric DF patients were recruited, with a mortality rate of 4.3% (27 deaths and 600 survivals). The following 4 independent mortality predictors were identified: severe coma [Glasgow Coma Scale: ≤8; adjusted odds ratio (AOR): 11.36; 95% confidence interval (CI): 1.89–68.19], bedridden (AOR: 10.46; 95% CI: 1.58–69.16), severe hepatitis (aspartate aminotransferase >1000 U/L; AOR: 96.08; 95% CI: 14.11–654.40), and renal failure (serum creatinine >2 mg/dL; AOR: 6.03; 95% CI: 1.50–24.24). When we combined the predictors, we found that the sensitivity, specificity, positive predictive value, and negative predictive value for patients with 1 or more predictors were 70.37%, 88.17%, 21.11%, and 98.51%, respectively. For patients with 2 or more predictors, the respective values were 33.33%, 99.44%, 57.14%, and 98.51%. We developed a new method to help decision making. Among geriatric patients with none of the predictors, the survival rate was 98.51%, and among those with 2 or more predictors, the mortality rate was 57.14%. This method is simple and useful, especially in an outbreak. PMID:28906367

  15. Monitoring of the newborn dog and prediction of neonatal mortality.

    Science.gov (United States)

    Mila, Hanna; Grellet, Aurélien; Delebarre, Marine; Mariani, Claire; Feugier, Alexandre; Chastant-Maillard, Sylvie

    2017-08-01

    Despite the high neonatal mortality rate in puppies, pertinent criteria for health evaluation of the newborns are not defined. This study was thus designed to measure and to characterize factors of variation of six health parameters in dog neonates, and to evaluate their value as predictors of neonatal mortality. A total of 347 purebred puppies under identical conditions of housing and management were examined within the first 8h after birth and then at Day 1. The first health evaluation included Apgar score, weight, blood glucose, lactate and β-hydroxybutyrate concentration, rectal temperature and urine specific gravity (SG). The second evaluation at Day 1 included the same parameters, excluding Apgar score and weight. The mortality rate over the first 24h and over 21days of age was recorded. The early predictors of neonatal mortality in the dog were determined with generalized linear mixed models and receiver operating characteristic curves analyses. An Apgar score at or below 6 evaluated within the first 8h after birth was found associated with a higher risk of death during the first 24h. A reduced glucose concentration (≤92mg/dl) at Day 1 was found to be associated with higher mortality between 1 and 21days of age. Low-birth-weight puppies were characterized by both low viability (low Apgar score) and low blood glucose concentration, and thus were found indirectly at higher risk of neonatal mortality. This study promotes two low cost easy-to-use tests for health evaluation in puppies, i.e. Apgar scoring and blood glucose assay. Further investigation is necessary to establish if the strong relationship between blood glucose and neonatal survival reflects high energy requirements or other benefits from colostrum intake. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  16. Projecting future summer mortality due to ambient ozone concentration and temperature changes

    Science.gov (United States)

    Lee, Jae Young; Lee, Soo Hyun; Hong, Sung-Chul; Kim, Ho

    2017-05-01

    Climate change is known to affect the human health both directly by increased heat stress and indirectly by altering environments, particularly by altering the rate of ambient ozone formation in the atmosphere. Thus, the risks of climate change may be underestimated if the effects of both future temperature and ambient ozone concentrations are not considered. This study presents a projection of future summer non-accidental mortality in seven major cities of South Korea during the 2020s (2016-2025) and 2050s (2046-2055) considering changes in temperature and ozone concentration, which were predicted by using the HadGEM3-RA model and Integrated Climate and Air Quality Modeling System, respectively. Four Representative Concentration Pathway (RCP) scenarios (RCP 2.6, 4.5, 6.0, and 8.5) were considered. The result shows that non-accidental summer mortality will increase by 0.5%, 0.0%, 0.4%, and 0.4% in the 2020s, 1.9%, 1.5%, 1.2%, and 4.4% in the 2050s due to temperature change compared to the baseline mortality during 2001-2010, under RCP 2.6, 4.5, 6.0, and 8.5, respectively, whereas the mortality will increase by 0.0%, 0.5%, 0.0%, and 0.5% in the 2020s, and 0.2%, 0.2%, 0.4%, and 0.6% in the 2050s due to ozone concentration change. The projection result shows that the future summer morality in South Korea is increased due to changes in both temperature and ozone, and the magnitude of ozone-related increase is much smaller than that of temperature-related increase, especially in the 2050s.

  17. Prediction Methods for Blood Glucose Concentration

    DEFF Research Database (Denmark)

    -day workshop on the design, use and evaluation of prediction methods for blood glucose concentration was held at the Johannes Kepler University Linz, Austria. One intention of the workshop was to bring together experts working in various fields on the same topic, in order to shed light from different angles...... discussions which allowed to receive direct feedback from the point of view of different disciplines. This book is based on the contributions of that workshop and is intended to convey an overview of the different aspects involved in the prediction. The individual chapters are based on the presentations given...... in the process of writing this book: All authors for their individual contributions, all reviewers of the book chapters, Daniela Hummer for the entire organization of the workshop, Boris Tasevski for helping with the typesetting, Florian Reiterer for his help editing the book, as well as Oliver Jackson and Karin...

  18. Lung cancer mortality in European women: trends and predictions.

    Science.gov (United States)

    Bosetti, Cristina; Malvezzi, Matteo; Rosso, Tiziana; Bertuccio, Paola; Gallus, Silvano; Chatenoud, Liliane; Levi, Fabio; Negri, Eva; La Vecchia, Carlo

    2012-12-01

    Female lung cancer mortality increased by 50% between the mid 1960s and the early 2000s in the European Union (EU). To monitor the current lung cancer epidemic in European women, we analyzed mortality trends in 33 European countries between 1970 and 2009 and estimated rates for the year 2015 using data from the World Health Organization. Female lung cancer mortality has been increasing up to recent calendar years in most European countries, with the exceptions of Belarus, Russia, and Ukraine, with relatively low rates, and the UK, Iceland and Ireland, where high rates were reached in mid/late 1990s to leveled off thereafter. In the EU, female lung cancer mortality rates rose over the last decade from 11.3 to 12.7/100,000 (+2.3% per year) at all ages and from 18.6 to 21.5/100,000 (+3.0% per year) in middle-age. A further increase is predicted, to reach 14/100,000 women in 2015. Lung cancer mortality trends have been more favorable over the last decade in young women (20-44 years), particularly in the UK and other former high-risk countries from northern and central/eastern Europe, but also in France, Italy, and Spain where mortality in young women has been increasing up to the early 2000s. In the EU as a whole, mortality at age 20-44 years decreased from 1.6 to 1.4/100,000 (-2.2% per year). Although the female lung cancer epidemic in Europe is still expanding, the epidemic may be controlled through the implementation of effective anti-tobacco measures, and it will probably never reach the top US rates. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  19. Periodontitis in older Swedish individuals fails to predict mortality.

    Science.gov (United States)

    Renvert, Stefan; Wallin-Bengtsson, Viveca; Berglund, Johan; Persson, Rutger G

    2015-03-01

    This study aims to assess mortality risk and its association to health aspects in dentate individuals 60 years of age and older. Medical and periodontal data from 870 dentate individuals (age range 60–96) participating in the Swedish National Study on Aging and Care in Blekinge (SNACBlekinge)with survival statistics over 6 years were studied. During 6 years of follow-up, 42/474 of the individuals(8.9 %), who at baseline were between age 60 and 75, and 134/396 individuals of the individuals (33.9 %), who at baseline were ≥75 years, died. Surviving dentate individuals had more teeth (mean 19.3, S.D.±7.9) than those who died (mean 15.9,S.D.±7.3; mean diff 3,3; S.E. mean diff 0.7; 95 % CI 2.0, 4.6;p=0.001). A self-reported history of high blood pressure (F=15.0, pheart failure (F=24.5, pheart disease, diabetes, any form of cancer,or periodontitis failed to predict mortality. A self-reported history of angina pectoris, chronic heart failure, elevated serum HbA1c, and few remaining teeth were associated with mortality risk. A professional diagnosis of cardiovascular disease, diabetes, cancer, or periodontitis was not predictive of mortality. Self-health reports are important to observe in the assessment of disease and survival in older individual.

  20. Predicting Early Mortality After Hip Fracture Surgery: The Hip Fracture Estimator of Mortality Amsterdam.

    Science.gov (United States)

    Karres, Julian; Kieviet, Noera; Eerenberg, Jan-Peter; Vrouenraets, Bart C

    2018-01-01

    Early mortality after hip fracture surgery is high and preoperative risk assessment for the individual patient is challenging. A risk model could identify patients in need of more intensive perioperative care, provide insight in the prognosis, and allow for risk adjustment in audits. This study aimed to develop and validate a risk prediction model for 30-day mortality after hip fracture surgery: the Hip fracture Estimator of Mortality Amsterdam (HEMA). Data on 1050 consecutive patients undergoing hip fracture surgery between 2004 and 2010 were retrospectively collected and randomly split into a development cohort (746 patients) and validation cohort (304 patients). Logistic regression analysis was performed in the development cohort to determine risk factors for the HEMA. Discrimination and calibration were assessed in both cohorts using the area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow goodness-of-fit test, and by stratification into low-, medium- and high-risk groups. Nine predictors for 30-day mortality were identified and used in the final model: age ≥85 years, in-hospital fracture, signs of malnutrition, myocardial infarction, congestive heart failure, current pneumonia, renal failure, malignancy, and serum urea >9 mmol/L. The HEMA showed good discrimination in the development cohort (AUC = 0.81) and the validation cohort (AUC = 0.79). The Hosmer-Lemeshow test indicated no lack of fit in either cohort (P > 0.05). The HEMA is based on preoperative variables and can be used to predict the risk of 30-day mortality after hip fracture surgery for the individual patient. Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

  1. Can the Obesity Surgery Mortality Risk Score predict postoperative complications other than mortality?

    Science.gov (United States)

    Major, Piotr; Wysocki, Michał; Pędziwiatr, Michał; Małczak, Piotr; Pisarska, Magdalena; Migaczewski, Marcin; Winiarski, Marek; Budzyński, Andrzej

    2016-01-01

    Laparoscopic sleeve gastrectomy (LSG) and laparoscopic Roux-en-Y gastric bypass (LRYGB) are bariatric procedures with acceptable risk of postoperative morbidities and mortalities, but identification of high-risk patients is an ongoing issue. DeMaria et al. introduced the Obesity Surgery Mortality Risk Score (OS-MRS), which was designed for mortality risk assessment but not perioperative morbidity risk. To assess the possibility to use the OS-MRS to predict the risk of perioperative complications related to LSG and LRYGB. Retrospective analysis of patients operated on for morbid obesity was performed. Patients were evaluated before and after surgery. We included 408 patients (233 LSG, 175 LRYGB). Perioperative complications were defined as adverse effects in the 30-day period. The Clavien-Dindo scale was used for description of complications. Patients were assigned to five grades and three classes according to the OS-MRS results, then risk of morbidity was analyzed. Complications were observed in 30 (7.35%) patients. Similar morbidity was related to both procedures (OR = 1.14, 95% CI: 0.53-2.44, p = 0.744). The reoperation and mortality rates were 1.23% and 0.49% respectively. There were no significant differences in median OS-MRS value between the group without and the group with perioperative complications. There were no significant differences in OS-MRS between groups (p = 0.091). Obesity Surgery Mortality Risk Score was not related to Clavien-Dindo grades (p = 0.800). It appears that OS-MRS is not useful in predicting risk of perioperative morbidity after bariatric procedures.

  2. Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities.

    Science.gov (United States)

    Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

    2016-01-01

    Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. A low serum bicarbonate concentration as a risk factor for mortality in peritoneal dialysis patients.

    Directory of Open Access Journals (Sweden)

    Tae Ik Chang

    Full Text Available BACKGROUND AND AIM: Metabolic acidosis is common in patients with chronic kidney disease and is associated with increased mortality in hemodialysis patients. However, this relationship has not yet been determined in peritoneal dialysis (PD patients. METHODS: This prospective observational study included a total of 441 incident patients who started PD between January 2000 and December 2005. Using time-averaged serum bicarbonate (TA-Bic levels, we aimed to investigate whether a low serum bicarbonate concentration can predict mortality in these patients. RESULTS: Among the baseline parameters, serum bicarbonate level was positively associated with hemoglobin level and residual glomerular filtration rate (GFR, while it was negatively associated with albumin, C-reactive protein (CRP levels, peritoneal Kt/V urea, and normalized protein catabolic rate (nPCR in a multivariable linear regression analysis. During a median follow-up of 34.8 months, 149 deaths were recorded. After adjustment for age, diabetes, coronary artery disease, serum albumin, ferritin, CRP, residual GFR, peritoneal Kt/V urea, nPCR, and percentage of lean body mass, TA-Bic level was associated with a significantly decreased risk of mortality (HR per 1 mEq/L increase, 0.83; 95% CI, 0.76-0.91; p < 0.001. In addition, compared to patients with a TA-Bic level of 24-26 mEq/L, those with a TA-Bic level < 22 and between 22-24 mEq/L conferred a 13.10- and 2.13-fold increased risk of death, respectively. CONCLUSIONS: This study showed that a low serum bicarbonate concentration is an independent risk factor for mortality in PD patients. This relationship between low bicarbonate levels and adverse outcome could be related to enhanced inflammation and a more rapid loss of RRF associated with metabolic acidosis. Large randomized clinical trials to correct acidosis are warranted to confirm our findings.

  4. Moving from measuring to predicting bycatch mortality: predicting the capture condition of a longline-caught pelagic shark

    Directory of Open Access Journals (Sweden)

    Derek Richard Dapp

    2016-01-01

    Full Text Available Incidental fisheries capture has been identified as having a major effect on shark populations throughout the world. However, factors that contribute to the mortality of shark bycatch during fisheries capture are not fully understood. Here, we investigated the effects of capture duration, sea surface temperature, and shark total length (snout to the tip of the upper caudal lobe on the physiology and condition of longline-caught bronze whalers, Carcharhinus brachyurus. Plasma lactate and potassium concentration had a positive linear relationship with capture duration, indicating that this species experiences increasing physiological challenges while on fishing gear. Additionally, we used stereotype logistic regression models to determine variables that could predict the capture condition of sharks (categorized as healthy, sluggish, or moribund or dead. In these models, elevated plasma lactate concentration, plasma potassium concentration, and capture duration increased the likelihood of C. brachyurus being captured in a sluggish condition or in a moribund or dead condition. After plasma lactate concentration exceeded 27.4 mmol/L, plasma potassium concentration exceeded 8.3 mmol/L, or capture durations exceeded 293 minutes, the majority of captured sharks (>50% were predicted to be moribund or dead. We recommend that a reduction in the amount of time longlines are left fishing (soak time will reduce immediate and post-release mortality in C. brachyurus bycatch and that our methods could be applied to identify causes of fisheries-induced mortality in future studies. The identification of operational, environmental, and biological variables contributing to poor condition will be necessary to implement conservation strategies that reduce mortality during capture.

  5. Acute aluminium phosphide poisoning: Can we predict mortality?

    Directory of Open Access Journals (Sweden)

    Ashu Mathai

    2010-01-01

    Full Text Available In India, acute aluminium phosphide poisoning (AAlPP is a serious health care problem. This study aimed to determine the characteristics of AAlPP and the predictors of mortality at the time of patients′ admission. We studied consecutive admissions of patients with AAlPP admitted to the intensive care unit (ICU between November 2004 and October 2006. We noted 38 parameters at admission to the hospital and the ICU and compared survivor and non-survivor groups. A total of 27 patients were enrolled comprising5 females and 22 males and the mean ingested dose of poison was 0.75 ± 0.745 grams. Hypotension was noted in 24 patients (89% at admission and electrocardiogram abnormalities were noted in 13 patients (48.1%. The mean pH on admission was 7.20 ± 0.14 and the mean bicarbonate concentration was 12.32 ± 5.45 mmol/ L. The mortality from AAlPP was 59.3%. We found the following factors to be associated with an increased risk of mortality: a serum creatinine concentration of more than 1.0 mg % (P = 0.01, pH value less than 7.2 (P = 0.014, serum bicarbonate value less than 15 mmol/L (P = 0.048, need for mechanical ventilation (P = 0.045, need for vasoactive drugs like dobutamine (P = 0.027 and nor adrenaline (P = 0.048 and a low APACHE II score at admission (P = 0.019. AAlPP causes high mortality primarily due to early haemodynamic failure and multi-organ dysfunction

  6. Measured glomerular filtration rate does not improve prediction of mortality by cystatin C and creatinine.

    Science.gov (United States)

    Sundin, Per-Ola; Sjöström, Per; Jones, Ian; Olsson, Lovisa A; Udumyan, Ruzan; Grubb, Anders; Lindström, Veronica; Montgomery, Scott

    2017-04-01

    Cystatin C may add explanatory power for associations with mortality in combination with other filtration markers, possibly indicating pathways other than glomerular filtration rate (GFR). However, this has not been firmly established since interpretation of associations independent of measured GFR (mGFR) is limited by potential multicollinearity between markers of GFR. The primary aim of this study was to assess associations between cystatin C and mortality, independent of mGFR. A secondary aim was to evaluate the utility of combining cystatin C and creatinine to predict mortality risk. Cox regression was used to assess the associations of cystatin C and creatinine with mortality in 1157 individuals referred for assessment of plasma clearance of iohexol. Since cystatin C and creatinine are inversely related to mGFR, cystatin C - 1 and creatinine - 1 were used. After adjustment for mGFR, lower cystatin C - 1 (higher cystatin C concentration) and higher creatinine - 1 (lower creatinine concentration) were independently associated with increased mortality. When nested models were compared, avoiding the potential influence of multicollinearity, the independence of the associations was supported. Among models combining the markers of GFR, adjusted for demographic factors and comorbidity, cystatin C - 1 and creatinine - 1 combined explained the largest proportion of variance in associations with mortality risk ( R 2  = 0.61). Addition of mGFR did not improve the model. Our results suggest that both creatinine and cystatin C have independent associations with mortality not explained entirely by mGFR and that mGFR does not offer a more precise mortality risk assessment than these endogenous filtration markers combined. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  7. Diagnosis trajectories of prior multi-morbidity predict sepsis mortality

    DEFF Research Database (Denmark)

    Beck, Mette Kristina; Jensen, Anders Boeck; Nielsen, Annelaura Bach

    2016-01-01

    Sepsis affects millions of people every year, many of whom will die. In contrast to current survival prediction models for sepsis patients that primarily are based on data from within-admission clinical measurements (e.g. vital parameters and blood values), we aim for using the full disease histo...... of disease history to scoring based on within-admission clinical measurements emphasizing the value of long term data in novel patient scores that combine the two types of data.......Sepsis affects millions of people every year, many of whom will die. In contrast to current survival prediction models for sepsis patients that primarily are based on data from within-admission clinical measurements (e.g. vital parameters and blood values), we aim for using the full disease history...... recurrent trajectories of time-ordered co-morbidities had significantly increased sepsis mortality compared to those who did not follow a trajectory. We identified trajectories which significantly altered sepsis mortality, and found three major starting points in a combined temporal sepsis network: Alcohol...

  8. IMPACT OF OXYGEN CONCENTRATION ON ZEBRA MUSSEL MORTALITY

    Energy Technology Data Exchange (ETDEWEB)

    Daniel P. Molloy

    2003-01-27

    These tests have indicated that the bacterium Pseudomonas fluorescens strain CL0145A is effective at killing zebra mussels in environments having dissolved oxygen (DO) concentrations ranging from very low to very high. The results suggest that the highest mussel kill can be achieved in moderately to highly aerated environments, while kill may be 0-20% lower under conditions of very low oxygen. For example, under highly oxygenated conditions 97% kill was achieved while conditions having low DO produced 79% mussel kill. Service water measured in a local power plant indicated that DO concentrations were in the range of 8-9 ppm (e.g., highly aerated) within their pipes. Therefore, we will not expect to see decreases in the efficacy of CL0145A treatments due to oxygen levels within such power plant pipes.

  9. IMPACT OF OXYGEN CONCENTRATION ON ZEBRA MUSSEL MORTALITY

    International Nuclear Information System (INIS)

    Molloy, Daniel P.

    2003-01-01

    These tests have indicated that the bacterium Pseudomonas fluorescens strain CL0145A is effective at killing zebra mussels in environments having dissolved oxygen (DO) concentrations ranging from very low to very high. The results suggest that the highest mussel kill can be achieved in moderately to highly aerated environments, while kill may be 0-20% lower under conditions of very low oxygen. For example, under highly oxygenated conditions 97% kill was achieved while conditions having low DO produced 79% mussel kill. Service water measured in a local power plant indicated that DO concentrations were in the range of 8-9 ppm (e.g., highly aerated) within their pipes. Therefore, we will not expect to see decreases in the efficacy of CL0145A treatments due to oxygen levels within such power plant pipes

  10. African Anthropogenic Combustion Emissions: Estimate of Regional Mortality Attributable to Fine Particle Concentrations in 2030

    Science.gov (United States)

    Liousse, C.; Roblou, L.; Assamoi, E.; Criqui, P.; Galy-Lacaux, C.; Rosset, R.

    2014-12-01

    Fossil fuel (traffic, industries) and biofuel (domestic fires) emissions of gases and particles in Africa are expected to significantly increase in the near future, particularly due to rapid growth of African cities and megacities. In this study, we will present the most recent developments of African combustion emission inventories, including African specificities. Indeed, a regional fossil fuel and biofuel inventory for gases and particulates described in Liousse et al. (2014) has been developed for Africa at a resolution of 0.25° x 0.25° for the years 2005 and 2030. For 2005, the original database of Junker and Liousse (2008) was used after modification for updated regional fuel consumption and emission factors. Two prospective inventories for 2030 are derived based on Prospective Outlook on Long-term Energy Systems (POLES) model (Criqui, 2001). The first is a reference scenario (2030ref) with no emission controls and the second is for a "clean" scenario (2030ccc*) including Kyoto policy and African specific emission control. This inventory predicts very large increases of pollutant emissions in 2030 (e.g. contributing to 50% of global anthropogenic organic particles), if no emission regulations are implemented. These inventories have been introduced in RegCM4 model. In this paper we will focus on aerosol modelled concentrations in 2005, 2030ref and 2030ccc*. Spatial distribution of aerosol concentrations will be presented with a zoom at a few urban and rural sites. Finally mortality rates (respiratory, cardiovascular) caused by anthropogenic PM2.5 increase from 2005 to 2030, calculated following Lelieveld et al. (2013), will be shown for each scenarios. To conclude, this paper will discuss the effectiveness of scenarios to reduce emissions, aerosol concentrations and mortality rates, underlining the need for further measurements scheduled in the frame of the new DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions) program.

  11. Fibrotic idiopathic interstitial pneumonias: HRCT findings that predict mortality

    Energy Technology Data Exchange (ETDEWEB)

    Edey, Anthony J.; Hansell, David M. [The Royal Brompton Hospital, Department of Radiology, London (United Kingdom); Devaraj, Anand A. [St. George' s NHS Foundation Trust, Department of Radiology, Tooting (United Kingdom); Barker, Robert P. [Frimley Park Hosptal, Department of Radiology, Frimley, Surrey (United Kingdom); Nicholson, Andrew G. [The Royal Brompton Hospital, Department of Histopathology, London (United Kingdom); Wells, Athol U. [The Royal Brompton Hospital, Interstitial Lung Disease Unit, London (United Kingdom)

    2011-08-15

    The study aims were to identify CT features that predict outcome of fibrotic idiopathic interstitial pneumonia (IIP) when information from lung biopsy data is unavailable. HRCTs of 146 consecutive patients presenting with fibrotic IIP were studied. Visual estimates were made of the extent of abnormal lung and proportional contribution of fine and coarse reticulation, microcystic (cysts {<=}4 mm) and macrocystic honeycombing. A score for severity of traction bronchiectasis was also assigned. Using death as our primary outcome measure, variables were analysed using the Cox proportional hazards model. CT features predictive of a worse outcome were coarse reticulation, microcystic and macrocystic honeycombing, as well as overall extent of lung abnormality (p < 0.001). Importantly, increased severity of traction bronchiectasis, corrected for extent of parenchymal abnormality, was predictive of poor prognosis regardless of the background pattern of abnormal lung (HR = 1.04, CI = 1.03-1.06, p < 0.001). On bivariate Cox analysis microcystic honeycombing was a more powerful determinant of a poor prognosis than macrocystic honeycombing. In fibrotic IIPs we have shown that increasingly severe traction bronchiectasis is indicative of higher mortality irrespective of the HRCT pattern and extent of disease. Extent of microcystic honeycombing is a more powerful determinant of outcome than macrocystic honeycombing. (orig.)

  12. The gamma gap predicts 4-year all-cause mortality among nonagenarians and centenarians.

    Science.gov (United States)

    Yang, Ming; Xie, Linlin; Liu, Xiu; Hao, Qiukui; Jiang, Jiaojiao; Dong, Birong

    2018-01-18

    Recent studies have revealed the prognostic role of the gamma gap, the total serum proteins concentration minus the albumin concentration, for predicting all-cause mortality among adults. This study aims to investigate the relationship between the gamma gap and all-cause mortality among nonagenarians and centenarians via a secondary data analysis of a prospective observational study. The analysis included 801 participants (260 men and 541 women, mean age: 93.7 ± 3.5 years), 46 of which were lost at the 4-year follow-up. The mean gamma gap was 2.7 ± 0.5 g/dl. After adjusting for relevant confounders, the gamma gap was significantly associated with 4-year all-cause mortality (hazard ratio [HR] per 1-SD = 1.22, 95% confidential interval [CI]: 1.12-1.78). Using different cut-off points, the elevated gamma gap could be defined as ≥2.9, 3.0, 3.1, or 3.2 g/dl. The relevant HRs and 95% CIs of the elevated gamma gap for predicting mortality were 1.27 (1.12-1.90), 1.29 (1.03-1.78), 1.21 (1.23-1.66), and 1.26 (1.09-1.69), respectively. In conclusion, the gamma gap is an independent prognostic factor for long-term mortality in nonagenarians and centenarians. A value greater than or equal to 3.1 g/dl may define an elevated gamma gap, but further studies are required.

  13. Value of routine blood tests for prediction of mortality risk in hip fracture patients

    DEFF Research Database (Denmark)

    Mosfeldt, Mathias; Pedersen, Ole Birger Vesterager; Riis, Troels

    2012-01-01

    There is a 5- to 8-fold increased risk of mortality during the first 3 months after a hip fracture. Several risk factors are known. We studied the predictive value (for mortality) of routine blood tests taken on admission.......There is a 5- to 8-fold increased risk of mortality during the first 3 months after a hip fracture. Several risk factors are known. We studied the predictive value (for mortality) of routine blood tests taken on admission....

  14. Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease : a molecular and genetic association study

    NARCIS (Netherlands)

    Zewinger, Stephen; Kleber, Marcus E.; Tragante Do O, V; McCubrey, Raymond O.; Schmidt, Amand F.; Direk, Kenan; Laufs, Ulrich; Werner, Christian; Koenig, Wolfgang; Rothenbacher, Dietrich; Mons, Ute; Breitling, Lutz P; Brenner, Herrmann; Jennings, Richard T.; Petrakis, Ioannis; Triem, Sarah; Klug, Mira; Filips, Alexandra; Blankenberg, Stefan; Waldeyer, Christoph; Sinning, Christoph; Schnabel, Renate B.; Lackner, Karl J.; Vlachopoulou, Efthymia; Nygård, Ottar; Svingen, Gard Frodahl Tveitevåg; Pedersen, Eva Ringdal; Tell, Grethe S.; Sinisalo, Juha; Nieminen, Markku S.; Laaksonen, Reijo; Trompet, Stella; Smit, Roelof A.J.; Sattar, Naveed; Jukema, J. Wouter; Groesdonk, Heinrich V.; Delgado, Graciela; Stojakovic, Tatjana; Pilbrow, Anna P.; Cameron, Vicky A.; Richards, A. Mark; Doughty, Robert N.; Gong, Yan; Cooper-Dehoff, Rhonda M; Johnson, Julie A; Scholz, Markus; Beutner, Frank; Thiery, Joachim; Smith, J. Gustav; Vilmundarson, Ragnar O.; McPherson, Ruth; Stewart, Alexandre F. R.; Cresci, Sharon; Lenzini, Petra A.; Spertus, John A.; Olivieri, Oliviero; Girelli, Domenico; Martinelli, Nicola I.; Leiherer, Andreas; Saely, Christoph H.; Drexel, Heinz; Mündlein, Axel; Braund, Peter S; Nelson, Christopher P.; Samani, Nilesh J.; Kofink, Daniel; Hoefer, Imo E.; Pasterkamp, Gerard; Quyyumi, Arshed A.; Ko, Yi-An; Hartiala, Jaana A.; Allayee, Hooman; Tang, W. H. Wilson; Hazen, Stanley L.; Eriksson, Niclas; Held, Claes; Hagström, Emil; Wallentin, Lars; Åkerblom, Axel; Siegbahn, Agneta; Karp, Igor; Labos, Christopher; Pilote, Louise; Engert, James C.; Brophy, James M.; Thanassoulis, George; Bogaty, Peter; Szczeklik, Wojciech; Kaczor, Marcin; Sanak, Marek; Virani, Salim S.; Ballantyne, Christie M.; Lee, Vei Vei; Boerwinkle, Eric; Holmes, Michael V.; Horne, Benjamin D; Hingorani, Aroon D.; Asselbergs, Folkert W.; Patel, Riyaz S; Krämer, Bernhard K; Scharnagl, Hubert; Fliser, Danilo; März, Winfried; Speer, Thimoteus

    Background Lipoprotein(a) concentrations in plasma are associated with cardiovascular risk in the general population. Whether lipoprotein(a) concentrations or LPA genetic variants predict long-term mortality in patients with established coronary heart disease remains less clear. Methods We obtained

  15. Is standard deviation of daily PM2.5 concentration associated with respiratory mortality?

    Science.gov (United States)

    Lin, Hualiang; Ma, Wenjun; Qiu, Hong; Vaughn, Michael G; Nelson, Erik J; Qian, Zhengmin; Tian, Linwei

    2016-09-01

    Studies on health effects of air pollution often use daily mean concentration to estimate exposure while ignoring daily variations. This study examined the health effects of daily variation of PM2.5. We calculated daily mean and standard deviations of PM2.5 in Hong Kong between 1998 and 2011. We used a generalized additive model to estimate the association between respiratory mortality and daily mean and variation of PM2.5, as well as their interaction. We controlled for potential confounders, including temporal trends, day of the week, meteorological factors, and gaseous air pollutants. Both daily mean and standard deviation of PM2.5 were significantly associated with mortalities from overall respiratory diseases and pneumonia. Each 10 μg/m(3) increment in daily mean concentration at lag 2 day was associated with a 0.61% (95% CI: 0.19%, 1.03%) increase in overall respiratory mortality and a 0.67% (95% CI: 0.14%, 1.21%) increase in pneumonia mortality. And a 10 μg/m(3) increase in standard deviation at lag 1 day corresponded to a 1.40% (95% CI: 0.35%, 2.46%) increase in overall respiratory mortality, and a 1.80% (95% CI: 0.46%, 3.16%) increase in pneumonia mortality. We also observed a positive but non-significant synergistic interaction between daily mean and variation on respiratory mortality and pneumonia mortality. However, we did not find any significant association with mortality from chronic obstructive pulmonary diseases. Our study suggests that, besides mean concentration, the standard deviation of PM2.5 might be one potential predictor of respiratory mortality in Hong Kong, and should be considered when assessing the respiratory effects of PM2.5. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. PREDICTION OF STRESS CONCENTRATION FACTORS IN

    African Journals Online (AJOL)

    ES OBE

    consider the effect of brace spacing on strengths of tubular K joints without consideration of same effect on square section K Joints. This lack of studies design strengths of gapped square section K joints makes availability of information on stress concentration factors in same joints scarce. However, information on 'Hot Spot' ...

  17. Lung cancer mortality and indoor radon concentrations in 18 Canadian cities

    International Nuclear Information System (INIS)

    Letourneau, E.G.; Mao, Y.; McGregor, R.G.; Semenciw, R.; Smith, M.H.; Wigle, D.T.

    1983-01-01

    Indoor radon and radon daughter concentrations were measured in a survey of 14,000 homes in 18 Canadian cities conducted in the summers of 1978 through 1980. Mortality and population data for the period 1966 through 1979 were retrieved for the geographic areas surveyed in each city. The results of analysis of the relation between lung cancer and radon daughter concentration, smoking habits and socioeconomic indicators for each city showed no detectable association between radon daughter concentrations and lung cancer mortality rates with or without adjustment for differences in smoking habits between cities

  18. Predicting mortality and incident immobility in older Belgian men by characteristics related to sarcopenia and frailty

    DEFF Research Database (Denmark)

    Kruse, C; Goemaere, S; De Buyser, S

    2018-01-01

    and bone mineral density scores were the most important predictors. INTRODUCTION: Machine learning principles were used to predict 5-year mortality and 3-year incident severe immobility in a population of older men by frailty and sarcopenia characteristics. METHODS: Using prospective data from 1997 on 264......There is an increasing awareness of sarcopenia in older people. We applied machine learning principles to predict mortality and incident immobility in older Belgian men through sarcopenia and frailty characteristics. Mortality could be predicted with good accuracy. Serum 25-hydroxyvitamin D...... the most important predictors of immobility. Sarcopenia assessed by lean mass estimates was relevant to mortality prediction but not immobility prediction. CONCLUSIONS: Using advanced statistical models and a machine learning approach 5-year mortality can be predicted with good accuracy using a Bayesian...

  19. Performance of in-hospital mortality prediction models for acute hospitalization: Hospital Standardized Mortality Ratio in Japan

    Directory of Open Access Journals (Sweden)

    Motomura Noboru

    2008-11-01

    Full Text Available Abstract Objective In-hospital mortality is an important performance measure for quality improvement, although it requires proper risk adjustment. We set out to develop in-hospital mortality prediction models for acute hospitalization using a nation-wide electronic administrative record system in Japan. Methods Administrative records of 224,207 patients (patients discharged from 82 hospitals in Japan between July 1, 2002 and October 31, 2002 were randomly split into preliminary (179,156 records and test (45,051 records groups. Study variables included Major Diagnostic Category, age, gender, ambulance use, admission status, length of hospital stay, comorbidity, and in-hospital mortality. ICD-10 codes were converted to calculate comorbidity scores based on Quan's methodology. Multivariate logistic regression analysis was then performed using in-hospital mortality as a dependent variable. C-indexes were calculated across risk groups in order to evaluate model performances. Results In-hospital mortality rates were 2.68% and 2.76% for the preliminary and test datasets, respectively. C-index values were 0.869 for the model that excluded length of stay and 0.841 for the model that included length of stay. Conclusion Risk models developed in this study included a set of variables easily accessible from administrative data, and still successfully exhibited a high degree of prediction accuracy. These models can be used to estimate in-hospital mortality rates of various diagnoses and procedures.

  20. Sustained high serum caspase-3 concentrations and mortality in septic patients.

    Science.gov (United States)

    Lorente, L; Martín, M M; Pérez-Cejas, A; González-Rivero, A F; López, R O; Ferreres, J; Solé-Violán, J; Labarta, L; Díaz, C; Palmero, S; Jiménez, A

    2018-02-01

    Caspase-3 is the main executor of the apoptotic process. Higher serum caspase-3 concentrations in non-survivor compared to survivor septic patients have been found. The objectives of this work (with the increase of sample size to 308 patients, and the determination of serum caspase-3 concentrations also on days 4 and 8 of diagnosis of severe sepsis) were to know whether an association between serum caspase-3 concentrationss during the first week, degree of apoptosis, sepsis severity, and sepsis mortality exists. We collected serum samples of 308 patients with severe sepsis from eight intensive care units on days 1, 4 and 8 to measure concentrations of caspase-3 and caspase-cleaved cytokeratin (CCCK)-18 (to assess degree of apoptosis). End point was 30-day mortality. We found higher serum concentrations of caspase-3 and CCCK-18 in non-survivors compared to survivors on days 1 (p < 0.001), 4 (p < 0.001), and 8 (p < 0.001). We found an association between serum caspase-3 concentrations on days 1, 4 and 8 of severe sepsis diagnosis and serum CCCK-18 concentrations (p < 0.001), SOFA (p < 0.001), serum acid lactic concentrations (p < 0.001), and 30-day sepsis mortality (p < 0.001). The new findings of this work were that an association between serum caspase-3 concentrations during the first week, apoptosis degree, sepsis severity, and sepsis mortality exists.

  1. The Rural Inpatient Mortality Study: Does Urban-Rural County Classification Predict Hospital Mortality in California?

    Science.gov (United States)

    Linnen, Daniel T; Kornak, John; Stephens, Caroline

    2018-03-28

    Evidence suggests an association between rurality and decreased life expectancy. To determine whether rural hospitals have higher hospital mortality, given that very sick patients may be transferred to regional hospitals. In this ecologic study, we combined Medicare hospital mortality ratings (N = 1267) with US census data, critical access hospital classification, and National Center for Health Statistics urban-rural county classifications. Ratings included mortality for coronary artery bypass grafting, stroke, chronic obstructive pulmonary disease, heart attack, heart failure, and pneumonia across 277 California hospitals between July 2011 and June 2014. We used generalized estimating equations to evaluate the association of urban-rural county classifications on mortality ratings. Unfavorable Medicare hospital mortality rating "worse than the national rate" compared with "better" or "same." Compared with large central "metro" (metropolitan) counties, hospitals in medium-sized metro counties had 6.4 times the odds of rating "worse than the national rate" for hospital mortality (95% confidence interval = 2.8-14.8, p centers may contribute to these results, a potential factor that future research should examine.

  2. Use of a semiquantitative procalcitonin kit for evaluating severity and predicting mortality in patients with sepsis

    Directory of Open Access Journals (Sweden)

    Kenzaka T

    2012-05-01

    Full Text Available Tsuneaki Kenzaka,1 Masanobu Okayama,2 Shigehiro Kuroki,1 Miho Fukui,3 Shinsuke Yahata,3 Hiroki Hayashi,3 Akihito Kitao,3 Eiji Kajii,2 Masayoshi Hashimoto41Division of General Medicine, 2Division of Community and Family Medicine, Center for Community Medicine, Jichi Medical University School of Medicine, Shimotsuke; 3Department of General Medicine, Toyooka Public Hospital, Toyooka; 4Department of Family and Community Medicine, Kobe University Graduate School of Medicine, Kobe, JapanBackground: The aim of this study was to evaluate the clinical usefulness of a semiquantitative procalcitonin kit for assessing severity of sepsis and early determination of mortality in affected patients.Methods: This was a prospective, observational study including 206 septic patients enrolled between June 2008 and August 2009. Disseminated intravascular coagulation (DIC, Sequential Organ Failure Assessment (SOFA, Acute Physiology and Chronic Health Evaluation (APACHE II scores were measured, along with semiquantitative procalcitonin concentrations. Patients were divided into three groups based on their semiquantitative procalcitonin concentrations (group A, <2 ng/mL; group B ≥ 2 ng/mL < 10 ng/mL; group C ≥ 10 ng/mL.Results: A significant difference in DIC, SOFA, and APACHE II scores was found between group A and group C and between group B and group C (P < 0.01. Patients with severe sepsis and septic shock had significantly higher procalcitonin concentrations than did patients with less severe disease. The rate of patients with septic shock with high procalcitonin concentrations showed an upward trend. There was a significant (P < 0.01 difference between the three groups with regard to numbers of patients and rates of severe sepsis, septic shock, DIC, and mortality.Conclusion: Semiquantitative procalcitonin concentration testing can be helpful for early assessment of disease severity in patients with sepsis. Furthermore, it may also help in predicting early

  3. Chemotherapy effectiveness and mortality prediction in surgically treated osteosarcoma dogs: A validation study.

    Science.gov (United States)

    Schmidt, A F; Nielen, M; Withrow, S J; Selmic, L E; Burton, J H; Klungel, O H; Groenwold, R H H; Kirpensteijn, J

    2016-03-01

    Canine osteosarcoma is the most common bone cancer, and an important cause of mortality and morbidity, in large purebred dogs. Previously we constructed two multivariable models to predict a dog's 5-month or 1-year mortality risk after surgical treatment for osteosarcoma. According to the 5-month model, dogs with a relatively low risk of 5-month mortality benefited most from additional chemotherapy treatment. In the present study, we externally validated these results using an independent cohort study of 794 dogs. External performance of our prediction models showed some disagreement between observed and predicted risk, mean difference: -0.11 (95% confidence interval [95% CI]-0.29; 0.08) for 5-month risk and 0.25 (95%CI 0.10; 0.40) for 1-year mortality risk. After updating the intercept, agreement improved: -0.0004 (95%CI-0.16; 0.16) and -0.002 (95%CI-0.15; 0.15). The chemotherapy by predicted mortality risk interaction (P-value=0.01) showed that the chemotherapy compared to no chemotherapy effectiveness was modified by 5-month mortality risk: dogs with a relatively lower risk of mortality benefited most from additional chemotherapy. Chemotherapy effectiveness on 1-year mortality was not significantly modified by predicted risk (P-value=0.28). In conclusion, this external validation study confirmed that our multivariable risk prediction models can predict a patient's mortality risk and that dogs with a relatively lower risk of 5-month mortality seem to benefit most from chemotherapy. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Perceived extrinsic mortality risk and reported effort in looking after health: testing a behavioral ecological prediction.

    Science.gov (United States)

    Pepper, Gillian V; Nettle, Daniel

    2014-09-01

    Socioeconomic gradients in health behavior are pervasive and well documented. Yet, there is little consensus on their causes. Behavioral ecological theory predicts that, if people of lower socioeconomic position (SEP) perceive greater personal extrinsic mortality risk than those of higher SEP, they should disinvest in their future health. We surveyed North American adults for reported effort in looking after health, perceived extrinsic and intrinsic mortality risks, and measures of SEP. We examined the relationships between these variables and found that lower subjective SEP predicted lower reported health effort. Lower subjective SEP was also associated with higher perceived extrinsic mortality risk, which in turn predicted lower reported health effort. The effect of subjective SEP on reported health effort was completely mediated by perceived extrinsic mortality risk. Our findings indicate that perceived extrinsic mortality risk may be a key factor underlying SEP gradients in motivation to invest in future health.

  5. Serum thiamine concentration and oxidative stress as predictors of mortality in patients with septic shock.

    Science.gov (United States)

    Costa, Nara Aline; Gut, Ana Lúcia; de Souza Dorna, Mariana; Pimentel, José Alexandre Coelho; Cozzolino, Silvia Maria Franciscato; Azevedo, Paula Schmidt; Fernandes, Ana Angélica Henrique; Zornoff, Leonardo Antonio Mamede; de Paiva, Sergio Alberto Rupp; Minicucci, Marcos Ferreira

    2014-04-01

    The purpose of the study is to determine the influence of serum thiamine, glutathione peroxidase (GPx) activity, and serum protein carbonyl concentrations in hospital mortality in patients with septic shock. This prospective study included all patients with septic shock on admission or during intensive care unit (ICU) stay, older than 18 years, admitted to 1 of the 3 ICUs of the Botucatu Medical School, from January to August 2012. Demographic information, clinical evaluation, and blood sample were taken within the first 72 hours of the patient's admission or within 72 hours after septic shock diagnosis for serum thiamine, GPx activity, and protein carbonyl determination. One hundred eight consecutive patients were evaluated. The mean age was 57.5 ± 16.0 years, 63% were male, 54.6% died in the ICU, and 71.3% had thiamine deficiency. Thiamine was not associated with oxidative stress. Neither vitamin B1 levels nor the GPx activity was associated with outcomes in these patients. However, protein carbonyl concentration was associated with increased mortality. In patients with septic shock, oxidative stress was associated with mortality. On the other hand, thiamine was not associated with oxidative stress or mortality in these patients. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Validation of lactate clearance at 6 h for mortality prediction in critically ill children

    OpenAIRE

    Rajeev Kumar; Nirmal Kumar

    2016-01-01

    Background and Aims: To validate the lactate clearance (LC) at 6 h for mortality prediction in Pediatric Intensive Care Unit (PICU)-admitted patients and its comparison with a pediatric index of mortality 2 (PIM 2) score. Design: A prospective, observational study in a tertiary care center. Materials and Methods: Children

  7. Performance of Simplified Acute Physiology Score 3 In Predicting Hospital Mortality In Emergency Intensive Care Unit

    Directory of Open Access Journals (Sweden)

    Qing-Bian Ma

    2017-01-01

    Conclusions: The SAPS 3 score system exhibited satisfactory performance even superior to APACHE II in discrimination. In predicting hospital mortality, SAPS 3 did not exhibit good calibration and overestimated hospital mortality, which demonstrated that SAPS 3 needs improvement in the future.

  8. Chemotherapy effectiveness and mortality prediction in surgically treated osteosarcoma dogs : A validation study

    NARCIS (Netherlands)

    Schmidt, A F; Nielen, M; Withrow, S J; Selmic, L E; Burton, J H; Klungel, O H; Groenwold, R H H; Kirpensteijn, J

    2016-01-01

    Canine osteosarcoma is the most common bone cancer, and an important cause of mortality and morbidity, in large purebred dogs. Previously we constructed two multivariable models to predict a dog's 5-month or 1-year mortality risk after surgical treatment for osteosarcoma. According to the 5-month

  9. Inflammation biomarkers and mortality prediction in patients with type 2 diabetes (ZODIAC-27)

    NARCIS (Netherlands)

    Landman, Gijs W. D.; Kleefstra, Nanne; Groenier, Klaas H.; Bakker, Stephan J. L.; Groeneveld, Geert H.; Bilo, Henk J. G.; van Hateren, Kornelis J. J.

    Background: C-reactive protein (CRP), procalcitonin (PCT) and pro-adrenomedullin (MR-proADM) are inflammation markers associated with long-term mortality risk. We compared the associations and predictive capacities of CRP, PCT and MR-proADM with cardiovascular and all-cause mortality in patients

  10. Midline shift in relation to thickness of traumatic acute subdural hematoma predicts mortality

    NARCIS (Netherlands)

    Bartels, R.H.M.A.; Meijer, F.J.; Hoeven, H. van der; Edwards, M.J.; Prokop, M.

    2015-01-01

    BACKGROUND: Traumatic acute subdural hematoma has a high mortality despite intensive treatment. Despite the existence of several prediction models, it is very hard to predict an outcome. We investigated whether a specific combination of initial head CT-scan findings is a factor in predicting

  11. Monitoring and Predicting Traffic Induced Vertebrate Mortality Near Wetlands

    OpenAIRE

    DeWoody, J. Andrew; Nogle, Jamie M.; Hoover, Melissa; Dunning, Barny

    2010-01-01

    Animal-vehicle collisions are undesirable to the general public, to drivers, to insurance providers, to biologists, and presumably to the animals themselves. However, traffic-induced mortality (―roadkill‖) is difficult to mitigate in large part because scientists lack the empirical data required to understand the patterns and processes associated with roadkill. Roadkill is not randomly distributed in space or in time, but what are the primary determinants of roadkill? And do they differ acros...

  12. One- and 2-Year Mortality Prediction for Patients Starting Chronic Dialysis

    Directory of Open Access Journals (Sweden)

    Mikko Haapio

    2017-11-01

    Discussion: Mortality prediction algorithms could be more widely implemented into management of ESRD patients. The presented models are practical with only a limited number of variables and fairly good performance.

  13. Low serum leptin predicts mortality in patients with chronic kidney disease stage 5

    DEFF Research Database (Denmark)

    Scholze, Alexandra; Rattensperger, Dirk; Zidek, Walter

    2007-01-01

    Leptin, secreted from adipose tissue, regulates food intake, energy expenditure, and immune function. It is unknown whether leptin predicts mortality in patients with chronic kidney disease stage 5 on hemodialysis therapy....

  14. Low plasma arginine:asymmetric dimethyl arginine ratios predict mortality after intracranial aneurysm rupture

    DEFF Research Database (Denmark)

    Staalsø, Jonatan Myrup; Bergström, Anita; Edsen, Troels

    2013-01-01

    Asymmetrical dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthases, predicts mortality in cardiovascular disease and has been linked to cerebral vasospasm after aneurysmal subarachnoid hemorrhage (SAH). In this prospective study, we assessed whether circulating ADMA, arginine...

  15. A biological approach to the interspecies prediction of radiation-induced mortality risk

    International Nuclear Information System (INIS)

    Carnes, B.A.; Grahn, D.; Olshansky, S.J.

    1997-01-01

    Evolutionary explanations for why sexually reproducing organisms grow old suggest that the forces of natural selection affect the ages when diseases occur that are subject to a genetic influence (referred to here as intrinsic diseases). When extended to the population level for a species, this logic leads to the general prediction that age-specific death rates from intrinsic causes should begin to rise as the force of selection wanes once the characteristic age of sexual maturity is attained. Results consistent with these predictions have been found for laboratory mice, beagles, and humans where, after adjusting for differences in life span, it was demonstrated that these species share a common age pattern of mortality for intrinsic causes of death. In quantitative models used to predict radiation-induced mortality, risks are often expressed as multiples of those observed in a control population. A control population, however, is an aging population. As such, mortality risks related to exposure must be interpreted relative to the age-specific risk of death associated with aging. Given the previous success in making interspecies predictions of age-related mortality, the purpose of this study was to determine whether radiation-induced mortality observed in one species could also be predicted quantitatively from a model used to describe the mortality consequences of exposure to radiation in a different species. Mortality data for B6CF 1 mice and beagles exposed to 60 Co γ-rays for the duration of life were used for analysis

  16. Clinical utility of EMSE and STESS in predicting hospital mortality for status epilepticus.

    Science.gov (United States)

    Zhang, Yu; Chen, Deng; Xu, Da; Tan, Ge; Liu, Ling

    2018-05-25

    To explore the applicability of the epidemiology-based mortality score in status epilepticus (EMSE) and the status epilepticus severity score (STESS) in predicting hospital mortality in patients with status epilepticus (SE) in western China. Furthermore, we sought to compare the abilities of the two scales to predict mortality from convulsive status epilepticus (CSE) and non-convulsive status epilepticus (NCSE). Patients with epilepsy (n = 253) were recruited from the West China Hospital of Sichuan University from January 2012 to January 2016. The EMSE and STESS for all patients were calculated immediately after admission. The main outcome was in-hospital death. The predicted values were analysed using SPSS 22.0 receiver operating characteristic (ROC) curves. Of the 253 patients with SE who were included in the study, 39 (15.4%) died in the hospital. Using STESS ≥4 points to predict SE mortality, the area under the ROC curve (AUC) was 0.724 (P  0.05), while EMSE ≥90 points gave an AUC of 0.666 (P > 0.05). The hospital mortality rate from SE in this study was 15.4%. Those with STESS ≥4 points or EMSE ≥79 points had higher rates of SE mortality. Both STESS and EMSE are less useful predicting in-hospital mortality in NCSE compared to CSE. Furthermore, the EMSE has some advantages over the STESS. Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

  17. Plasma Lactate Dehydrogenase Levels Predict Mortality in Acute Aortic Syndromes

    Science.gov (United States)

    Morello, Fulvio; Ravetti, Anna; Nazerian, Peiman; Liedl, Giovanni; Veglio, Maria Grazia; Battista, Stefania; Vanni, Simone; Pivetta, Emanuele; Montrucchio, Giuseppe; Mengozzi, Giulio; Rinaldi, Mauro; Moiraghi, Corrado; Lupia, Enrico

    2016-01-01

    Abstract In acute aortic syndromes (AAS), organ malperfusion represents a key event impacting both on diagnosis and outcome. Increased levels of plasma lactate dehydrogenase (LDH), a biomarker of malperfusion, have been reported in AAS, but the performance of LDH for the diagnosis of AAS and the relation of LDH with outcome in AAS have not been evaluated so far. This was a bi-centric prospective diagnostic accuracy study and a cohort outcome study. From 2008 to 2014, patients from 2 Emergency Departments suspected of having AAS underwent LDH assay at presentation. A final diagnosis was obtained by aortic imaging. Patients diagnosed with AAS were followed-up for in-hospital mortality. One thousand five hundred seventy-eight consecutive patients were clinically eligible, and 999 patients were included in the study. The final diagnosis was AAS in 201 (20.1%) patients. Median LDH was 424 U/L (interquartile range [IQR] 367–557) in patients with AAS and 383 U/L (IQR 331–460) in patients with alternative diagnoses (P < 0.001). Using a cutoff of 450 U/L, the sensitivity of LDH for AAS was 44% (95% confidence interval [CI] 37–51) and the specificity was 73% (95% CI 69–76). Overall in-hospital mortality for AAS was 23.8%. Mortality was 32.6% in patients with LDH ≥ 450 U/L and 16.8% in patients with LDH < 450 U/L (P = 0.006). Following stratification according to LDH quartiles, in-hospital mortality was 12% in the first (lowest) quartile, 18.4% in the second quartile, 23.5% in the third quartile, and 38% in the fourth (highest) quartile (P = 0.01). LDH ≥ 450 U/L was further identified as an independent predictor of death in AAS both in univariate and in stepwise logistic regression analyses (odds ratio 2.28, 95% CI 1.11–4.66; P = 0.025), in addition to well-established risk markers such as advanced age and hypotension. Subgroup analysis showed excess mortality in association with LDH ≥ 450 U/L in elderly, hemodynamically stable

  18. [Value of sepsis single-disease manage system in predicting mortality in patients with sepsis].

    Science.gov (United States)

    Chen, J; Wang, L H; Ouyang, B; Chen, M Y; Wu, J F; Liu, Y J; Liu, Z M; Guan, X D

    2018-04-03

    Objective: To observe the effect of sepsis single-disease manage system on the improvement of sepsis treatment and the value in predicting mortality in patients with sepsis. Methods: A retrospective study was conducted. Patients with sepsis admitted to the Department of Surgical Intensive Care Unit of Sun Yat-Sen University First Affiliated Hospital from September 22, 2013 to May 5, 2015 were enrolled in this study. Sepsis single-disease manage system (Rui Xin clinical data manage system, China data, China) was used to monitor 25 clinical quality parameters, consisting of timeliness, normalization and outcome parameters. Based on whether these quality parameters could be completed or not, the clinical practice was evaluated by the system. The unachieved quality parameter was defined as suspicious parameters, and these suspicious parameters were used to predict mortality of patients with receiver operating characteristic curve (ROC). Results: A total of 1 220 patients with sepsis were enrolled, included 805 males and 415 females. The mean age was (59±17) years, and acute physiology and chronic health evaluation (APACHE Ⅱ) scores was 19±8. The area under ROC curve of total suspicious numbers for predicting 28-day mortality was 0.70; when the suspicious parameters number was more than 6, the sensitivity was 68.0% and the specificity was 61.0% for predicting 28-day mortality. In addition, the area under ROC curve of outcome suspicious number for predicting 28-day mortality was 0.89; when the suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 78.0% for predicting 28-day mortality. Moreover, the area under ROC curve of total suspicious number for predicting 90-day mortality was 0.73; when the total suspicious parameters number was more than 7, the sensitivity was 60.0% and the specificity was 74.0% for predicting 90-day mortality. Finally, the area under ROC curve of outcome suspicious numbers for predicting 90

  19. Comparison of observed and predicted Kr-85 air concentrations

    International Nuclear Information System (INIS)

    Yildiran, M.; Miller, C.W.

    1984-01-01

    A computer code, ANEMOS has been written to estimate concentrations in air and ground deposition rates for Atmospheric Nuclides Emitted from Multiple Operation Sources. This code uses a modified Gaussian plume equation. Output from ANEMOS includes annual-average air concentrations and ground deposition rates of dispersed radionuclides and daughters. To use the environmental transport model properly, some estimate of the models predictive accuracy must be obtained. To validate the ANEMOS model, one year of weekly average Kr-85 concentrations observed at 13 stations located 28 to 144 km distant from continuous point source at the Savannah River Plant have been used. There was a general tendency for the model to underpredict the observed air concentrations slightly. Pearson's correlation between pairs of logarithms of observed and predicted annual-average values was r=0.84. The monthly results tend to show more scatter than do either the seasonal or the annual comparisons. (orig.)

  20. Comparison of observed and predicted Kr-85 air concentrations

    International Nuclear Information System (INIS)

    Yildiran, M.; Miller, C.W.

    1984-01-01

    A computer code, ANEMOS has been written to estimate concentrations in air and ground deposition rates for Atmospheric Nuclides Emitted from Multiple Operation Sources. This code uses a modified Gaussian plum equation. Output from ANEMOS includes annual-average air concentrations and ground deposition rates of dispersed radionuclides and daughters. To use the environmental transport model properly, some estimate of the models predictive accuracy must be obtained. To validate the ANEMOS model, one year of weekly average Kr-85 concentrations observed at 13 stations located 28 to 144 km distant from continuous point source at the Savannah River Plant (SRP), Aiken, South Carolina, have been used. There was a general tendency for the model to underpredict the observed air concentrations slightly. Pearsons's correlation between pairs of logarithms of observed and predicted annual-average values was r = 0.84. The monthly results tend to show more scatter than do either the seasonal or the annual comparisons. 18 references, 3 figures, 3 tables

  1. Penalized regression techniques for prediction: a case study for predicting tree mortality using remotely sensed vegetation indices

    NARCIS (Netherlands)

    Lazaridis, D.C.; Verbesselt, J.; Robinson, A.P.

    2011-01-01

    Constructing models can be complicated when the available fitting data are highly correlated and of high dimension. However, the complications depend on whether the goal is prediction instead of estimation. We focus on predicting tree mortality (measured as the number of dead trees) from change

  2. The Prediction of Drought-Related Tree Mortality in Vegetation Models

    Science.gov (United States)

    Schwinning, S.; Jensen, J.; Lomas, M. R.; Schwartz, B.; Woodward, F. I.

    2013-12-01

    Drought-related tree die-off events at regional scales have been reported from all wooded continents and it has been suggested that their frequency may be increasing. The prediction of these drought-related die-off events from regional to global scales has been recognized as a critical need for the conservation of forest resources and improving the prediction of climate-vegetation interactions. However, there is no conceptual consensus on how to best approach the quantitative prediction of tree mortality. Current models use a variety of mechanisms to represent demographic events. Mortality is modeled to represent a number of different processes, including death by fire, wind throw, extreme temperatures, and self-thinning, and each vegetation model differs in the emphasis they place on specific mechanisms. Dynamic global vegetation models generally operate on the assumption of incremental vegetation shift due to changes in the carbon economy of plant functional types and proportional effects on recruitment, growth, competition and mortality, but this may not capture sudden and sweeping tree death caused by extreme weather conditions. We tested several different approaches to predicting tree mortality within the framework of the Sheffield Dynamic Global Vegetation Model. We applied the model to the state of Texas, USA, which in 2011 experienced extreme drought conditions, causing the death of an estimated 300 million trees statewide. We then compared predicted to actual mortality to determine which algorithms most accurately predicted geographical variation in tree mortality. We discuss implications regarding the ongoing debate on the causes of tree death.

  3. Predicting radon/radon daughter concentrations in underground mines

    International Nuclear Information System (INIS)

    Leach, V.A.

    1984-01-01

    A detailed description of a computer programme is outlined for the calculation of radon/radon daughter concentrations in air. This computer model is used to predict the radon/radon daughter concentrations in Working Level (WL) at the workplace and at the various junctions at either end of the branches in a typical ventilation network proposed for the Jabiluka mine in the Northern Territory

  4. Development of system on predicting uranium concentration from pregnant solution

    International Nuclear Information System (INIS)

    Yi Weiping

    2004-01-01

    Uranium concentration from pregnant solution is primary index of process for in-situ leaching of uranium, and the suitable method with which to predicate this index and effective means to solve it with were continuously studied hard. SPUC-system on predicting uranium concentration based on GM model of gray system theory is developed, and the mathematical model, constitution, function and theory foundation of this system are introduced. (authors)

  5. Validation of predicted exponential concentration profiles of chemicals in soils

    International Nuclear Information System (INIS)

    Hollander, Anne; Baijens, Iris; Ragas, Ad; Huijbregts, Mark; Meent, Dik van de

    2007-01-01

    Multimedia mass balance models assume well-mixed homogeneous compartments. Particularly for soils, this does not correspond to reality, which results in potentially large uncertainties in estimates of transport fluxes from soils. A theoretically expected exponential decrease model of chemical concentrations with depth has been proposed, but hardly tested against empirical data. In this paper, we explored the correspondence between theoretically predicted soil concentration profiles and 84 field measured profiles. In most cases, chemical concentrations in soils appear to decline exponentially with depth, and values for the chemical specific soil penetration depth (d p ) are predicted within one order of magnitude. Over all, the reliability of multimedia models will improve when they account for depth-dependent soil concentrations, so we recommend to take into account the described theoretical exponential decrease model of chemical concentrations with depth in chemical fate studies. In this model the d p -values should estimated be either based on local conditions or on a fixed d p -value, which we recommend to be 10 cm for chemicals with a log K ow > 3. - Multimedia mass model predictions will improve when taking into account depth dependent soil concentrations

  6. Comparison of predicted and measured variations of indoor radon concentration

    International Nuclear Information System (INIS)

    Arvela, H.; Voutilainen, A.; Maekelaeinen, I.; Castren, O.; Winqvist, K.

    1988-01-01

    Prediction of the variations of indoor radon concentration were calculated using a model relating indoor radon concentration to radon entry rate, air infiltration and meteorological factors. These calculated variations have been compared with seasonal variations of 33 houses during 1-4 years, with winter-summer concentration ratios of 300 houses and the measured diurnal variation. In houses with a slab in ground contact the measured seasonal variations are quite often in agreement with variations predicted for nearly pure pressure difference driven flow. The contribution of a diffusion source is significant in houses with large porous concrete walls against the ground. Air flow due to seasonally variable thermal convection within eskers strongly affects the seasonal variations within houses located thereon. Measured and predicted winter-summer concentration ratios demonstrate that, on average, the ratio is a function of radon concentration. The ratio increases with increasing winter concentration. According to the model the diurnal maximum caused by a pressure difference driven flow occurs in the morning, a finding which is in agreement with the measurements. The model presented can be used for differentiating between factors affecting radon entry into houses. (author)

  7. Mortality associated with particulate concentration and Asian dust storms in Metropolitan Taipei

    Science.gov (United States)

    Wang, Yu-Chun; Lin, Yu-Kai

    2015-09-01

    This study evaluates mortality risks from all causes, circulatory diseases, and respiratory diseases associated with particulate matter (PM10 and PM2.5) concentrations and Asian dust storms (ADS) from 2000 to 2008 in Metropolitan Taipei. This study uses a distributed lag non-linear model with Poisson distribution to estimate the cumulative 5-day (lags 0-4) relative risks (RRs) and confidence intervals (CIs) of cause-specific mortality associated with daily PM10 and PM2.5 concentrations, as well as ADS, for total (all ages) and elderly (≥65 years) populations based on study periods (ADS frequently inflicted period: 2000-2004; and less inflicted period: 2005-2008). Risks associated with ADS characteristics, including inflicted season (winter and spring), strength (the ratio of stations with Pollutant Standard Index >100 is increase in PM10 from 10 μg/m3 to 50 μg/m3 was associated with increased all-cause mortality risk with cumulative 5-day RR of 1.10 (95% CI: 1.04, 1.17) for the total population and 1.10 (95% CI: 1.02, 1.18) for elders. Mortality from circulatory diseases for the elderly was related to increased PM2.5 from 5 μg/m3 to 30 μg/m3, with cumulative 5-day RR of 1.21 (95% CI: 1.02, 1.44) from 2005 to 2008. Compared with normal days, the mortality from all causes and circulatory diseases for the elderly population was associated with winter ADS with RRs of 1.05 (95% CI: 1.01, 1.08) and 1.08 (95% CI: 1.01, 1.15), respectively. Moreover, all-cause mortality was associated with shorter and less area-affected ADS with an RR of 1.04 for total and elderly populations from 2000 to 2004. Population health risk differed not only with PM concentration but also with ADS characteristics.

  8. Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.

    Science.gov (United States)

    Awad, Aya; Bader-El-Den, Mohamed; McNicholas, James; Briggs, Jim

    2017-12-01

    Mortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By contrast, early mortality prediction for intensive care unit patients remains an open challenge. Most research has focused on severity of illness scoring systems or data mining (DM) models designed for risk estimation at least 24 or 48h after ICU admission. This study highlights the main data challenges in early mortality prediction in ICU patients and introduces a new machine learning based framework for Early Mortality Prediction for Intensive Care Unit patients (EMPICU). The proposed method is evaluated on the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database. Mortality prediction models are developed for patients at the age of 16 or above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU). We employ the ensemble learning Random Forest (RF), the predictive Decision Trees (DT), the probabilistic Naive Bayes (NB) and the rule-based Projective Adaptive Resonance Theory (PART) models. The primary outcome was hospital mortality. The explanatory variables included demographic, physiological, vital signs and laboratory test variables. Performance measures were calculated using cross-validated area under the receiver operating characteristic curve (AUROC) to minimize bias. 11,722 patients with single ICU stays are considered. Only patients at the age of 16 years old and above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU) are considered in this study. The proposed EMPICU framework outperformed standard scoring systems (SOFA, SAPS-I, APACHE-II, NEWS and qSOFA) in terms of AUROC and time (i.e. at 6h compared to 48h or more after admission). The results show that although there are many values missing in the first few hour of ICU admission

  9. Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

    Science.gov (United States)

    Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

    2015-08-01

    Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

  10. A Risk Prediction Model for In-hospital Mortality in Patients with Suspected Myocarditis.

    Science.gov (United States)

    Xu, Duo; Zhao, Ruo-Chi; Gao, Wen-Hui; Cui, Han-Bin

    2017-04-05

    Myocarditis is an inflammatory disease of the myocardium that may lead to cardiac death in some patients. However, little is known about the predictors of in-hospital mortality in patients with suspected myocarditis. Thus, the aim of this study was to identify the independent risk factors for in-hospital mortality in patients with suspected myocarditis by establishing a risk prediction model. A retrospective study was performed to analyze the clinical medical records of 403 consecutive patients with suspected myocarditis who were admitted to Ningbo First Hospital between January 2003 and December 2013. A total of 238 males (59%) and 165 females (41%) were enrolled in this study. We divided the above patients into two subgroups (survival and nonsurvival), according to their clinical in-hospital outcomes. To maximize the effectiveness of the prediction model, we first identified the potential risk factors for in-hospital mortality among patients with suspected myocarditis, based on data pertaining to previously established risk factors and basic patient characteristics. We subsequently established a regression model for predicting in-hospital mortality using univariate and multivariate logistic regression analyses. Finally, we identified the independent risk factors for in-hospital mortality using our risk prediction model. The following prediction model for in-hospital mortality in patients with suspected myocarditis, including creatinine clearance rate (Ccr), age, ventricular tachycardia (VT), New York Heart Association (NYHA) classification, gender and cardiac troponin T (cTnT), was established in the study: P = ea/(1 + ea) (where e is the exponential function, P is the probability of in-hospital death, and a = -7.34 + 2.99 × [Ccr model demonstrated that a Ccr prediction model for in-hospital mortality in patients with suspected myocarditis. In addition, sufficient life support during the early stage of the disease might improve the prognoses of patients with

  11. Prediction of toxic metals concentration using artificial intelligence techniques

    Science.gov (United States)

    Gholami, R.; Kamkar-Rouhani, A.; Doulati Ardejani, F.; Maleki, Sh.

    2011-12-01

    Groundwater and soil pollution are noted to be the worst environmental problem related to the mining industry because of the pyrite oxidation, and hence acid mine drainage generation, release and transport of the toxic metals. The aim of this paper is to predict the concentration of Ni and Fe using a robust algorithm named support vector machine (SVM). Comparison of the obtained results of SVM with those of the back-propagation neural network (BPNN) indicates that the SVM can be regarded as a proper algorithm for the prediction of toxic metals concentration due to its relative high correlation coefficient and the associated running time. As a matter of fact, the SVM method has provided a better prediction of the toxic metals Fe and Ni and resulted the running time faster compared with that of the BPNN.

  12. Flow-covariate prediction of stream pesticide concentrations.

    Science.gov (United States)

    Mosquin, Paul L; Aldworth, Jeremy; Chen, Wenlin

    2018-01-01

    Potential peak functions (e.g., maximum rolling averages over a given duration) of annual pesticide concentrations in the aquatic environment are important exposure parameters (or target quantities) for ecological risk assessments. These target quantities require accurate concentration estimates on nonsampled days in a monitoring program. We examined stream flow as a covariate via universal kriging to improve predictions of maximum m-day (m = 1, 7, 14, 30, 60) rolling averages and the 95th percentiles of atrazine concentration in streams where data were collected every 7 or 14 d. The universal kriging predictions were evaluated against the target quantities calculated directly from the daily (or near daily) measured atrazine concentration at 32 sites (89 site-yr) as part of the Atrazine Ecological Monitoring Program in the US corn belt region (2008-2013) and 4 sites (62 site-yr) in Ohio by the National Center for Water Quality Research (1993-2008). Because stream flow data are strongly skewed to the right, 3 transformations of the flow covariate were considered: log transformation, short-term flow anomaly, and normalized Box-Cox transformation. The normalized Box-Cox transformation resulted in predictions of the target quantities that were comparable to those obtained from log-linear interpolation (i.e., linear interpolation on the log scale) for 7-d sampling. However, the predictions appeared to be negatively affected by variability in regression coefficient estimates across different sample realizations of the concentration time series. Therefore, revised models incorporating seasonal covariates and partially or fully constrained regression parameters were investigated, and they were found to provide much improved predictions in comparison with those from log-linear interpolation for all rolling average measures. Environ Toxicol Chem 2018;37:260-273. © 2017 SETAC. © 2017 SETAC.

  13. The Impact of EuroSCORE II Risk Factors on Prediction of Long-Term Mortality.

    Science.gov (United States)

    Barili, Fabio; Pacini, Davide; D'Ovidio, Mariangela; Dang, Nicholas C; Alamanni, Francesco; Di Bartolomeo, Roberto; Grossi, Claudio; Davoli, Marina; Fusco, Danilo; Parolari, Alessandro

    2016-10-01

    The European System for Cardiac Operation Risk Evaluation (EuroSCORE) II has not been tested yet for predicting long-term mortality. This study was undertaken to evaluate the relationship between EuroSCORE II and long-term mortality and to develop a new algorithm based on EuroSCORE II factors to predict long-term survival after cardiac surgery. Complete data on 10,033 patients who underwent major cardiac surgery during a 7-year period were retrieved from three prospective institutional databases and linked with the Italian Tax Register Information System. Mortality at follow-up was analyzed with time-to-event analysis. The Kaplan-Meier estimates of survival at 1 and 5 were, respectively, 95.0% ± 0.2% and 84.7% ± 0.4%. Both discrimination and calibration of EuroSCORE II decreased in the prediction of 1-year and 5-year mortality. Nonetheless, EuroSCORE II was confirmed to be an independent predictor of long-term mortality with a nonlinear trend. Several EuroSCORE II variables were independent risk factors for long-term mortality in a regression model, most of all very low ejection fraction (less than 20%), salvage operation, and dialysis. In the final model, isolated mitral valve surgery and isolated coronary artery bypass graft surgery were associated with improved long-term survival. The EuroSCORE II cannot be considered a direct estimator of long-term risk of death, as its performance fades for mortality at follow-up longer than 30 days. Nonetheless, it is nonlinearly associated with long-term mortality, and most of its variables are risk factors for long-term mortality. Hence, they can be used in a different algorithm to stratify the risk of long-term mortality after surgery. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  14. Multi-scale predictions of coniferous forest mortality in the northern hemisphere

    Science.gov (United States)

    McDowell, N. G.

    2015-12-01

    Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.

  15. Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease: The SADL Model.

    Science.gov (United States)

    Morisset, Julie; Vittinghoff, Eric; Elicker, Brett M; Hu, Xiaowen; Le, Stephanie; Ryu, Jay H; Jones, Kirk D; Haemel, Anna; Golden, Jeffrey A; Boin, Francesco; Ley, Brett; Wolters, Paul J; King, Talmadge E; Collard, Harold R; Lee, Joyce S

    2017-11-01

    Interstitial lung disease (ILD) is an important cause of morbidity and mortality in patients with scleroderma (Scl). Risk prediction and prognostication in patients with Scl-ILD are challenging because of heterogeneity in the disease course. We aimed to develop a clinical mortality risk prediction model for Scl-ILD. Patients with Scl-ILD were identified from two ongoing longitudinal cohorts: 135 patients at the University of California, San Francisco (derivation cohort) and 90 patients at the Mayo Clinic (validation cohort). Using these two separate cohorts, a mortality risk prediction model was developed and validated by testing every potential candidate Cox model, each including three or four variables of a possible 19 clinical predictors, for time to death. Model discrimination was assessed using the C-index. Three variables were included in the final risk prediction model (SADL): ever smoking history, age, and diffusing capacity of the lung for carbon monoxide (% predicted). This continuous model had similar performance in the derivation (C-index, 0.88) and validation (C-index, 0.84) cohorts. We created a point scoring system using the combined cohort (C-index, 0.82) and used it to identify a classification with low, moderate, and high mortality risk at 3 years. The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  16. Validation of CRIB II for prediction of mortality in premature babies.

    Science.gov (United States)

    Rastogi, Pallav Kumar; Sreenivas, V; Kumar, Nirmal

    2010-02-01

    Validation of Clinical Risk Index for Babies (CRIB II) score in predicting the neonatal mortality in preterm neonates < or = 32 weeks gestational age. Prospective cohort study. Tertiary care neonatal unit. 86 consecutively born preterm neonates with gestational age < or = 32 weeks. The five variables related to CRIB II were recorded within the first hour of admission for data analysis. The receiver operating characteristics (ROC) curve was used to check the accuracy of the mortality prediction. HL Goodness of fit test was used to see the discrepancy between observed and expected outcomes. A total of 86 neonates (males 59.6% mean birthweight: 1228 +/- 398 grams; mean gestational age: 28.3 +/- 2.4 weeks) were enrolled in the study, of which 17 (19.8%) left hospital against medical advice (LAMA) before reaching the study end point. Among 69 neonates completing the study, 24 (34.8%) had adverse outcome during hospital stay and 45 (65.2%) had favorable outcome. CRIB II correctly predicted adverse outcome in 90.3% (Hosmer Lemeshow goodness of fit test P=0.6). Area under curve (AUC) for CRIB II was 0.9032. In intention to treat analysis with LAMA cases included as survivors, the mortality prediction was 87%. If these were included as having died then mortality prediction was 83.1%. The CRIB II score was found to be a good predictive instrument for mortality in preterm infants < or = 32 weeks gestation.

  17. Hepatic Venous Pressure Gradient Predicts Long-Term Mortality in Patients with Decompensated Cirrhosis

    Science.gov (United States)

    Kim, Tae Yeob; Lee, Jae Gon; Kim, Ji Yeoun; Kim, Sun Min; Kim, Jinoo; Jeong, Woo Kyoung

    2016-01-01

    Purpose The present study aimed to investigate the role of hepatic venous pressure gradient (HVPG) for prediction of long-term mortality in patients with decompensated cirrhosis. Materials and Methods Clinical data from 97 non-critically-ill cirrhotic patients with HVPG measurements were retrospectively and consecutively collected between 2009 and 2012. Patients were classified according to clinical stages and presence of ascites. The prognostic accuracy of HVPG for death, survival curves, and hazard ratios were analyzed. Results During a median follow-up of 24 (interquartile range, 13-36) months, 22 patients (22.7%) died. The area under the receiver operating characteristics curves of HVPG for predicting 1-year, 2-year, and overall mortality were 0.801, 0.737, and 0.687, respectively (all p17 mm Hg, respectively (p=0.015). In the ascites group, the mortality rates at 1 and 2 years were 3.9% and 17.6% with HVPG ≤17 mm Hg and 17.5% and 35.2% with HVPG >17 mm Hg, respectively (p=0.044). Regarding the risk factors for mortality, both HVPG and model for end-stage liver disease were positively related with long-term mortality in all patients. Particularly, for the patients with ascites, both prothrombin time and HVPG were independent risk factors for predicting poor outcomes. Conclusion HVPG is useful for predicting the long-term mortality in patients with decompensated cirrhosis, especially in the presence of ascites. PMID:26632394

  18. A Satellite Mortality Study to Support Space Systems Lifetime Prediction

    Science.gov (United States)

    Fox, George; Salazar, Ronald; Habib-Agahi, Hamid; Dubos, Gregory

    2013-01-01

    Estimating the operational lifetime of satellites and spacecraft is a complex process. Operational lifetime can differ from mission design lifetime for a variety of reasons. Unexpected mortality can occur due to human errors in design and fabrication, to human errors in launch and operations, to random anomalies of hardware and software or even satellite function degradation or technology change, leading to unrealized economic or mission return. This study focuses on data collection of public information using, for the first time, a large, publically available dataset, and preliminary analysis of satellite lifetimes, both operational lifetime and design lifetime. The objective of this study is the illustration of the relationship of design life to actual lifetime for some representative classes of satellites and spacecraft. First, a Weibull and Exponential lifetime analysis comparison is performed on the ratio of mission operating lifetime to design life, accounting for terminated and ongoing missions. Next a Kaplan-Meier survivor function, standard practice for clinical trials analysis, is estimated from operating lifetime. Bootstrap resampling is used to provide uncertainty estimates of selected survival probabilities. This study highlights the need for more detailed databases and engineering reliability models of satellite lifetime that include satellite systems and subsystems, operations procedures and environmental characteristics to support the design of complex, multi-generation, long-lived space systems in Earth orbit.

  19. Prediction of mortality 1 year after hospital admission.

    LENUS (Irish Health Repository)

    Kellett, J

    2012-09-01

    Hospital admission, especially for the elderly, can be a seminal event as many patients die within a year. This study reports the prediction of death within a year of admission to hospital of the Simple Clinical Score (SCS) and ECG dispersion mapping (ECG-DM). ECG-DM is a novel technique that analyzes low-amplitude ECG oscillations and reports them as the myocardial micro-alternation index (MMI).

  20. Comparing observed and predicted mortality among ICUs using different prognostic systems: why do performance assessments differ?

    Science.gov (United States)

    Kramer, Andrew A; Higgins, Thomas L; Zimmerman, Jack E

    2015-02-01

    To compare ICU performance using standardized mortality ratios generated by the Acute Physiology and Chronic Health Evaluation IVa and a National Quality Forum-endorsed methodology and examine potential reasons for model-based standardized mortality ratio differences. Retrospective analysis of day 1 hospital mortality predictions at the ICU level using Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models on the same patient cohort. Forty-seven ICUs at 36 U.S. hospitals from January 2008 to May 2013. Eighty-nine thousand three hundred fifty-three consecutive unselected ICU admissions. None. We assessed standardized mortality ratios for each ICU using data for patients eligible for Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum predictions in order to compare unit-level model performance, differences in ICU rankings, and how case-mix adjustment might explain standardized mortality ratio differences. Hospital mortality was 11.5%. Overall standardized mortality ratio was 0.89 using Acute Physiology and Chronic Health Evaluation IVa and 1.07 using National Quality Forum, the latter having a widely dispersed and multimodal standardized mortality ratio distribution. Model exclusion criteria eliminated mortality predictions for 10.6% of patients for Acute Physiology and Chronic Health Evaluation IVa and 27.9% for National Quality Forum. The two models agreed on the significance and direction of standardized mortality ratio only 45% of the time. Four ICUs had standardized mortality ratios significantly less than 1.0 using Acute Physiology and Chronic Health Evaluation IVa, but significantly greater than 1.0 using National Quality Forum. Two ICUs had standardized mortality ratios exceeding 1.75 using National Quality Forum, but nonsignificant performance using Acute Physiology and Chronic Health Evaluation IVa. Stratification by patient and institutional characteristics indicated that units caring for more

  1. Prediction of morbidity and mortality in patients with type 2 diabetes

    Directory of Open Access Journals (Sweden)

    Brian J. Wells

    2013-06-01

    Full Text Available Introduction. The objective of this study was to create a tool that accurately predicts the risk of morbidity and mortality in patients with type 2 diabetes according to an oral hypoglycemic agent.Materials and Methods. The model was based on a cohort of 33,067 patients with type 2 diabetes who were prescribed a single oral hypoglycemic agent at the Cleveland Clinic between 1998 and 2006. Competing risk regression models were created for coronary heart disease (CHD, heart failure, and stroke, while a Cox regression model was created for mortality. Propensity scores were used to account for possible treatment bias. A prediction tool was created and internally validated using tenfold cross-validation. The results were compared to a Framingham model and a model based on the United Kingdom Prospective Diabetes Study (UKPDS for CHD and stroke, respectively.Results and Discussion. Median follow-up for the mortality outcome was 769 days. The numbers of patients experiencing events were as follows: CHD (3062, heart failure (1408, stroke (1451, and mortality (3661. The prediction tools demonstrated the following concordance indices (c-statistics for the specific outcomes: CHD (0.730, heart failure (0.753, stroke (0.688, and mortality (0.719. The prediction tool was superior to the Framingham model at predicting CHD and was at least as accurate as the UKPDS model at predicting stroke.Conclusions. We created an accurate tool for predicting the risk of stroke, coronary heart disease, heart failure, and death in patients with type 2 diabetes. The calculator is available online at http://rcalc.ccf.org under the heading “Type 2 Diabetes” and entitled, “Predicting 5-Year Morbidity and Mortality.” This may be a valuable tool to aid the clinician’s choice of an oral hypoglycemic, to better inform patients, and to motivate dialogue between physician and patient.

  2. Predictability Analysis of PM10 Concentrations in Budapest

    Science.gov (United States)

    Ferenczi, Zita

    2013-04-01

    Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

  3. Do causal concentration-response functions exist? A critical review of associational and causal relations between fine particulate matter and mortality.

    Science.gov (United States)

    Cox, Louis Anthony Tony

    2017-08-01

    Concentration-response (C-R) functions relating concentrations of pollutants in ambient air to mortality risks or other adverse health effects provide the basis for many public health risk assessments, benefits estimates for clean air regulations, and recommendations for revisions to existing air quality standards. The assumption that C-R functions relating levels of exposure and levels of response estimated from historical data usefully predict how future changes in concentrations would change risks has seldom been carefully tested. This paper critically reviews literature on C-R functions for fine particulate matter (PM2.5) and mortality risks. We find that most of them describe historical associations rather than valid causal models for predicting effects of interventions that change concentrations. The few papers that explicitly attempt to model causality rely on unverified modeling assumptions, casting doubt on their predictions about effects of interventions. A large literature on modern causal inference algorithms for observational data has been little used in C-R modeling. Applying these methods to publicly available data from Boston and the South Coast Air Quality Management District around Los Angeles shows that C-R functions estimated for one do not hold for the other. Changes in month-specific PM2.5 concentrations from one year to the next do not help to predict corresponding changes in average elderly mortality rates in either location. Thus, the assumption that estimated C-R relations predict effects of pollution-reducing interventions may not be true. Better causal modeling methods are needed to better predict how reducing air pollution would affect public health.

  4. Predicting of mortality in patients with intracrani al hemorrhage: A review article

    Directory of Open Access Journals (Sweden)

    Farzad Rahmani

    2014-11-01

    Full Text Available Introduction: Stroke is one of the important and common diseases, which can lead to permanent disability or even death to people. Intracranial hemorrhage (ICH is a type of stroke that is associated with high mortality despite improved diagnostic and treatment methods, as well as the mortality rate remains high. Methods: In the present review article, reputable internet databases since 2000 were analyzed. Studies that discussed the predicting mortality of ICH were included in this review. Results: For predicting the mortality rates in patients with primary ICH, physicians use several methods such as level of consciousness, bleeding volume and multiple rating systems. In this review, we introduce three scoring system of ICH in patients with ICH. Conclusion: Perhaps its cut-off point of these three score systems were different in different societies according to conditions and facilities therefore it is needed to review these scores and record their results in different societies.

  5. Development of Indoor Air Pollution Concentration Prediction by Geospatial Analysis

    Directory of Open Access Journals (Sweden)

    Adyati Pradini Yudison

    2015-07-01

    Full Text Available People living near busy roads are potentially exposed to traffic-induced air pollutants. The pollutants may intrude into the indoor environment, causing health risks to the occupants. Prediction of pollutant exposure therefore is of great importance for impact assessment and policy making related to environmentally sustainable transport. This study involved the selection of spatial interpolation methods that can be used for prediction of indoor air quality based on outdoor pollutant mapping without indoor measurement data. The research was undertaken in the densely populated area of Karees, Bandung, Indonesia. The air pollutant NO2 was monitored in this area as a preliminary study. Nitrogen dioxide concentrations were measured by passive diffusion tube. Outdoor NO2 concentrations were measured at 94 locations, consisting of 30 roadside and 64 outdoor locations. Residential indoor NO2 concentrations were measured at 64 locations. To obtain a spatially continuous air quality map, the spatial interpolation methods of inverse distance weighting (IDW and Kriging were applied. Selection of interpolation method was done based on the smallest root mean square error (RMSE and standard deviation (SD. The most appropriate interpolation method for outdoor NO2 concentration mapping was Kriging with an SD value of 5.45 µg/m3 and an RMSE value of 5.45 µg/m3, while for indoor NO2 concentration mapping the IDW was best fitted with an RMSE value of 5.92 µg/m3 and an SD value of 5.92 µg/m3.

  6. Circulating CD147 predicts mortality in advanced hepatocellular carcinoma.

    Science.gov (United States)

    Lee, Aimei; Rode, Anthony; Nicoll, Amanda; Maczurek, Annette E; Lim, Lucy; Lim, Seok; Angus, Peter; Kronborg, Ian; Arachchi, Niranjan; Gorelik, Alexandra; Liew, Danny; Warner, Fiona J; McCaughan, Geoffrey W; McLennan, Susan V; Shackel, Nicholas A

    2016-02-01

    The glycoprotein CD147 has a role in tumor progression, is readily detectable in the circulation, and is abundantly expressed in hepatocellular carcinoma (HCC). Advanced HCC patients are a heterogeneous group with some individuals having dismal survival. The aim of this study was to examine circulating soluble CD147 levels as a prognostic marker in HCC patients. CD147 was measured in 277 patients (110 HCC, 115 chronic liver disease, and 52 non-liver disease). Clinical data included etiology, tumor progression, Barcelona Clinic Liver Cancer (BCLC) stage, and treatment response. Patients with HCC were stratified into two groups based upon the 75th percentile of CD147 levels (24 ng/mL). CD147 in HCC correlated inversely with poor survival (P = 0.031). Increased CD147 predicted poor survival in BCLC stages C and D (P = 0.045), and CD147 levels >24 ng/mL predicted a significantly diminished 90-day and 180-day survival time (hazard ratio [HR] = 6.1; 95% confidence interval [CI]: 2.1-63.2; P = 0.0045 and HR = 2.8; 95% CI: 1.2-12.6; P = 0.028, respectively). In BCLC stage C, CD147 predicted prognosis; levels >24 ng/mL were associated with a median survival of 1.5 months compared with 6.5 months with CD147 levels ≤24 ng/mL (P = 0.03). CD147 also identified patients with a poor prognosis independent from treatment frequency, modality, and tumor size. Circulating CD147 is an independent marker of survival in advanced HCC. CD147 requires further evaluation as a potential new prognostic measure in HCC to identify patients with advanced disease who have a poor prognosis. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  7. Multi-scale predictions of massive conifer mortality due to chronic temperature rise

    Science.gov (United States)

    McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.

    2016-03-01

    Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

  8. Limitations of Cox Proportional Hazards Analysis in Mortality Prediction of Patients with Acute Coronary Syndrome

    Directory of Open Access Journals (Sweden)

    Babińska Magdalena

    2015-12-01

    Full Text Available The aim of this study was to evaluate the possibility of incorrect assessment of mortality risk factors in a group of patients affected by acute coronary syndrome, due to the lack of hazard proportionality in the Cox regression model. One hundred and fifty consecutive patients with acute coronary syndrome (ACS and no age limit were enrolled. Univariable and multivariable Cox proportional hazard analyses were performed. The proportional hazard assumptions were verified using Schoenfeld residuals, χ2 test and rank correlation coefficient t between residuals and time. In the total group of 150 patients, 33 (22.0% deaths from any cause were registered in the follow-up time period of 64 months. The non-survivors were significantly older and had increased prevalence of diabetes and erythrocyturia, longer history of coronary artery disease, higher concentrations of serum creatinine, cystatin C, uric acid, glucose, C-reactive protein (CRP, homocysteine and B-type natriuretic peptide (NT-proBNP, and lower concentrations of serum sodium. No significant differences in echocardiography parameters were observed between groups. The following factors were risk of death factors and fulfilled the proportional hazard assumption in the univariable model: smoking, occurrence of diabetes and anaemia, duration of coronary artery disease, and abnormal serum concentrations of uric acid, sodium, homocysteine, cystatin C and NT-proBNP, while in the multivariable model, the risk of death factors were: smoking and elevated concentrations of homocysteine and NT-proBNP. The study has demonstrated that violation of the proportional hazard assumption in the Cox regression model may lead to creating a false model that does not include only time-independent predictive factors.

  9. Using Wind Tunnels to Predict Bird Mortality in Wind Farms: The Case of Griffon Vultures

    OpenAIRE

    de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F. E.

    2012-01-01

    Background: Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. Methodology/Principal Findings: As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topo...

  10. Plasma Vascular Endothelial Growth Factor Concentration and Alveolar Nitric Oxide as Potential Predictors of Disease Progression and Mortality in Idiopathic Pulmonary Fibrosis

    Directory of Open Access Journals (Sweden)

    Jalpa Kotecha

    2016-09-01

    Full Text Available Background: Declining lung function signifies disease progression in idiopathic pulmonary fibrosis (IPF. Vascular endothelial growth factor (VEGF concentration is associated with declining lung function in 6 and 12-month studies. Alveolar nitric oxide concentration (CANO is increased in patients with IPF, however its significance is unclear. This study investigated whether baseline plasma VEGF concentration and CANO are associated with disease progression or mortality in IPF. Methods: 27 IPF patients were studied (maximum follow-up 65 months. Baseline plasma VEGF concentration, CANO and pulmonary function tests (PFTs were measured. PFTs were performed the preceding year and subsequent PFTs and data regarding mortality were collected. Disease progression was defined as one of: death, relative decrease of ≥10% in baseline forced vital capacity (FVC % predicted, or relative decrease of ≥15% in baseline single breath diffusion capacity of carbon monoxide (TLCO-SB % predicted. Results: Plasma VEGF concentration was not associated with progression-free survival or mortality. There was a trend towards shorter time to disease progression and death with higher CANO. CANO was significantly higher in patients with previous declining versus stable lung function. Conclusion: The role of VEGF in IPF remains uncertain. It may be of value to further investigate CANO in IPF.

  11. Usefulness of serum interleukin-18 in predicting cardiovascular mortality in patients with chronic kidney disease--systems and clinical approach.

    Science.gov (United States)

    Formanowicz, Dorota; Wanic-Kossowska, Maria; Pawliczak, Elżbieta; Radom, Marcin; Formanowicz, Piotr

    2015-12-16

    The aim of this study was to check if serum interleukin-18 (IL-18) predicts 2-year cardiovascular mortality in patients at various stages of chronic kidney disease (CKD) and history of acute myocardial infarction (AMI) within the previous year. Diabetes mellitus was one of the key factors of exclusion. It was found that an increase in serum concentration of IL-18 above the cut-off point (1584.5 pg/mL) was characterized by 20.63-fold higher risk of cardiovascular deaths among studied patients. IL-18 serum concentration was found to be superior to the well-known cardiovascular risk parameters, like high sensitivity C-reactive protein (hsCRP), carotid intima media thickness (CIMT), glomerular filtration rate, albumins, ferritin, N-terminal prohormone of brain natriuretic peptide (NT-proBNP) in prognosis of cardiovascular mortality. The best predictive for IL-18 were 4 variables, such as CIMT, NT-proBNP, albumins and hsCRP, as they predicted its concentration at 89.5%. Concluding, IL-18 seems to be important indicator and predictor of cardiovascular death in two-year follow-up among non-diabetic patients suffering from CKD, with history of AMI in the previous year. The importance of IL-18 in the process of atherosclerotic plaque formation has been confirmed by systems analysis based on a formal model expressed in the language of Petri nets theory.

  12. Cognitive impairment as assessed by a short form of MMSE was predictive of mortality

    DEFF Research Database (Denmark)

    Schultz-Larsen, Kirsten; Rahmanfard, Naghmeh; Kreiner, Svend

    2008-01-01

    OBJECTIVE: This study explores the association between cognitive impairment and mortality in late senescence. A specific purpose was to validate the ability of a short form of the Mini-Mental State Examination (MMSE) in predicting mortality. STUDY DESIGN AND SETTING: The cognition-mortality link,...... chronic diseases and mortality. A short, valid MMSE subscale, which was a powerful predictor of mortality especially among men, is attractive for research and clinical practice......., as assessed by the original MMSE and D-MMSE (a subscale associated to dementia) was estimated on a community sample of 1,111 older people using Cox proportional hazards models. RESULTS: Impaired cognitive function as assessed by both the original MMSE and D-MMSE predicted mortality in older men and women over...... long intervals. The association persisted after controlling for sociodemographic variables, Body Mass Index, mobility, and comorbidity and was unaffected by self-reported specific chronic diseases in both men and women. In addition, disease related risk of mortality was substantially reduced...

  13. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality

    DEFF Research Database (Denmark)

    Collaboration, Emerging Risk Factors; Erqou, Sebhat; Kaptoge, Stephen

    2009-01-01

    were recorded, including 9336 CHD outcomes, 1903 ischemic strokes, 338 hemorrhagic strokes, 751 unclassified strokes, 1091 other vascular deaths, 8114 nonvascular deaths, and 242 deaths of unknown cause. Within-study regression analyses were adjusted for within-person variation and combined using meta.......02-1.18) for ischemic stroke, 1.01 (95% CI, 0.98-1.05) for the aggregate of nonvascular mortality, 1.00 (95% CI, 0.97-1.04) for cancer deaths, and 1.00 (95% CI, 0.95-1.06) for nonvascular deaths other than cancer. CONCLUSION: Under a wide range of circumstances, there are continuous, independent, and modest......CONTEXT: Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein-like particle, may be associated with risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationship of Lp(a) concentration with risk of major vascular...

  14. Comparing predicted estrogen concentrations with measurements in US waters

    International Nuclear Information System (INIS)

    Kostich, Mitch; Flick, Robert; Martinson, John

    2013-01-01

    The range of exposure rates to the steroidal estrogens estrone (E1), beta-estradiol (E2), estriol (E3), and ethinyl estradiol (EE2) in the aquatic environment was investigated by modeling estrogen introduction via municipal wastewater from sewage plants across the US. Model predictions were compared to published measured concentrations. Predictions were congruent with most of the measurements, but a few measurements of E2 and EE2 exceed those that would be expected from the model, despite very conservative model assumptions of no degradation or in-stream dilution. Although some extreme measurements for EE2 may reflect analytical artifacts, remaining data suggest concentrations of E2 and EE2 may reach twice the 99th percentile predicted from the model. The model and bulk of the measurement data both suggest that cumulative exposure rates to humans are consistently low relative to effect levels, but also suggest that fish exposures to E1, E2, and EE2 sometimes substantially exceed chronic no-effect levels. -- Highlights: •Conservatively modeled steroidal estrogen concentrations in ambient water. •Found reasonable agreement between model and published measurements. •Model and measurements agree that risks to humans are remote. •Model and measurements agree significant questions remain about risk to fish. •Need better understanding of temporal variations and their impact on fish. -- Our model and published measurements for estrogens suggest aquatic exposure rates for humans are below potential effect levels, but fish exposure sometimes exceeds published no-effect levels

  15. Factors Influencing the Predictive Power of Models for Predicting Mortality and/or Heart Failure Hospitalization in Patients With Heart Failure

    NARCIS (Netherlands)

    Ouwerkerk, Wouter; Voors, Adriaan A.; Zwinderman, Aeilko H.

    2014-01-01

    The present paper systematically reviews and compares existing prediction models in order to establish the strongest variables, models, and model characteristics in patients with heart failure predicting outcome. To improve decision making accurately predicting mortality and heart-failure

  16. Use of APACHE II and SAPS II to predict mortality for hemorrhagic and ischemic stroke patients.

    Science.gov (United States)

    Moon, Byeong Hoo; Park, Sang Kyu; Jang, Dong Kyu; Jang, Kyoung Sool; Kim, Jong Tae; Han, Yong Min

    2015-01-01

    We studied the applicability of the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) in patients admitted to the intensive care unit (ICU) with acute stroke and compared the results with the Glasgow Coma Scale (GCS) and National Institutes of Health Stroke Scale (NIHSS). We also conducted a comparative study of accuracy for predicting hemorrhagic and ischemic stroke mortality. Between January 2011 and December 2012, ischemic or hemorrhagic stroke patients admitted to the ICU were included in the study. APACHE II and SAPS II-predicted mortalities were compared using a calibration curve, the Hosmer-Lemeshow goodness-of-fit test, and the receiver operating characteristic (ROC) curve, and the results were compared with the GCS and NIHSS. Overall 498 patients were included in this study. The observed mortality was 26.3%, whereas APACHE II and SAPS II-predicted mortalities were 35.12% and 35.34%, respectively. The mean GCS and NIHSS scores were 9.43 and 21.63, respectively. The calibration curve was close to the line of perfect prediction. The ROC curve showed a slightly better prediction of mortality for APACHE II in hemorrhagic stroke patients and SAPS II in ischemic stroke patients. The GCS and NIHSS were inferior in predicting mortality in both patient groups. Although both the APACHE II and SAPS II systems can be used to measure performance in the neurosurgical ICU setting, the accuracy of APACHE II in hemorrhagic stroke patients and SAPS II in ischemic stroke patients was superior. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Mortality, morbidity and refractoriness prediction in status epilepticus: Comparison of STESS and EMSE scores.

    Science.gov (United States)

    Giovannini, Giada; Monti, Giulia; Tondelli, Manuela; Marudi, Andrea; Valzania, Franco; Leitinger, Markus; Trinka, Eugen; Meletti, Stefano

    2017-03-01

    Status epilepticus (SE) is a neurological emergency, characterized by high short-term morbidity and mortality. We evaluated and compared two scores that have been developed to evaluate status epilepticus prognosis: STESS (Status Epilepticus Severity Score) and EMSE (Epidemiology based Mortality score in Status Epilepticus). A prospective observational study was performed on consecutive patients with SE admitted between September 2013 and August 2015. Demographics, clinical variables, STESS-3 and -4, and EMSE-64 scores were calculated for each patient at baseline. SE drug response, 30-day mortality and morbidity were the outcomes measure. 162 episodes of SE were observed: 69% had a STESS ≥3; 34% had a STESS ≥4; 51% patients had an EMSE ≥64. The 30-days mortality was 31.5%: EMSE-64 showed greater negative predictive value (NPV) (97.5%), positive predictive value (PPV) (59.8%) and accuracy in the prediction of death than STESS-3 and STESS-4 (pstatus epilepticus proved refractory to non-anaesthetic treatment. All three scales showed a high NPV (EMSE-64: 87.3%; STESS-4: 89.4%; STESS-3: 87.5%) but a low PPV (EMSE-64: 40.9%; STESS-4: 52.9%; STESS-3: 32%) for the prediction of refractoriness to first and second line drugs. This means that accuracy for the prediction of refractoriness was equally poor for all scales. EMSE-64 appears superior to STESS-3 and STESS-4 in the prediction of 30-days mortality and morbidity. All scales showed poor accuracy in the prediction of response to first and second line antiepileptic drugs. At present, there are no reliable scores capable of predicting treatment responsiveness. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

  18. COPD predicts mortality in HF: the Norwegian Heart Failure Registry.

    Science.gov (United States)

    De Blois, Jonathan; Simard, Serge; Atar, Dan; Agewall, Stefan

    2010-03-01

    Chronic obstructive pulmonary disease (COPD) and chronic heart failure (HF) are common clinical conditions that share tobacco as a risk factor. Our aim was to evaluate the prognostic impact of COPD on HF patients. The Norwegian Heart Failure Registry was used. The study included 4132 HF patients (COPD, n = 699) from 22 hospitals (mean follow-up, 13.3 months). COPD patients were older, more often smokers and diabetics, less often on beta-blockers and had a higher heart rate. They were more often in New York Heart Association (NYHA) Class III or IV (COPD, 63%; no COPD, 51%), although left ventricular ejection fraction (LVEF) distribution was similar. COPD independently predicted death (adjusted hazard ratio [HR], 1.188; 95% CI: 1.015 to 1.391; P = 0.03) along with age, creatinine, NYHA Class III/IV (HR, 1.464; 95% CI: 1.286 to 1.667) and diabetes. beta-blockers at baseline were associated with improved survival in patients with LVEF < or =40% independently of COPD. COPD is associated with a poorer survival in HF patients. COPD patients are overrated in terms of NYHA class in comparison with patients with similar LVEF. Nonetheless, NYHA class remains the strongest predictor of death in these patients. Copyright (c) 2010 Elsevier Inc. All rights reserved.

  19. [Evaluation of the capacity of the APR-DRG classification system to predict hospital mortality].

    Science.gov (United States)

    De Marco, Maria Francesca; Lorenzoni, Luca; Addari, Piero; Nante, Nicola

    2002-01-01

    Inpatient mortality has increasingly been used as an hospital outcome measure. Comparing mortality rates across hospitals requires adjustment for patient risks before making inferences about quality of care based on patient outcomes. Therefore it is essential to dispose of well performing severity measures. The aim of this study is to evaluate the ability of the All Patient Refined DRG system to predict inpatient mortality for congestive heart failure, myocardial infarction, pneumonia and ischemic stroke. Administrative records were used in this analysis. We used two statistics methods to assess the ability of the APR-DRG to predict mortality: the area under the receiver operating characteristics curve (referred to as the c-statistic) and the Hosmer-Lemeshow test. The database for the study included 19,212 discharges for stroke, pneumonia, myocardial infarction and congestive heart failure from fifteen hospital participating in the Italian APR-DRG Project. A multivariate analysis was performed to predict mortality for each condition in study using age, sex and APR-DRG risk mortality subclass as independent variables. Inpatient mortality rate ranges from 9.7% (pneumonia) to 16.7% (stroke). Model discrimination, calculated using the c-statistic, was 0.91 for myocardial infarction, 0.68 for stroke, 0.78 for pneumonia and 0.71 for congestive heart failure. The model calibration assessed using the Hosmer-Leme-show test was quite good. The performance of the APR-DRG scheme when used on Italian hospital activity records is similar to that reported in literature and it seems to improve by adding age and sex to the model. The APR-DRG system does not completely capture the effects of these variables. In some cases, the better performance might be due to the inclusion of specific complications in the risk-of-mortality subclass assignment.

  20. Hypotension, bedridden, leukocytosis, thrombocytopenia and elevated serum creatinine predict mortality in geriatric patients with fever.

    Science.gov (United States)

    Chung, Min-Hsien; Chu, Feng-Yuan; Yang, Tzu-Meng; Lin, Hung-Jung; Chen, Jiann-Hwa; Guo, How-Ran; Vong, Si-Chon; Su, Shih-Bin; Huang, Chien-Cheng; Hsu, Chien-Chin

    2015-07-01

    The geriatric population (aged ≥65 years) accounts for 12-24% of all emergency department (ED) visits. Of them, 10% have a fever, 70-90% will be admitted and 7-10% of will die within a month. Therefore, mortality prediction and appropriate disposition after ED treatment are of great concern for geriatric patients with fever. We tried to identify independent mortality predictors of geriatric patients with fever, and combine these predictors to predict their mortality. We enrolled consecutive geriatric patients visiting the ED between 1 June and 21 July 2010 with the following criteria of fever: a tympanic temperature ≥37.2°C or a baseline temperature elevated ≥1.3°C. We used 30-day mortality as the primary end-point. A total of 330 patients were enrolled. Hypotension, bedridden, leukocytosis, thrombocytopenia and serum creatinine >2 mg/dL, but not age, were independently associated with 30-day mortality. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) ranged from 18.2% to 90.9%, 34.7% to 100%, 9.0% to 100% and 94.5% to 98.2%, respectively, depending on how many predictors there were. The 30-day mortality increased with the number of independent mortality predictors. With at least four predictors, 100% of the patients died within 30 days. With none of the predictors, just 1.8% died. These findings might help physicians make decisions about geriatric patients with fever. © 2014 Japan Geriatrics Society.

  1. Predicting in-hospital mortality after redo cardiac operations: development of a preoperative scorecard.

    Science.gov (United States)

    Launcelott, Sebastian; Ouzounian, Maral; Buth, Karen J; Légaré, Jean-Francois

    2012-09-01

    The present study generated a risk model and an easy-to-use scorecard for the preoperative prediction of in-hospital mortality for patients undergoing redo cardiac operations. All patients who underwent redo cardiac operations in which the initial and subsequent procedures were performed through a median sternotomy were included. A logistic regression model was created to identify independent preoperative predictors of in-hospital mortality. The results were then used to create a scorecard predicting operative risk. A total of 1,521 patients underwent redo procedures between 1995 and 2010 at a single institution. Coronary bypass procedures were the most common previous (58%) or planned operations (54%). The unadjusted in-hospital mortality for all redo cases was higher than for first-time procedures (9.7% vs. 3.4%; pscorecard was generated using these independent predictors, stratifying patients undergoing redo cardiac operations into 6 risk categories of in-hospital mortality ranging from risk to >40%. Reoperation represents a significant proportion of modern cardiac surgical procedures and is often associated with significantly higher mortality than first-time operations. We created an easy-to-use scorecard to assist clinicians in estimating operative mortality to ensure optimal decision making in the care of patients facing redo cardiac operations. Copyright © 2012 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  2. Do plasma concentrations of apelin predict prognosis in patients with advanced heart failure?

    Science.gov (United States)

    Dalzell, Jonathan R; Jackson, Colette E; Chong, Kwok S; McDonagh, Theresa A; Gardner, Roy S

    2014-01-01

    Apelin is an endogenous vasodilator and inotrope, plasma concentrations of which are reduced in advanced heart failure (HF). We determined the prognostic significance of plasma concentrations of apelin in advanced HF. Plasma concentrations of apelin were measured in 182 patients with advanced HF secondary to left ventricular systolic dysfunction. The predictive value of apelin for the primary end point of all-cause mortality was assessed over a median follow-up period of 544 (IQR: 196-923) days. In total, 30 patients (17%) reached the primary end point. Of those patients with a plasma apelin concentration above the median, 14 (16%) reached the primary end point compared with 16 (17%) of those with plasma apelin levels below the median (p = NS). NT-proBNP was the most powerful prognostic marker in this population (log rank statistic: 10.37; p = 0.001). Plasma apelin concentrations do not predict medium to long-term prognosis in patients with advanced HF secondary to left ventricular systolic dysfunction.

  3. Lactate clearance cut off for early mortality prediction in adult sepsis and septic shock patients

    Science.gov (United States)

    Sinto, R.; Widodo, D.; Pohan, H. T.

    2018-03-01

    Previous lactate clearance cut off for early mortality prediction in sepsis and septic shock patient was determined by consensus from small sample size-study. We investigated the best lactate clearance cut off and its ability to predict early mortality in sepsis and septic shock patients. This cohort study was conducted in Intensive Care Unit of CiptoMangunkusumo Hospital in 2013. Patients’ lactate clearance and eight other resuscitationendpoints were recorded, and theoutcome was observed during the first 120 hours. The clearance cut off was determined using receiver operating characteristic (ROC) analysis, and its ability was investigated with Cox’s proportional hazard regression analysis using other resuscitation endpoints as confounders. Total of 268 subjects was included, of whom 70 (26.11%) subjects died within the first 120 hours. The area under ROC of lactate clearance to predict early mortality was 0.78 (95% % confidence interval [CI] 0.71-0.84) with best cut off was <7.5% (sensitivity and specificity 88.99% and 81.4% respectively). Compared with group achieving lactate clearance target, group not achieving lactate clearance target had to increase early mortality risk (adjusted hazard ratio 13.42; 95%CI 7.19-25.07). In conclusion, the best lactate clearance cut off as anearly mortality predictor in sepsis and septic shock patients is 7.5%.

  4. Prognostic durability of liver fibrosis tests and improvement in predictive performance for mortality by combining tests.

    Science.gov (United States)

    Bertrais, Sandrine; Boursier, Jérôme; Ducancelle, Alexandra; Oberti, Frédéric; Fouchard-Hubert, Isabelle; Moal, Valérie; Calès, Paul

    2017-06-01

    There is currently no recommended time interval between noninvasive fibrosis measurements for monitoring chronic liver diseases. We determined how long a single liver fibrosis evaluation may accurately predict mortality, and assessed whether combining tests improves prognostic performance. We included 1559 patients with chronic liver disease and available baseline liver stiffness measurement (LSM) by Fibroscan, aspartate aminotransferase to platelet ratio index (APRI), FIB-4, Hepascore, and FibroMeter V2G . Median follow-up was 2.8 years during which 262 (16.8%) patients died, with 115 liver-related deaths. All fibrosis tests were able to predict mortality, although APRI (and FIB-4 for liver-related mortality) showed lower overall discriminative ability than the other tests (differences in Harrell's C-index: P fibrosis, 1 year in patients with significant fibrosis, and liver disease (MELD) score testing sets. In the training set, blood tests and LSM were independent predictors of all-cause mortality. The best-fit multivariate model included age, sex, LSM, and FibroMeter V2G with C-index = 0.834 (95% confidence interval, 0.803-0.862). The prognostic model for liver-related mortality included the same covariates with C-index = 0.868 (0.831-0.902). In the testing set, the multivariate models had higher prognostic accuracy than FibroMeter V2G or LSM alone for all-cause mortality and FibroMeter V2G alone for liver-related mortality. The prognostic durability of a single baseline fibrosis evaluation depends on the liver fibrosis level. Combining LSM with a blood fibrosis test improves mortality risk assessment. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  5. A prediction model for assessing residential radon concentration in Switzerland

    International Nuclear Information System (INIS)

    Hauri, Dimitri D.; Huss, Anke; Zimmermann, Frank; Kuehni, Claudia E.; Röösli, Martin

    2012-01-01

    Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th–90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40–111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69–215 Bq/m³) in the medium category, and 219 Bq/m³ (108–427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be

  6. Variation in Annual Volume at a University Hospital Does Not Predict Mortality for Pancreatic Resections

    Directory of Open Access Journals (Sweden)

    Rita A. Mukhtar

    2008-01-01

    Full Text Available Annual volume of pancreatic resections has been shown to affect mortality rates, prompting recommendations to regionalize these procedures to high-volume hospitals. Implementation has been difficult, given the paucity of high-volume centers and the logistical hardships facing patients. Some studies have shown that low-volume hospitals achieve good outcomes as well, suggesting that other factors are involved. We sought to determine whether variations in annual volume affected patient outcomes in 511 patients who underwent pancreatic resections at the University of California, San Francisco between 1990 and 2005. We compared postoperative mortality and complication rates between low, medium, or high volume years, designated by the number of resections performed, adjusting for patient characteristics. Postoperative mortality rates did not differ between high volume years and medium/low volume years. As annual hospital volume of pancreatic resections may not predict outcome, identification of actual predictive factors may allow low-volume centers to achieve excellent outcomes.

  7. Applications of Machine learning in Prediction of Breast Cancer Incidence and Mortality

    International Nuclear Information System (INIS)

    Helal, N.; Sarwat, E.

    2012-01-01

    Breast cancer is one of the leading causes of cancer deaths for the female population in both developed and developing countries. In this work we have used the baseline descriptive data about the incidence (new cancer cases) of in situ breast cancer among Wisconsin females. The documented data were from the most recent 12-years period for which data are available. Wiscons in cancer incidence and mortality (deaths due to cancer) that occurred were also considered in this work. Artificial Neural network (ANN) have been successfully applied to problems in the prediction of the number of new cancer cases and mortality. Using artificial intelligence (AI) in this study, the numbers of new cancer cases and mortality that may occur are predicted.

  8. Risk prediction models for mortality in patients with ventilator-associated pneumonia

    DEFF Research Database (Denmark)

    Larsson, Johan E; Itenov, Theis Skovsgaard; Bestle, Morten Heiberg

    2017-01-01

    the receiver operator characteristic curve (AUC). RESULTS: We identified 19 articles studying 7 different models' ability to predict mortality in VAP patients. The models were Acute Physiology and Chronic Health Evaluation (APACHE) II (9 studies, n = 1398); Clinical Pulmonary Infection Score (4 studies, n...... = 303); "Immunodeficiency, Blood pressure, Multilobular infiltrates on chest radiograph, Platelets and hospitalization 10 days before onset of VAP" (3 studies, n = 406); "VAP Predisposition, Insult Response and Organ dysfunction" (2 studies, n = 589); Sequential Organ Failure Assessment (7 studies, n......: The PubMed and EMBASE were searched in February 2016. We included studies in English that evaluated models' ability to predict the risk of mortality in patients with VAP. The reported mortality with the longest follow-up was used in the meta-analysis. Prognostic accuracy was measured with the area under...

  9. Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

    Science.gov (United States)

    Hidalgo, J Ignacio; Colmenar, J Manuel; Kronberger, Gabriel; Winkler, Stephan M; Garnica, Oscar; Lanchares, Juan

    2017-08-08

    Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections. In particular, we use the following four techniques: genetic programming, random forests, k-nearest neighbors, and grammatical evolution. We propose two new enhanced modeling algorithms for glucose prediction, namely (i) a variant of grammatical evolution which uses an optimized grammar, and (ii) a variant of tree-based genetic programming which uses a three-compartment model for carbohydrate and insulin dynamics. The predictors were trained and tested using data of ten patients from a public hospital in Spain. We analyze our experimental results using the Clarke error grid metric and see that 90% of the forecasts are correct (i.e., Clarke error categories A and B), but still even the best methods produce 5 to 10% of serious errors (category D) and approximately 0.5% of very serious errors (category E). We also propose an enhanced genetic programming algorithm that incorporates a three-compartment model into symbolic regression models to create smoothed time series of the original carbohydrate and insulin time series.

  10. Predictive Factors for Mortality and Morbidity of Ruptured Abdominal Aortic Aneurysm Repair

    Directory of Open Access Journals (Sweden)

    Manabu Shiraishi

    2012-04-01

    Conclusions: Emergency open repair can be safely performed in patients for infrarenal rAAA. In particular, we identified specific independent predictive factors of clinical examination and laboratory studies for mortality, major morbidity and renal insufficiency. [Arch Clin Exp Surg 2012; 1(2.000: 94-101

  11. Brain-Derived Neurotrophic Factor Predicts Mortality Risk in Older Women

    DEFF Research Database (Denmark)

    Krabbe, K.S.; Mortensen, E.L.; Avlund, K.

    2009-01-01

    OBJECTIVES To test the hypothesis that low circulating brain-derived neurotrophic factor (BDNF), a secretory member of the neurotrophin family that has a protective role in neurodegeneration and stress responses and a regulatory role in metabolism, predicts risk of all-cause mortality in 85-year...

  12. Predicting mortality and length-of-stay for neonatal admissions to ...

    African Journals Online (AJOL)

    Objectives: To predict neonatal mortality and length of stay (LOS) from readily available perinatal data for neonatal intensive care unit (NICU) admissions in Southern African private hospitals. Methods: Retrospective observational study using perinatal data from a large multicentre sample. Fifteen participating NICU centres ...

  13. The evaluation of CRIB II scoring system in predicting mortality in preterm newborns

    Directory of Open Access Journals (Sweden)

    Homa Babaei

    2015-02-01

    Full Text Available Background: The survival rate of premature newborns depends on gestational age, birth weight and condition when they are hospitalized. Different scoring systems to predict mortality in newborns has been designed. The purpose of this study was to evaluate value of CRIB II scoring system in predicting mortality rate of infants with birth weights less than 1500 grams. Material and Methods: In this 8 month cross - sectional study (September 2010 to April 2010 which was conducted in the NICU of Imam Reza hospital in Kermanshah, preterm newborns with birth weight less than 1500 gr and gestational age less than 32 weeks who were admitted within 12 hours after birth in the NICU ,were evaluated based on CRIB II scoring system . Results: 50 neonates out of 1360 (36.8% survived and 86 neonates(63.2% died. Average CRIB II score in newborn survived was 5.8±2.9 and in infants died was 9.8±2.9 (p <0.0001. Based on the AUC, the CRIB II score could predict about 0.85 (CI: 0.77-0.92 of mortality. Also based on the ROC curve cut-off point for scoring CRIB II, was 6.5. Conclusion: Our study showed that CRIB II has a high value( about %85 in predicting mortality in newborns with birth weights less than 1500 grams.

  14. Predictive factors for mortality in Fournier' gangrene: a series of 59 cases.

    Science.gov (United States)

    García Marín, Andrés; Turégano Fuentes, Fernando; Cuadrado Ayuso, Marta; Andueza Lillo, Juan Antonio; Cano Ballesteros, Juan Carlos; Pérez López, Mercedes

    2015-01-01

    Fournier's gangrene (FG) is the necrotizing fasciitis of the perineum and genital area and presents a high mortality rate. The aim was to assess prognostic factors for mortality, create a new mortality predictive scale and compare it with previously published scales in patients diagnosed with FG in our Emergency Department. Retrospective analysis study between 1998 and 2012. Of the 59 patients, 44 survived (74%) (S) and 15 died (26%) (D). Significant differences were found in peripheral vasculopathy (S 5 [11%]; D 6 [40%]; P=.023), hemoglobin (S 13; D 11; P=.014), hematocrit (S 37; D 31.4; P=.009), white blood cells (S 17,400; D 23,800; P=.023), serum urea (S 58; D 102; PFournier's gangrene severity index score (FGSIS) (S 4; D 7; P=.002) and Uludag Fournier's Gangrene Severity Index (UFGSI) (S 9; D 13; P=.004). Independent predictive factors were peripheral vasculopathy, serum potassium and severe sepsis criteria, and a model was created with an area under the ROC curve of 0.850 (0.760-0.973), higher than FGSIS (0.746 [0.601-0.981]) and UFGSI (0.760 [0.617-0.904]). FG showed a high mortality rate. Independent predictive factors were peripheral vasculopathy, potassium and severe sepsis criteria creating a predictive model that performed better than those previously described. Copyright © 2014 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

  15. Update of predictions of mortality from pleural mesothelioma in the Netherlands

    NARCIS (Netherlands)

    O. Segura; A. Burdorf (Alex); C.W.N. Looman (Caspar)

    2003-01-01

    textabstractAIMS: To predict the expected number of pleural mesothelioma deaths in the Netherlands from 2000 to 2028 and to study the effect of main uncertainties in the modelling technique. METHODS: Through an age-period-cohort modelling technique, age specific mortality rates

  16. Development and validation of multivariable models to predict mortality and hospitalization in patients with heart failure

    NARCIS (Netherlands)

    Voors, Adriaan A.; Ouwerkerk, Wouter; Zannad, Faiez; van Veldhuisen, Dirk J.; Samani, Nilesh J.; Ponikowski, Piotr; Ng, Leong L.; Metra, Marco; ter Maaten, Jozine M.; Lang, Chim C.; Hillege, Hans L.; van der Harst, Pim; Filippatos, Gerasimos; Dickstein, Kenneth; Cleland, John G.; Anker, Stefan D.; Zwinderman, Aeilko H.

    Introduction From a prospective multicentre multicountry clinical trial, we developed and validated risk models to predict prospective all-cause mortality and hospitalizations because of heart failure (HF) in patients with HF. Methods and results BIOSTAT-CHF is a research programme designed to

  17. Development and validation of multivariable models to predict mortality and hospitalization in patients with heart failure

    NARCIS (Netherlands)

    Voors, Adriaan A.; Ouwerkerk, Wouter; Zannad, Faiez; van Veldhuisen, Dirk J.; Samani, Nilesh J.; Ponikowski, Piotr; Ng, Leong L.; Metra, Marco; ter Maaten, Jozine M.; Lang, Chim C.; Hillege, Hans L.; van der Harst, Pim; Filippatos, Gerasimos; Dickstein, Kenneth; Cleland, John G.; Anker, Stefan D.; Zwinderman, Aeilko H.

    2017-01-01

    Introduction From a prospective multicentre multicountry clinical trial, we developed and validated risk models to predict prospective all-cause mortality and hospitalizations because of heart failure (HF) in patients with HF. Methods and results BIOSTAT-CHF is a research programme designed to

  18. Impact of Economic Conditions and Crises on Mortality and its Predictability.

    Science.gov (United States)

    Bohk, Christina; Rau, Roland

    To investigate how economic conditions and crises affect mortality and its predictability in industrialized countries, we review the related literature, and we forecast mortality developments in Spain, Hungary, and Russia-three countries which have recently undergone major transformation processes following the introduction of radical economic and political reforms. The results of our retrospective mortality forecasts from 1991 to 2009 suggest that our model can capture major changes in long-term mortality trends, and that the forecast errors it generates are usually smaller than those of other well-accepted models, like the Lee-Carter model and its coherent variant. This is because our approach is capable of modeling (1) dynamic shifts in survival improvements from younger to older ages over time, as well as (2) substantial changes in long-term trends by optionally complementing the extrapolated mortality trends in a country of interest with those of selected reference countries. However, the forecasting performance of our model is limited (like that of every model): e.g., if mortality becomes extremely volatile-as was the case in Russia after the dissolution of the Soviet Union-generating a precise forecast will depend more on luck than on methodology and expert judgment. In general, we conclude that, on their own, recent economic changes appear to have minor effects on life expectancy in industrialized countries, but that the effects of these changes are greater if they occur in conjunction with other major social and political changes.

  19. Early hospital readmission for gastrointestinal-related complications predicts long-term mortality after pancreatectomy.

    Science.gov (United States)

    Hicks, Caitlin W; Tosoian, Jeffrey J; Craig-Schapiro, Rebecca; Valero, Vicente; Cameron, John L; Eckhauser, Frederic E; Hirose, Kenzo; Makary, Martin A; Pawlik, Timothy M; Ahuja, Nita; Weiss, Matthew J; Wolfgang, Christopher L

    2015-10-01

    The purpose of this study was to investigate the prognostic significance of early (30-day) hospital readmission (EHR) on mortality after pancreatectomy. Using a prospectively collected institutional database linked with a statewide dataset, we evaluated the association between EHR and overall mortality in all patients undergoing pancreatectomy at our tertiary institution (2005 to 2010). Of 595 pancreatectomy patients, EHR occurred in 21.5%. Overall mortality was 29.4% (median follow-up 22.7 months). Patients with EHR had decreased survival compared with those who were not readmitted (P = .011). On multivariate analysis adjusting for baseline group differences, EHR for gastrointestinal-related complications was a significant independent predictor of mortality (hazard ratio 2.30, P = .001). In addition to known risk factors, 30-day readmission for gastrointestinal-related complications following pancreatectomy independently predicts increased mortality. Additional studies are necessary to identify surgical, medical, and social factors contributing to EHR, as well as interventions aimed at decreasing postpancreatectomy morbidity and mortality. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Prediction of Mortality and Causes of Death in a Burn Centre: A Retrospective Clinical Study

    Directory of Open Access Journals (Sweden)

    Celalettin Sever

    2011-09-01

    Full Text Available Aim: Mortality rates are important outcome parameters after burn. The causes of mortality have been reported differently in the literature. The aim of the study was to identify parameters that are predictive of major morbidity factors and risk of mortality in patients with burn injury. Material and Methods: This study was performed among the patients who admitted to the burn center period between December 2001 and June 2010. Within this period, demographic data, treatment, and outcomes of treatment were reviewed and analyzed. Results: The burn patients were analysed retrospectively during 9-years period between December 2001 and January 2010. Burns caused by scalding were the most frequent (69.7 % followed by flames (24.4 %. 4.30 % of the patients died because of multisystem organ failure, septicaemia and cardiac respiratory failure. Conclusions:The most common cause of mortality was multiorgan failure according to our study. The mortality rates and causes of burn centers should be investigated retrospectively between different burn centres to determine the most common cause of mortality in burn centers. 

  1. Does personality predict mortality? Results from the GAZEL French prospective cohort study.

    Science.gov (United States)

    Nabi, Hermann; Kivimäki, Mika; Zins, Marie; Elovainio, Marko; Consoli, Silla M; Cordier, Sylvaine; Ducimetière, Pierre; Goldberg, Marcel; Singh-Manoux, Archana

    2008-04-01

    Majority of studies on personality and physical health have focused on one or two isolated personality traits. We aim to test the independent association of 10 personality traits, from three major conceptual models, with all-cause and cause-specific mortality in the French GAZEL cohort. A total of 14,445 participants, aged 39-54 in 1993, completed the personality questionnaires composed of the Bortner Type-A scale, the Buss-Durkee Hostility Inventory (for total, neurotic and reactive hostility) and the Grossarth-Maticek-Eysenck Personality Stress Inventory that assesses six personality types [cancer-prone, coronary heart disease (CHD)-prone, ambivalent, healthy, rational, anti-social]. The association between personality traits and mortality, during a mean follow-up of 12.7 years, was assessed using the Relative Index of Inequality (RII) in Cox regression. In models adjusted for age, sex, marital status and education, all-cause and cause-specific mortality were predicted by 'total hostility', its 'neurotic hostility' component as well as by 'CHD-prone', 'ambivalent' 'antisocial', and 'healthy' personality types. After mutually adjusting personality traits for each other, only high 'neurotic hostility' remained a robust predictor of excess mortality from all causes [RII = 2.62; 95% confidence interval (CI) = 1.68-4.09] and external causes (RII = 3.24; 95% CI = 1.03-10.18). 'CHD-prone' (RII = 2.23; 95% CI = 0.72-6.95) and 'anti-social' (RII = 2.13; 95% CI 0.61-6.58) personality types were associated with cardiovascular mortality and with mortality from external causes, respectively, but CIs were wider. Adjustment for potential behavioural mediators had only a modest effect on these associations. Neurotic hostility, CHD-prone personality and anti-social personality were all predictive of mortality outcomes. Further research is required to determine the precise mechanisms that contribute to these associations.

  2. Does life satisfaction predict five-year mortality in community-living older adults?

    Science.gov (United States)

    St John, Philip D; Mackenzie, Corey; Menec, Verena

    2015-01-01

    Depression and depressive symptoms predict death, but it is less clear if more general measures of life satisfaction (LS) predict death. Our objectives were to determine: (1) if LS predicts mortality over a five-year period in community-living older adults; and (2) which aspects of LS predict death. 1751 adults over the age of 65 who were living in the community were sampled from a representative population sampling frame in 1991/1992 and followed five years later. Age, gender, and education were self-reported. An index of multimorbidity and the Older American Resource Survey measured health and functional status, and the Terrible-Delightful Scale assessed overall LS as well as satisfaction with: health, finances, family, friends, housing, recreation, self-esteem, religion, and transportation. Cox proportional hazards models examined the influence of LS on time to death. 417 participants died during the five-year study period. Overall LS and all aspects of LS except finances, religion, and self-esteem predicted death in unadjusted analyses. In fully adjusted analyses, LS with health, housing, and recreation predicted death. Other aspects of LS did not predict death after accounting for functional status and multimorbidity. LS predicted death, but certain aspects of LS are more strongly associated with death. The effect of LS is complex and may be mediated or confounded by health and functional status. It is important to consider different domains of LS when considering the impact of this important emotional indicator on mortality among older adults.

  3. Predicting the probability of mortality of gastric cancer patients using decision tree.

    Science.gov (United States)

    Mohammadzadeh, F; Noorkojuri, H; Pourhoseingholi, M A; Saadat, S; Baghestani, A R

    2015-06-01

    Gastric cancer is the fourth most common cancer worldwide. This reason motivated us to investigate and introduce gastric cancer risk factors utilizing statistical methods. The aim of this study was to identify the most important factors influencing the mortality of patients who suffer from gastric cancer disease and to introduce a classification approach according to decision tree model for predicting the probability of mortality from this disease. Data on 216 patients with gastric cancer, who were registered in Taleghani hospital in Tehran,Iran, were analyzed. At first, patients were divided into two groups: the dead and alive. Then, to fit decision tree model to our data, we randomly selected 20% of dataset to the test sample and remaining dataset considered as the training sample. Finally, the validity of the model examined with sensitivity, specificity, diagnosis accuracy and the area under the receiver operating characteristic curve. The CART version 6.0 and SPSS version 19.0 softwares were used for the analysis of the data. Diabetes, ethnicity, tobacco, tumor size, surgery, pathologic stage, age at diagnosis, exposure to chemical weapons and alcohol consumption were determined as effective factors on mortality of gastric cancer. The sensitivity, specificity and accuracy of decision tree were 0.72, 0.75 and 0.74 respectively. The indices of sensitivity, specificity and accuracy represented that the decision tree model has acceptable accuracy to prediction the probability of mortality in gastric cancer patients. So a simple decision tree consisted of factors affecting on mortality of gastric cancer may help clinicians as a reliable and practical tool to predict the probability of mortality in these patients.

  4. Airborne Precursors Predict Maternal Serum Perfluoroalkyl Acid Concentrations.

    Science.gov (United States)

    Makey, Colleen M; Webster, Thomas F; Martin, Jonathan W; Shoeib, Mahiba; Harner, Tom; Dix-Cooper, Linda; Webster, Glenys M

    2017-07-05

    Human exposure to persistent perfluoroalkyl acids (PFAAs), including perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorooctanesulfonate (PFOS), can occur directly from contaminated food, water, air, and dust. However, precursors to PFAAs (PreFAAs), such as dipolyfluoroalkyl phosphates (diPAPs), fluorotelomer alcohols (FTOHs), perfluorooctyl sulfonamides (FOSAs), and sulfonamidoethanols (FOSEs), which can be biotransformed to PFAAs, may also be a source of exposure. PFAAs were analyzed in 50 maternal sera samples collected in 2007-2008 from participants in Vancouver, Canada, while PFAAs and PreFAAs were measured in matching samples of residential bedroom air collected by passive sampler and in sieved vacuum dust (<150 μm). Concentrations of PreFAAs were higher than for PFAAs in air and dust. Positive associations were discovered between airborne 10:2 FTOH and serum PFOA and PFNA and between airborne MeFOSE and serum PFOS. On average, serum PFOS concentrations were 2.3 ng/mL (95%CI: 0.40, 4.3) higher in participants with airborne MeFOSE concentrations in the highest tertile relative to the lowest tertile. Among all PFAAs, only PFNA in air and vacuum dust predicted serum PFNA. Results suggest that airborne PFAA precursors were a source of PFOA, PFNA, and PFOS exposure in this population.

  5. Variation in GYS1 interacts with exercise and gender to predict cardiovascular mortality.

    Directory of Open Access Journals (Sweden)

    Jenny Fredriksson

    Full Text Available BACKGROUND: The muscle glycogen synthase gene (GYS1 has been associated with type 2 diabetes (T2D, the metabolic syndrome (MetS, male myocardial infarction and a defective increase in muscle glycogen synthase protein in response to exercise. We addressed the questions whether polymorphism in GYS1 can predict cardiovascular (CV mortality in a high-risk population, if this risk is influenced by gender or physical activity, and if the association is independent of genetic variation in nearby apolipoprotein E gene (APOE. METHODOLOGY/PRINCIPAL FINDINGS: Polymorphisms in GYS1 (XbaIC>T and APOE (-219G>T, epsilon2/epsilon3/epsilon4 were genotyped in 4,654 subjects participating in the Botnia T2D-family study and followed for a median of eight years. Mortality analyses were performed using Cox proportional-hazards regression. During the follow-up period, 749 individuals died, 409 due to CV causes. In males the GYS1 XbaI T-allele (hazard ratio (HR 1.9 [1.2-2.9], T2D (2.5 [1.7-3.8], earlier CV events (1.7 [1.2-2.5], physical inactivity (1.9 [1.2-2.9] and smoking (1.5 [1.0-2.3] predicted CV mortality. The GYS1 XbaI T-allele predicted CV mortality particularly in physically active males (HR 1.7 [1.3-2.0]. Association of GYS1 with CV mortality was independent of APOE (219TT/epsilon4, which by its own exerted an effect on CV mortality risk in females (2.9 [1.9-4.4]. Other independent predictors of CV mortality in females were fasting plasma glucose (1.2 [1.1-1.2], high body mass index (BMI (1.0 [1.0-1.1], hypertension (1.9 [1.2-3.1], earlier CV events (1.9 [1.3-2.8] and physical inactivity (1.9 [1.2-2.8]. CONCLUSIONS/SIGNIFICANCE: Polymorphisms in GYS1 and APOE predict CV mortality in T2D families in a gender-specific fashion and independently of each other. Physical exercise seems to unmask the effect associated with the GYS1 polymorphism, rendering carriers of the variant allele less susceptible to the protective effect of exercise on the risk of CV death

  6. Biomarkers improve mortality prediction by prognostic scales in community-acquired pneumonia.

    Science.gov (United States)

    Menéndez, R; Martínez, R; Reyes, S; Mensa, J; Filella, X; Marcos, M A; Martínez, A; Esquinas, C; Ramirez, P; Torres, A

    2009-07-01

    Prognostic scales provide a useful tool to predict mortality in community-acquired pneumonia (CAP). However, the inflammatory response of the host, crucial in resolution and outcome, is not included in the prognostic scales. The aim of this study was to investigate whether information about the initial inflammatory cytokine profile and markers increases the accuracy of prognostic scales to predict 30-day mortality. To this aim, a prospective cohort study in two tertiary care hospitals was designed. Procalcitonin (PCT), C-reactive protein (CRP) and the systemic cytokines tumour necrosis factor alpha (TNFalpha) and interleukins IL6, IL8 and IL10 were measured at admission. Initial severity was assessed by PSI (Pneumonia Severity Index), CURB65 (Confusion, Urea nitrogen, Respiratory rate, Blood pressure, > or = 65 years of age) and CRB65 (Confusion, Respiratory rate, Blood pressure, > or = 65 years of age) scales. A total of 453 hospitalised CAP patients were included. The 36 patients who died (7.8%) had significantly increased levels of IL6, IL8, PCT and CRP. In regression logistic analyses, high levels of CRP and IL6 showed an independent predictive value for predicting 30-day mortality, after adjustment for prognostic scales. Adding CRP to PSI significantly increased the area under the receiver operating characteristic curve (AUC) from 0.80 to 0.85, that of CURB65 from 0.82 to 0.85 and that of CRB65 from 0.79 to 0.85. Adding IL6 or PCT values to CRP did not significantly increase the AUC of any scale. When using two scales (PSI and CURB65/CRB65) and CRP simultaneously the AUC was 0.88. Adding CRP levels to PSI, CURB65 and CRB65 scales improves the 30-day mortality prediction. The highest predictive value is reached with a combination of two scales and CRP. Further validation of that improvement is needed.

  7. Prognostic factors for mortality due to pneumonia among adults from different age groups in Singapore and mortality predictions based on PSI and CURB-65.

    Science.gov (United States)

    Zhang, Zoe Xz; Yong, Yang; Tan, Wan C; Shen, Liang; Ng, Han Seong; Fong, Kok Yong

    2017-08-14

    Pneumonia is associated with considerable mortality. However, the information on age-specific prognostic factors for death from pneumonia is limited. Patients hospitalised with a diagnosis of pneumonia through the emergency department were stratified into three age groups: 18-64 years; 65-84 years; and ≥ 85 years. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were conducted to evaluate prognostic factors for mortality and the performance of pneumonia severity scoring tools for mortality prediction. There were 1,902 patients (18-64 years: 614 [32.3%]; 65-84 years: 944 [49.6%]; ≥ 85 years: 344 [18.1%]) enrolled. Mortality rates increased with age (18-64 years: 7.3%; 65-84 years: 16.1%; ≥ 85 years: 29.7%; p aged 18-64 years. Male gender, malignancy, congestive heart failure and eight other parameters reflecting acute disease severity were associated with mortality among patients aged 65-84 years. For patients aged ≥ 85 years, altered mental status, tachycardia, blood urea nitrogen, hypoxaemia, arterial pH and pleural effusion were significantly predictive of mortality. Pneumonia Severity Index (PSI) was more sensitive than CURB-65 (Confusion, Uraemia, Respiratory rate ≥ 30 per minute, low Blood pressure, age 65 years or older) for mortality prediction across all age groups. The predictive effect of prognostic factors for mortality varied among patients with pneumonia from the different age groups. PSI performed significantly better than CURB-65 for mortality prediction, but its discriminative power decreased with advancing age.

  8. Performance of Surgical Risk Scores to Predict Mortality after Transcatheter Aortic Valve Implantation

    Directory of Open Access Journals (Sweden)

    Leonardo Sinnott Silva

    2015-01-01

    Full Text Available Abstract Background: Predicting mortality in patients undergoing transcatheter aortic valve implantation (TAVI remains a challenge. Objectives: To evaluate the performance of 5 risk scores for cardiac surgery in predicting the 30-day mortality among patients of the Brazilian Registry of TAVI. Methods: The Brazilian Multicenter Registry prospectively enrolled 418 patients undergoing TAVI in 18 centers between 2008 and 2013. The 30-day mortality risk was calculated using the following surgical scores: the logistic EuroSCORE I (ESI, EuroSCORE II (ESII, Society of Thoracic Surgeons (STS score, Ambler score (AS and Guaragna score (GS. The performance of the risk scores was evaluated in terms of their calibration (Hosmer–Lemeshow test and discrimination [area under the receiver–operating characteristic curve (AUC]. Results: The mean age was 81.5 ± 7.7 years. The CoreValve (Medtronic was used in 86.1% of the cohort, and the transfemoral approach was used in 96.2%. The observed 30-day mortality was 9.1%. The 30-day mortality predicted by the scores was as follows: ESI, 20.2 ± 13.8%; ESII, 6.5 ± 13.8%; STS score, 14.7 ± 4.4%; AS, 7.0 ± 3.8%; GS, 17.3 ± 10.8%. Using AUC, none of the tested scores could accurately predict the 30-day mortality. AUC for the scores was as follows: 0.58 [95% confidence interval (CI: 0.49 to 0.68, p = 0.09] for ESI; 0.54 (95% CI: 0.44 to 0.64, p = 0.42 for ESII; 0.57 (95% CI: 0.47 to 0.67, p = 0.16 for AS; 0.48 (95% IC: 0.38 to 0.57, p = 0.68 for STS score; and 0.52 (95% CI: 0.42 to 0.62, p = 0.64 for GS. The Hosmer–Lemeshow test indicated acceptable calibration for all scores (p > 0.05. Conclusions: In this real world Brazilian registry, the surgical risk scores were inaccurate in predicting mortality after TAVI. Risk models specifically developed for TAVI are required.

  9. A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

    Science.gov (United States)

    Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen. Fitzgerald

    2012-01-01

    Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

  10. Prediction of mortality after radical cystectomy for bladder cancer by machine learning techniques.

    Science.gov (United States)

    Wang, Guanjin; Lam, Kin-Man; Deng, Zhaohong; Choi, Kup-Sze

    2015-08-01

    Bladder cancer is a common cancer in genitourinary malignancy. For muscle invasive bladder cancer, surgical removal of the bladder, i.e. radical cystectomy, is in general the definitive treatment which, unfortunately, carries significant morbidities and mortalities. Accurate prediction of the mortality of radical cystectomy is therefore needed. Statistical methods have conventionally been used for this purpose, despite the complex interactions of high-dimensional medical data. Machine learning has emerged as a promising technique for handling high-dimensional data, with increasing application in clinical decision support, e.g. cancer prediction and prognosis. Its ability to reveal the hidden nonlinear interactions and interpretable rules between dependent and independent variables is favorable for constructing models of effective generalization performance. In this paper, seven machine learning methods are utilized to predict the 5-year mortality of radical cystectomy, including back-propagation neural network (BPN), radial basis function (RBFN), extreme learning machine (ELM), regularized ELM (RELM), support vector machine (SVM), naive Bayes (NB) classifier and k-nearest neighbour (KNN), on a clinicopathological dataset of 117 patients of the urology unit of a hospital in Hong Kong. The experimental results indicate that RELM achieved the highest average prediction accuracy of 0.8 at a fast learning speed. The research findings demonstrate the potential of applying machine learning techniques to support clinical decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Risk Prediction of One-Year Mortality in Patients with Cardiac Arrhythmias Using Random Survival Forest

    Directory of Open Access Journals (Sweden)

    Fen Miao

    2015-01-01

    Full Text Available Existing models for predicting mortality based on traditional Cox proportional hazard approach (CPH often have low prediction accuracy. This paper aims to develop a clinical risk model with good accuracy for predicting 1-year mortality in cardiac arrhythmias patients using random survival forest (RSF, a robust approach for survival analysis. 10,488 cardiac arrhythmias patients available in the public MIMIC II clinical database were investigated, with 3,452 deaths occurring within 1-year followups. Forty risk factors including demographics and clinical and laboratory information and antiarrhythmic agents were analyzed as potential predictors of all-cause mortality. RSF was adopted to build a comprehensive survival model and a simplified risk model composed of 14 top risk factors. The built comprehensive model achieved a prediction accuracy of 0.81 measured by c-statistic with 10-fold cross validation. The simplified risk model also achieved a good accuracy of 0.799. Both results outperformed traditional CPH (which achieved a c-statistic of 0.733 for the comprehensive model and 0.718 for the simplified model. Moreover, various factors are observed to have nonlinear impact on cardiac arrhythmias prognosis. As a result, RSF based model which took nonlinearity into account significantly outperformed traditional Cox proportional hazard model and has great potential to be a more effective approach for survival analysis.

  12. Predictive modelling of fatigue failure in concentrated lubricated contacts.

    Science.gov (United States)

    Evans, H P; Snidle, R W; Sharif, K J; Bryant, M J

    2012-01-01

    Reducing frictional losses in response to the energy agenda will require use of less viscous lubricants causing hydrodynamically-lubricated bearings to operate with thinner films leading to "mixed lubrication" conditions in which a degree of direct interaction occurs between surfaces protected only by boundary tribofilms. The paper considers the consequences of thinner films and mixed lubrication for concentrated contacts such as those occurring between the teeth of power transmission gears and in rolling element bearings. Surface fatigue in gears remains a serious problem in demanding applications, and its solution will become more pressing with the tendency towards thinner oils. The particular form of failure examined here is micropitting, which is identified as a fatigue phenomenon occurring at the scale of the surface roughness asperities. It has emerged recently as a systemic difficulty in the operation of large scale wind turbines where it occurs in both power transmission gears and their support bearings. Predictive physical modelling of these contacts requires a transient mixed lubrication analysis for conditions in which the predicted lubricant film thickness is of the same order or significantly less than the height of surface roughness features. Numerical solvers have therefore been developed which are able to deal with situations in which transient solid contacts occur between surface asperity features under realistic engineering conditions. Results of the analysis, which reveal the detailed time-varying behaviour of pressure and film clearance, have been used to predict fatigue and damage accumulation at the scale of surface asperity features with the aim of improving understanding of the micropitting phenomenon. The possible consequences on fatigue of residual stress fields resulting from plastic deformation of surface asperities is also considered.

  13. Interleukin-6 and procalcitonin as biomarkers in mortality prediction of hospitalized patients with community acquired pneumonia

    Directory of Open Access Journals (Sweden)

    Ilija Andrijevic

    2014-01-01

    Full Text Available Introduction: Community acquired pneumonia (CAP may present as life-threatening infection with uncertain progression and outcome of treatment. Primary aim of the trial was determination of the cut-off value of serum interleukin-6 (IL-6 and procalcitonin (PCT above which, 30-day mortality in hospitalized patients with CAP, could be predicted with high sensitivity and specificity. We investigated correlation between serum levels of IL-6 and PCT at admission and available scoring systems of CAP (pneumonia severity index-PSI, modified early warning score-MEWS and (Confusion, Urea nitrogen, respiratory rate, Blood pressure, ≥65 years of age-CURB65. Methods: This was prospective, non-randomized trial which included 101 patients with diagnosed CAP. PSI, MEWS and CURB65 were assessed on first day of hospitalization. IL-6 and PCT were also sampled on the first day of hospitalization. Results: Based on ROC curve analysis (AUC ± SE = 0.934 ± 0.035; 95%CI(0.864-1.0; P = 0.000 hospitalized CAP patients with elevated IL-6 level have 93.4% higher risk level for lethal outcome. Cut-off value of 20.2 pg/ml IL-6 shows sensitivity of 84% and specificity of 87% in mortality prediction. ROC curve analysis confirmed significant role of procalcitonin as a mortality predictor in CAP patients (AUC ± SE = 0.667 ± 0.062; 95%CI(0.546-0.789; P = 0.012. Patients with elevated PCT level have 66.7% higher risk level for lethal outcome. As a predictor of mortality at the cut-off value of 2.56 ng/ml PCT shows sensitivity of 76% and specificity of 61.8%. Conclusions: Both IL-6 and PCI are significant for prediction of 30-day mortality in hospitalized patients with CAP. Serum levels of IL6 correlate with major CAP scoring systems.

  14. Symptom clusters predict mortality among dialysis patients in Norway: a prospective observational cohort study.

    Science.gov (United States)

    Amro, Amin; Waldum, Bård; von der Lippe, Nanna; Brekke, Fredrik Barth; Dammen, Toril; Miaskowski, Christine; Os, Ingrid

    2015-01-01

    Patients with end-stage renal disease on dialysis have reduced survival rates compared with the general population. Symptoms are frequent in dialysis patients, and a symptom cluster is defined as two or more related co-occurring symptoms. The aim of this study was to explore the associations between symptom clusters and mortality in dialysis patients. In a prospective observational cohort study of dialysis patients (n = 301), Kidney Disease and Quality of Life Short Form and Beck Depression Inventory questionnaires were administered. To generate symptom clusters, principal component analysis with varimax rotation was used on 11 kidney-specific self-reported physical symptoms. A Beck Depression Inventory score of 16 or greater was defined as clinically significant depressive symptoms. Physical and mental component summary scores were generated from Short Form-36. Multivariate Cox regression analysis was used for the survival analysis, Kaplan-Meier curves and log-rank statistics were applied to compare survival rates between the groups. Three different symptom clusters were identified; one included loading of several uremic symptoms. In multivariate analyses and after adjustment for health-related quality of life and depressive symptoms, the worst perceived quartile of the "uremic" symptom cluster independently predicted all-cause mortality (hazard ratio 2.47, 95% CI 1.44-4.22, P = 0.001) compared with the other quartiles during a follow-up period that ranged from four to 52 months. The two other symptom clusters ("neuromuscular" and "skin") or the individual symptoms did not predict mortality. Clustering of uremic symptoms predicted mortality. Assessing co-occurring symptoms rather than single symptoms may help to identify dialysis patients at high risk for mortality. Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  15. Dimethylglycine accumulates in uremia and predicts elevated plasma homocysteine concentrations.

    Science.gov (United States)

    McGregor, D O; Dellow, W J; Lever, M; George, P M; Robson, R A; Chambers, S T

    2001-06-01

    Hyperhomocysteinemia is a risk factor for atherosclerosis that is common in chronic renal failure (CRF), but its cause is unknown. Homocysteine metabolism is linked to betaine-homocysteine methyl transferase (BHMT), a zinc metalloenzyme that converts glycine betaine (GB) to N,N dimethylglycine (DMG). DMG is a known feedback inhibitor of BHMT. We postulated that DMG might accumulate in CRF and contribute to hyperhomocysteinemia by inhibiting BHMT activity. Plasma and urine concentrations of GB and DMG were measured in 33 dialysis patients (15 continuous ambulatory peritoneal dialysis and 18 hemodialysis), 33 patients with CRF, and 33 age-matched controls. Concentrations of fasting plasma total homocysteine (tHcy), red cell and serum folate, vitamins B(6) and B(12), serum zinc, and routine biochemistry were also measured. Groups were compared, and determinants of plasma tHcy were identified by correlations and stepwise linear regression. Plasma DMG increased as renal function declined and was twofold to threefold elevated in dialysis patients. Plasma GB did not differ between groups. The fractional excretion of GB (FE(GB)) was increased tenfold, and FED(MG) was doubled in CRF patients compared with controls. Plasma tHcy correlated positively with plasma DMG, the plasma DMG:GB ratio, plasma creatinine, and FE(GB) and negatively with serum folate, zinc, and plasma GB. In the multiple regression model, only plasma creatinine, plasma DMG, or the DMG:GB ratio was independent predictors of tHcy. DMG accumulates in CRF and independently predicts plasma tHcy concentrations. These findings suggest that reduced BHMT activity is important in the pathogenesis of hyperhomocysteinemia in CRF.

  16. C-reactive protein level predicts mortality in COPD: a systematic review and meta-analysis

    Directory of Open Access Journals (Sweden)

    Giovanni Leuzzi

    2017-02-01

    Full Text Available The prognostic role of baseline C-reactive protein (CRP in chronic obstructive pulmonary disease (COPD is controversial. In order to clarify this issue, we performed a systematic review and meta-analysis to assess the predictive effect of baseline CRP level in COPD patients. 15 eligible articles focusing on late mortality in COPD were included in our study. We performed a random-effects meta-analysis, and assessed heterogeneity and publication bias. We pooled hazard ratio (HR estimates and their 95% confidence intervals on mortality for the comparison between the study-specific highest category of CRP level versus the lowest category. In overall analysis, elevated baseline CRP levels were significantly associated with higher mortality (HR 1.53, 95% CI 1.32–1.77, I2=68.7%, p<0.001. Similar results were observed across subgroups. However, higher mortality risk was reported in studies using a cut-off value of 3 mg·L−1 (HR 1.61, 95% CI 1.12–2.30 and in those enrolling an Asiatic population (HR 3.51, 95% CI 1.69–7.31. Our analysis indicates that baseline high CRP level is significantly associated with higher late mortality in patients with COPD. Further prospective controlled studies are needed to confirm these data.

  17. Value of geriatric frailty and nutritional status assessment in predicting postoperative mortality in gastric cancer surgery.

    Science.gov (United States)

    Tegels, Juul J W; de Maat, M F G; Hulsewé, K W E; Hoofwijk, A G M; Stoot, J H M B

    2014-03-01

    This study seeks to evaluate assessment of geriatric frailty and nutritional status in predicting postoperative mortality in gastric cancer surgery. Preoperatively, patients operated for gastric adenocarcinoma underwent assessment of Groningen Frailty Indicator (GFI) and Short Nutritional Assessment Questionnaire (SNAQ). We studied retrospectively whether these scores were associated with in-hospital mortality. From 2005 to September 2012 180 patients underwent surgery with an overall mortality of 8.3%. Patients with a GFI ≥ 3 (n = 30, 24%) had a mortality rate of 23.3% versus 5.2% in the lower GFI group (OR 4.0, 95%CI 1.1-14.1, P = 0.03). For patients who underwent surgery with curative intent (n = 125), this was 27.3% for patients with GFI ≥ 3 (n = 22, 18%) versus 5.7% with GFI gastric cancer surgical mortality and geriatric frailty as well as nutritional status using a simple questionnaire. This may have implications in preoperative decision making in selecting patients who optimally benefit from surgery.

  18. Predictive factors of mortality within 30 days in patients with nonvariceal upper gastrointestinal bleeding.

    Science.gov (United States)

    Lee, Yoo Jin; Min, Bo Ram; Kim, Eun Soo; Park, Kyung Sik; Cho, Kwang Bum; Jang, Byoung Kuk; Chung, Woo Jin; Hwang, Jae Seok; Jeon, Seong Woo

    2016-01-01

    Nonvariceal upper gastrointestinal bleeding (NVUGIB) is a common medical emergency that can be life threatening. This study evaluated predictive factors of 30-day mortality in patients with this condition. A prospective observational study was conducted at a single hospital between April 2010 and November 2012, and 336 patients with symptoms and signs of gastrointestinal bleeding were consecutively enrolled. Clinical characteristics and endoscopic findings were reviewed to identify potential factors associated with 30-day mortality. Overall, 184 patients were included in the study (men, 79.3%; mean age, 59.81 years), and 16 patients died within 30 days (8.7%). Multivariate analyses revealed that comorbidity of diabetes mellitus (DM) or metastatic malignancy, age ≥ 65 years, and hypotension (systolic pressure < 90 mmHg) during hospitalization were significant predictive factors of 30-day mortality. Comorbidity of DM or metastatic malignancy, age ≥ 65 years, and hemodynamic instability during hospitalization were predictors of 30-day mortality in patients with NVUGIB. These results will help guide the management of patients with this condition.

  19. Concentration-mortality responses of Myzus persicae and natural enemies to selected insecticides.

    Science.gov (United States)

    Bacci, Leandro; Rosado, Jander F; Picanço, Marcelo C; Pereira, Eliseu J G; Silva, Gerson A; Martins, Júlio C

    2012-01-01

    The toxicity of six insecticides was determined for the peach-potato aphid, Myzus persicae (Hemiptera: Aphididae), and some of its natural enemies - the predatory beetles Cycloneda sanguinea (Coccinellidae) and Acanthinus sp. (Anthicidae), and the wasp parasitoid Diaeretiella rapae (Aphidiidae). Natural enemies from these groups are important natural biological control agents in a number of agroecosystems, and insecticides potentially safe to these non-target organisms should be identified using standardized tests. Thus, concentration-mortality bioassays were carried out with both the aphid and its natural enemies to assess the toxicity and selectivity of acephate, deltamethrin, dimethoate, methamidophos, methyl parathion, and pirimicarb. The latter insecticide was highly selective to all natural enemies tested, and its LC(90) for M. persicae was 14-fold lower than the field rate recommended for control of the aphid in brassica crops. Methyl parathion also showed selectivity to C. sanguinea and Acanthinus sp., but not to D. rapae. Acephate was the least potent insecticide against M. persicae and was equally or more toxic to the natural enemies relative to the aphid. Pirimicarb and methyl parathion were efficient against M. persicae and selective in favor of two of the natural enemies tested. Acanthinus sp. and C. sanguinea were more tolerant to the insecticides than was the parasitoid D. rapae. This study shows that there are selective insecticides that may be compatible with conservation of natural enemies in brassica crops, which is important practical information to improve integrated pest management systems in these crops.

  20. Preadmission quality of life can predict mortality in intensive care unit—A prospective cohort study

    DEFF Research Database (Denmark)

    Bukan, Ramin I; Møller, Ann M; Henning, Mattias A S

    2014-01-01

    quality of life, assessed by SF-36 and SF-12, is as good at predicting ICU, 30-, and 90-day mortality as APACHE II in patients admitted to the ICU for longer than 24 hours. This indicates that estimated preadmission quality of life, potentially available in the pre-ICU setting, could aid decision making...... regarding ICU admission and deserves more attention by those caring for critically ill patients....

  1. Does inhalation injury predict mortality in burns patients or require redefinition?

    Directory of Open Access Journals (Sweden)

    Youngmin Kim

    Full Text Available Inhalation injury is known to be an important factor in predicting mortality in burns patients. However, the diagnosis is complicated by the heterogeneous presentation and inability to determine the severity of inhalation injury. The purpose of this study was to identify clinical features of inhalation injury that affect mortality and the values that could predict the outcome more precisely in burns patients with inhalation injury. This retrospective observational study included 676 burns patients who were over 18 years of age and hospitalized in the Burns Intensive Care Unit between January 2012 and December 2015. We analyzed variables that are already known to be prognostic factors (age, percentage of total body surface area (%TBSA burned, and inhalation injury and factors associated with inhalation injury (carboxyhemoglobin and PaO2/FiO2 [PF] ratio by univariate and multivariate logistic regression. Age group (odds ratio [OR] 1.069, p<0.001, %TBSA burned (OR 1.100, p<0.001, and mechanical ventilation (OR 3.774, p<0.001 were identified to be significant predictive factors. The findings for presence of inhalation injury, PF ratio, and carboxyhemoglobin were not statistically significant in multivariate logistic regression. Being in the upper inhalation group, the lower inhalation group, and having a PF ratio <100 were identified to be significant predictors only in univariate logistic regression analysis (OR 4.438, p<0.001; OR 2.379, p<0.001; and OR 2.765, p<0.001, respectively. History and physical findings are not appropriate for diagnosis of inhalation injury and do not predict mortality. Mechanical ventilation should be recognized as a risk factor for mortality in burns patients with inhalation injury.

  2. Temperature multiscale entropy analysis: a promising marker for early prediction of mortality in septic patients

    International Nuclear Information System (INIS)

    Papaioannou, V E; Pneumatikos, I A; Chouvarda, I G; Maglaveras, N K; Baltopoulos, G I

    2013-01-01

    A few studies estimating temperature complexity have found decreased Shannon entropy, during severe stress. In this study, we measured both Shannon and Tsallis entropy of temperature signals in a cohort of critically ill patients and compared these measures with the sequential organ failure assessment (SOFA) score, in terms of intensive care unit (ICU) mortality. Skin temperature was recorded in 21 mechanically ventilated patients, who developed sepsis and septic shock during the first 24 h of an ICU-acquired infection. Shannon and Tsallis entropies were calculated in wavelet-based decompositions of the temperature signal. Statistically significant differences of entropy features were tested between survivors and non-survivors and classification models were built, for predicting final outcome. Significantly reduced Tsallis and Shannon entropies were found in non-survivors (seven patients, 33%) as compared to survivors. Wavelet measurements of both entropy metrics were found to predict ICU mortality better than SOFA, according to a combination of area under the curve, sensitivity and specificity values. Both entropies exhibited similar prognostic accuracy. Combination of SOFA and entropy presented improved the outcome of univariate models. We suggest that reduced wavelet Shannon and Tsallis entropies of temperature signals may complement SOFA in mortality prediction, during the first 24 h of an ICU-acquired infection. (paper)

  3. Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

    Science.gov (United States)

    de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F E

    2012-01-01

    Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

  4. Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

    Directory of Open Access Journals (Sweden)

    Manuela de Lucas

    Full Text Available BACKGROUND: Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. METHODOLOGY/PRINCIPAL FINDINGS: As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. CONCLUSIONS: Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed. We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

  5. Fetal MRI for prediction of neonatal mortality following preterm premature rupture of the fetal membranes

    International Nuclear Information System (INIS)

    Messerschmidt, Agnes; Sauer, Alexandra; Pollak, Arnold; Pataraia, Anna; Kasprian, Gregor; Weber, Michael; Prayer, Daniela; Helmer, Hanns; Brugger, Peter C.

    2011-01-01

    Lung MRI volumetrics may be valuable for fetal assessment following early preterm premature rupture of the foetal membranes (pPROM). To evaluate the predictive value of MRI lung volumetrics after pPROM. Retrospective cohort study of 40 fetuses after pPROM in a large, tertiary, perinatal referral center. Fetuses underwent MRI lung volumetrics. Estimated lung volume was expressed as percentage of expected lung volume (our own normal references). Primary outcome was neonatal mortality due to respiratory distress before discharge from hospital. Gestational age range was 16-27 weeks. Estimated-to-expected lung volume was 73% in non-survivors and 102% in survivors (P < 0.05). There were no survivors with a lung volume less than 60% of expected. By logistic regression, mortality could be predicted with a sensitivity of 80%, specificity of 86% and accuracy of 85%. Fetal MR lung volumetrics may be useful for predicting mortality due to respiratory distress in children with early gestational pPROM. (orig.)

  6. Fetal MRI for prediction of neonatal mortality following preterm premature rupture of the fetal membranes

    Energy Technology Data Exchange (ETDEWEB)

    Messerschmidt, Agnes; Sauer, Alexandra; Pollak, Arnold [Medical University of Vienna, Department of Pediatrics and Adolescent Medicine, Vienna (Austria); Pataraia, Anna; Kasprian, Gregor; Weber, Michael; Prayer, Daniela [Medical University of Vienna, Department of Radiology, Vienna (Austria); Helmer, Hanns [Medical University of Vienna, Department of Obstetrics and Maternal-Fetal Medicine, Vienna (Austria); Brugger, Peter C. [Medical University of Vienna, Center of Anatomy and Cell Biology, Vienna (Austria)

    2011-11-15

    Lung MRI volumetrics may be valuable for fetal assessment following early preterm premature rupture of the foetal membranes (pPROM). To evaluate the predictive value of MRI lung volumetrics after pPROM. Retrospective cohort study of 40 fetuses after pPROM in a large, tertiary, perinatal referral center. Fetuses underwent MRI lung volumetrics. Estimated lung volume was expressed as percentage of expected lung volume (our own normal references). Primary outcome was neonatal mortality due to respiratory distress before discharge from hospital. Gestational age range was 16-27 weeks. Estimated-to-expected lung volume was 73% in non-survivors and 102% in survivors (P < 0.05). There were no survivors with a lung volume less than 60% of expected. By logistic regression, mortality could be predicted with a sensitivity of 80%, specificity of 86% and accuracy of 85%. Fetal MR lung volumetrics may be useful for predicting mortality due to respiratory distress in children with early gestational pPROM. (orig.)

  7. Discrimination ability of comorbidity, frailty, and subjective health to predict mortality in community-dwelling older people

    DEFF Research Database (Denmark)

    Kusumastuti, Sasmita; Gerds, Thomas Alexander; Lund, Rikke

    2017-01-01

    OBJECTIVE: To investigate the added value of comorbidity, frailty, and subjective health to mortality predictions in community-dwelling older people and whether it changes with increasing age. PARTICIPANTS: 36,751 community-dwelling subjects aged 50-100 from the longitudinal Survey of Health......, Ageing, and Retirement in Europe. METHODS: Mortality risk associated with Comorbidity Index, Frailty Index, Frailty Phenotype, and subjective health was analysed using Cox regression. The extent to which health indicators modified individual mortality risk predictions was examined and the added ability......, and household income. CONCLUSION: Calendar age encompasses most of the discrimination ability to predict mortality. The added value of comorbidity, frailty, and subjective health to mortality predictions decreases with increasing age....

  8. Depression increasingly predicts mortality in the course of congestive heart failure.

    Science.gov (United States)

    Jünger, Jana; Schellberg, Dieter; Müller-Tasch, Thomas; Raupp, Georg; Zugck, Christian; Haunstetter, Armin; Zipfel, Stephan; Herzog, Wolfgang; Haass, Markus

    2005-03-02

    Congestive heart failure (CHF) is frequently associated with depression. However, the impact of depression on prognosis has not yet been sufficiently established. To prospectively investigate the influence of depression on mortality in patients with CHF. In 209 CHF patients depression was assessed by the Hospital Anxiety and Depression Scale (HADS-D). Compared to survivors (n=164), non-survivors (n=45) were characterized by a higher New York Heart Association (NYHA) functional class (2.8+/-0.7 vs. 2.5+/-0.6), and a lower left ventricular ejection fraction (LVEF) (18+/-8 vs. 23+/-10%) and peakVO(2) (13.1+/-4.5 vs. 15.4+/-5.2 ml/kg/min) at baseline. Furthermore, non-survivors had a higher depression score (7.5+/-4.0 vs. 6.1+/-4.3) (all P<0.05). After a mean follow-up of 24.8 months the depression score was identified as a significant indicator of mortality (P<0.01). In multivariate analysis the depression score predicted mortality independent from NYHA functional class, LVEF and peakVO(2). Combination of depression score, LVEF and peakVO(2) allowed for a better risk stratification than combination of LVEF and peakVO(2) alone. The risk ratio for mortality in patients with an elevated depression score (i.e. above the median) rose over time to 8.2 after 30 months (CI 2.62-25.84). The depression score predicts mortality independent of somatic parameters in CHF patients not treated for depression. Its prognostic power increases over time and should, thus, be accounted for in risk stratification and therapy.

  9. Predictive Value of Cumulative Blood Pressure for All-Cause Mortality and Cardiovascular Events

    Science.gov (United States)

    Wang, Yan Xiu; Song, Lu; Xing, Ai Jun; Gao, Ming; Zhao, Hai Yan; Li, Chun Hui; Zhao, Hua Ling; Chen, Shuo Hua; Lu, Cheng Zhi; Wu, Shou Ling

    2017-02-01

    The predictive value of cumulative blood pressure (BP) on all-cause mortality and cardiovascular and cerebrovascular events (CCE) has hardly been studied. In this prospective cohort study including 52,385 participants from the Kailuan Group who attended three medical examinations and without CCE, the impact of cumulative systolic BP (cumSBP) and cumulative diastolic BP (cumDBP) on all-cause mortality and CCEs was investigated. For the study population, the mean (standard deviation) age was 48.82 (11.77) years of which 40,141 (76.6%) were male. The follow-up for all-cause mortality and CCEs was 3.96 (0.48) and 2.98 (0.41) years, respectively. Multivariate Cox proportional hazards regression analysis showed that for every 10 mm Hg·year increase in cumSBP and 5 mm Hg·year increase in cumDBP, the hazard ratio for all-cause mortality were 1.013 (1.006, 1.021) and 1.012 (1.006, 1.018); for CCEs, 1.018 (1.010, 1.027) and 1.017 (1.010, 1.024); for stroke, 1.021 (1.011, 1.031) and 1.018 (1.010, 1.026); and for MI, 1.013 (0.996, 1.030) and 1.015 (1.000, 1.029). Using natural spline function analysis, cumSBP and cumDBP showed a J-curve relationship with CCEs; and a U-curve relationship with stroke (ischemic stroke and hemorrhagic stroke). Therefore, increases in cumSBP and cumDBP were predictive for all-cause mortality, CCEs, and stroke.

  10. Physical Stress Echocardiography: Prediction of Mortality and Cardiac Events in Patients with Exercise Test showing Ischemia

    Directory of Open Access Journals (Sweden)

    Ana Carla Pereira de Araujo

    2014-11-01

    Full Text Available Background: Studies have demonstrated the diagnostic accuracy and prognostic value of physical stress echocardiography in coronary artery disease. However, the prediction of mortality and major cardiac events in patients with exercise test positive for myocardial ischemia is limited. Objective: To evaluate the effectiveness of physical stress echocardiography in the prediction of mortality and major cardiac events in patients with exercise test positive for myocardial ischemia. Methods: This is a retrospective cohort in which 866 consecutive patients with exercise test positive for myocardial ischemia, and who underwent physical stress echocardiography were studied. Patients were divided into two groups: with physical stress echocardiography negative (G1 or positive (G2 for myocardial ischemia. The endpoints analyzed were all-cause mortality and major cardiac events, defined as cardiac death and non-fatal acute myocardial infarction. Results: G2 comprised 205 patients (23.7%. During the mean 85.6 ± 15.0-month follow-up, there were 26 deaths, of which six were cardiac deaths, and 25 non-fatal myocardial infarction cases. The independent predictors of mortality were: age, diabetes mellitus, and positive physical stress echocardiography (hazard ratio: 2.69; 95% confidence interval: 1.20 - 6.01; p = 0.016. The independent predictors of major cardiac events were: age, previous coronary artery disease, positive physical stress echocardiography (hazard ratio: 2.75; 95% confidence interval: 1.15 - 6.53; p = 0.022 and absence of a 10% increase in ejection fraction. All-cause mortality and the incidence of major cardiac events were significantly higher in G2 (p < 0. 001 and p = 0.001, respectively. Conclusion: Physical stress echocardiography provides additional prognostic information in patients with exercise test positive for myocardial ischemia.

  11. Predicting mortality among hospitalized children with respiratory illness in Western Kenya, 2009-2012.

    Directory of Open Access Journals (Sweden)

    Gideon O Emukule

    Full Text Available BACKGROUND: Pediatric respiratory disease is a major cause of morbidity and mortality in the developing world. We evaluated a modified respiratory index of severity in children (mRISC scoring system as a standard tool to identify children at greater risk of death from respiratory illness in Kenya. MATERIALS AND METHODS: We analyzed data from children <5 years old who were hospitalized with respiratory illness at Siaya District Hospital from 2009-2012. We used a multivariable logistic regression model to identify patient characteristics predictive for in-hospital mortality. Model discrimination was evaluated using the concordance statistic. Using bootstrap samples, we re-estimated the coefficients and the optimism of the model. The mRISC score for each child was developed by adding up the points assigned to each factor associated with mortality based on the coefficients in the multivariable model. RESULTS: We analyzed data from 3,581 children hospitalized with respiratory illness; including 218 (6% who died. Low weight-for-age [adjusted odds ratio (aOR = 2.1; 95% CI 1.3-3.2], very low weight-for-age (aOR = 3.8; 95% CI 2.7-5.4, caretaker-reported history of unconsciousness (aOR = 2.3; 95% CI 1.6-3.4, inability to drink or breastfeed (aOR = 1.8; 95% CI 1.2-2.8, chest wall in-drawing (aOR = 2.2; 95% CI 1.5-3.1, and being not fully conscious on physical exam (aOR = 8.0; 95% CI 5.1-12.6 were independently associated with mortality. The positive predictive value for mortality increased with increasing mRISC scores. CONCLUSIONS: A modified RISC scoring system based on a set of easily measurable clinical features at admission was able to identify children at greater risk of death from respiratory illness in Kenya.

  12. Mortality after Spontaneous Subarachnoid Hemorrhage: Causality and Validation of a Prediction Model.

    Science.gov (United States)

    Abulhasan, Yasser B; Alabdulraheem, Najayeb; Simoneau, Gabrielle; Angle, Mark R; Teitelbaum, Jeanne

    2018-04-01

    To evaluate primary causes of death after spontaneous subarachnoid hemorrhage (SAH) and externally validate the HAIR score, a prognostication tool, in a single academic institution. We reviewed all patients with SAH admitted to our neuro-intensive care unit between 2010 and 2016. Univariate and multivariate logistic regressions were performed to identify predictors of in-hospital mortality. The HAIR score predictors were Hunt and Hess grade at treatment decision, age, intraventricular hemorrhage, and rebleeding within 24 hours. Validation of the HAIR score was characterized with the receiver operating curve, the area under the curve, and a calibration plot. Among 434 patients with SAH, in-hospital mortality was 14.1%. Of the 61 mortalities, 54 (88.5%) had a neurologic cause of death or withdrawal of care and 7 (11.5%) had cardiac death. Median time from SAH to death was 6 days. The main causes of death were effect of the initial hemorrhage (26.2%), rebleeding (23%) and refractory cerebral edema (19.7%). Factors significantly associated with in-hospital mortality in the multivariate analysis were age, Hunt and Hess grade, and intracerebral hemorrhage. Maximum lumen size was also a significant risk factor after aneurysmal SAH. The HAIR score had a satisfactory discriminative ability, with an area under the curve of 0.89. The in-hospital mortality is lower than in previous reports, attesting to the continuing improvement of our institutional SAH care. The major causes are the same as in previous reports. Despite a different therapeutic protocol, the HAIR score showed good discrimination and could be a useful tool for predicting mortality. Copyright © 2018 Elsevier Inc. All rights reserved.

  13. Bicarbonate Concentration, Acid-Base Status, and Mortality in the Health, Aging, and Body Composition Study.

    Science.gov (United States)

    Raphael, Kalani L; Murphy, Rachel A; Shlipak, Michael G; Satterfield, Suzanne; Huston, Hunter K; Sebastian, Anthony; Sellmeyer, Deborah E; Patel, Kushang V; Newman, Anne B; Sarnak, Mark J; Ix, Joachim H; Fried, Linda F

    2016-02-05

    Low serum bicarbonate associates with mortality in CKD. This study investigated the associations of bicarbonate and acid-base status with mortality in healthy older individuals. We analyzed data from the Health, Aging, and Body Composition Study, a prospective study of well functioning black and white adults ages 70-79 years old from 1997. Participants with arterialized venous blood gas measurements (n=2287) were grouped into respiratory alkalosis, and 1.35 (95% CI, 1.08 to 1.69) for metabolic alkalosis categories. Respiratory acidosis did not associate with mortality. In generally healthy older individuals, low serum bicarbonate associated with higher mortality independent of systemic pH and potential confounders. This association seemed to be present regardless of whether the cause of low bicarbonate was metabolic acidosis or respiratory alkalosis. Metabolic alkalosis also associated with higher mortality. Copyright © 2016 by the American Society of Nephrology.

  14. Risk score for predicting long-term mortality after coronary artery bypass graft surgery.

    Science.gov (United States)

    Wu, Chuntao; Camacho, Fabian T; Wechsler, Andrew S; Lahey, Stephen; Culliford, Alfred T; Jordan, Desmond; Gold, Jeffrey P; Higgins, Robert S D; Smith, Craig R; Hannan, Edward L

    2012-05-22

    No simplified bedside risk scores have been created to predict long-term mortality after coronary artery bypass graft surgery. The New York State Cardiac Surgery Reporting System was used to identify 8597 patients who underwent isolated coronary artery bypass graft surgery in July through December 2000. The National Death Index was used to ascertain patients' vital statuses through December 31, 2007. A Cox proportional hazards model was fit to predict death after CABG surgery using preprocedural risk factors. Then, points were assigned to significant predictors of death on the basis of the values of their regression coefficients. For each possible point total, the predicted risks of death at years 1, 3, 5, and 7 were calculated. It was found that the 7-year mortality rate was 24.2 in the study population. Significant predictors of death included age, body mass index, ejection fraction, unstable hemodynamic state or shock, left main coronary artery disease, cerebrovascular disease, peripheral arterial disease, congestive heart failure, malignant ventricular arrhythmia, chronic obstructive pulmonary disease, diabetes mellitus, renal failure, and history of open heart surgery. The points assigned to these risk factors ranged from 1 to 7; possible point totals for each patient ranged from 0 to 28. The observed and predicted risks of death at years 1, 3, 5, and 7 across patient groups stratified by point totals were highly correlated. The simplified risk score accurately predicted the risk of mortality after coronary artery bypass graft surgery and can be used for informed consent and as an aid in determining treatment choice.

  15. A New Weighted Injury Severity Scoring System: Better Predictive Power for Pediatric Trauma Mortality.

    Science.gov (United States)

    Shi, Junxin; Shen, Jiabin; Caupp, Sarah; Wang, Angela; Nuss, Kathryn E; Kenney, Brian; Wheeler, Krista K; Lu, Bo; Xiang, Henry

    2018-05-02

    An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted injury severity scoring (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank (NTDB). The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients less than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 vs. 0.86 in ISS=1-74 and 0.77 vs. 0.64 in ISS=25-74 (ppredictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 versus 19.7 for ISS=1-74 and 10.9 versus 12.6 for ISS= 25-74). The wISS showed even better discrimination with the NEDS. By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children.Level of Evidence and study typeLevel IV Prognostic/Epidemiological.

  16. Cardiac Troponin Elevation Predicts Mortality in Patients Undergoing Orthotopic Liver Transplantation

    Directory of Open Access Journals (Sweden)

    David Snipelisky

    2013-01-01

    Full Text Available Introduction. While patients undergoing orthotopic liver transplantation (OLT have high cardiovascular event rates, preoperative risk stratification may not necessarily predict those susceptible patients. Troponin T (TnT may help predict patients at risk for cardiovascular complications. Methods. Consecutive patients undergoing OLT at Mayo Clinic in Florida between 1998 and 2010 who had TnT obtained within 10 days following surgery were included. Three groups were compared based on TnT level: (1 normal (TnT ≤0.01 ng/mL, (2 intermediate (TnT 0.02–0.11 ng/mL, and (3 elevated (TnT >0.11 ng/mL. Overall and cardiovascular mortality was assessed. Results. Of the 78 patients included, there was no difference in age, gender, severity of liver disease, and echocardiographic findings. Patients in the normal and intermediate TnT groups had a lower overall mortality rate (14.3% and 0%, resp. when compared with those with elevated TnT (50%; P=0.001. Patients in the elevated TnT group had a cardiovascular mortality rate of 37.5% compared with 1.4% in the other groups combined (P<0.01. The elevated TnT group had a much higher mortality rate when compared with those in the intermediate group (P<0.0001. Conclusion. TnT may accurately help risk stratify patients in the early postoperative setting to better predict cardiovascular complications.

  17. Should the IDC-9 Trauma Mortality Prediction Model become the new paradigm for benchmarking trauma outcomes?

    Science.gov (United States)

    Haider, Adil H; Villegas, Cassandra V; Saleem, Taimur; Efron, David T; Stevens, Kent A; Oyetunji, Tolulope A; Cornwell, Edward E; Bowman, Stephen; Haack, Sara; Baker, Susan P; Schneider, Eric B

    2012-06-01

    Optimum quantification of injury severity remains an imprecise science with a need for improvement. The accuracy of the criterion standard Injury Severity Score (ISS) worsens as a patient's injury severity increases, especially among patients with penetrating trauma. The objective of this study was to comprehensively compare the mortality prediction ability of three anatomic injury severity indices: the ISS, the New ISS (NISS), and the DRG International Classification of Diseases-9th Rev.-Trauma Mortality Prediction Model (TMPM-ICD-9), a recently developed contemporary injury assessment model. Retrospective analysis of patients in the National Trauma Data Bank from 2007 to 2008. The TMPM-ICD-9 values were computed and compared with the ISS and NISS for each patient using in-hospital mortality after trauma as the outcome measure. Discrimination and calibration were compared using the area under the receiver operator characteristic curve. Subgroup analysis was performed to compare each score across varying ranges of injury severity and across different types of injury. A total of 533,898 patients were identified with a crude mortality rate of 4.7%. The ISS and NISS performed equally in the groups with minor (ISS, 1-8) and moderate (ISS, 9-15) injuries, regardless of the injury type. However, in the populations with severe (ISS, 16-24) and very severe (ISS, ≥ 25) injuries for all injury types, the NISS predicted mortality better than the ISS did. The TMPM-ICD-9 outperformed both the NISS and ISS almost consistently. The NISS and TMPM-ICD-9 are both superior predictors of mortality as compared with the ISS. The immediate adoption of NISS for evaluating trauma outcomes using trauma registry data is recommended. The TMPM-ICD-9 may be an even better measure of human injury, and its use in administrative or nonregistry data is suggested. Further research on its attributes is recommended because it has the potential to become the basis for benchmarking trauma outcomes

  18. The predictive value of malnutrition - inflammation score on 1-year mortality in Turkish maintenance hemodialysis patients.

    Science.gov (United States)

    Kara, Ekrem; Sahutoglu, Tuncay; Ahbap, Elbis; Sakaci, Tamer; Koc, Yener; Basturk, Taner; Sevinc, Mustafa; Akgol, Cuneyt; Unsal, Abdulkadir

    2016-08-01

    The aim of this study was to evaluate the predictive value of malnutrition-inflammation score (MIS) on short-term mortality and to identify the best cut-off point in the Turkish maintenance hemodialysis (MHD) population. A total of 100 patients on MHD were included in this prospective single-center study. Demographic, anthropometric, and biochemical data were obtained from all patients. The study population was followed up as a 12-month prospective cohort to evaluate mortality as the primary outcome. Median (IQR) age and HD vintage of 100 patients (M/F: 52/48) were 53 (39.5 - 67) years and 53.5 (11 - 104.7) months, respectively. Deceased patients (n = 7) had significantly older age (years) (50 (38.5 - 63.5) vs. 70 (62 - 82), respectively, p = 0.001), lower spKt/V (1.60 (1.40 - 1.79) vs. 1.35 (0.90 - 1.50), respectively, p = 0.002), lower triceps skinfold thickness (14 (10 - 19) vs. 9 (7 - 11), respectively, p = 0.021) and higher MIS (5 (4 - 7) vs. 10 (7 - 11), respectively, p = 0.013). In the ROC analysis, we found that the optimal cut-off value of MIS for predicting death was 6.5 with 85.7% sensitivity and 62.4% specificity (positive and negative predictive values were 0.6951 and 0.8136, respectively). Advanced age, low spKt/V, and high MIS were found to be predictors of mortality in multivariate logistic regression analysis. The 1-year mortality rate was significantly higher in MIS > 6.5 group compared to the MIS ≤ 6.5 group (14,3% (6/41) vs. 1.6% (1/59), respectively). Compared to MIS ≤ 6.5 group, 1 year survival time of the patients with MIS > 6.5 was found to be significantly lower (47.8 ± 0.16 vs. 43.6 ± 1.63 weeks, respectively, p (log-rank) = 0.012). MIS is a robust and independent predictor of short-term mortality in MHD patients. Patients with MIS > 6.5 had a significant risk, and additional risk factors associated with short-term mortality were advanced age and low spKt/V.

  19. Regional variation in the predictive validity of self-rated health for mortality

    Directory of Open Access Journals (Sweden)

    Edward R. Berchick

    2017-12-01

    Full Text Available Self-rated health (SRH is a commonly used measure for assessing general health in surveys in the United States. However, individuals from different parts of the United States may vary in how they assess their health. Geographic differences in health care access and in the prevalence of illnesses may make it difficult to discern true regional differences in health when using SRH as a health measure. In this article, we use data from the 1986 and 1989–2006 National Health Interview Survey Linked Mortality Files and estimate Cox regression models to examine whether the relationship between SRH and five-year all-cause mortality differs by Census region. Contrary to hypotheses, there is no evidence of regional variation in the predictive validity of SRH for mortality. At all levels of SRH, and for both non-Hispanic white and non-Hispanic black respondents, SRH is equally and strongly associated with five-year mortality across regions. Our results suggest that differences in SRH across regions are not solely due to differences in how respondents assess their health across regions, but reflect true differences in health. Future research can, therefore, employ this common measure to investigate the geographic patterning of health in the United States.

  20. Reliability of Modern Scores to Predict Long-Term Mortality After Isolated Aortic Valve Operations.

    Science.gov (United States)

    Barili, Fabio; Pacini, Davide; D'Ovidio, Mariangela; Ventura, Martina; Alamanni, Francesco; Di Bartolomeo, Roberto; Grossi, Claudio; Davoli, Marina; Fusco, Danilo; Perucci, Carlo; Parolari, Alessandro

    2016-02-01

    Contemporary scores for estimating perioperative death have been proposed to also predict also long-term death. The aim of the study was to evaluate the performance of the updated European System for Cardiac Operative Risk Evaluation II, The Society of Thoracic Surgeons Predicted Risk of Mortality score, and the Age, Creatinine, Left Ventricular Ejection Fraction score for predicting long-term mortality in a contemporary cohort of isolated aortic valve replacement (AVR). We also sought to develop for each score a simple algorithm based on predicted perioperative risk to predict long-term survival. Complete data on 1,444 patients who underwent isolated AVR in a 7-year period were retrieved from three prospective institutional databases and linked with the Italian Tax Register Information System. Data were evaluated with performance analyses and time-to-event semiparametric regression. Survival was 83.0% ± 1.1% at 5 years and 67.8 ± 1.9% at 8 years. Discrimination and calibration of all three scores both worsened for prediction of death at 1 year and 5 years. Nonetheless, a significant relationship was found between long-term survival and quartiles of scores (p System for Cardiac Operative Risk Evaluation II, 1.34 (95% CI, 1.28 to 1.40) for the Society of Thoracic Surgeons score, and 1.08 (95% CI, 1.06 to 1.10) for the Age, Creatinine, Left Ventricular Ejection Fraction score. The predicted risk generated by European System for Cardiac Operative Risk Evaluation II, The Society of Thoracic Surgeons score, and Age, Creatinine, Left Ventricular Ejection Fraction scores cannot also be considered a direct estimate of the long-term risk for death. Nonetheless, the three scores can be used to derive an estimate of long-term risk of death in patients who undergo isolated AVR with the use of a simple algorithm. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  1. Predicted vitamin D status and colon cancer recurrence and mortality in CALGB 89803 (Alliance).

    Science.gov (United States)

    Fuchs, M A; Yuan, C; Sato, K; Niedzwiecki, D; Ye, X; Saltz, L B; Mayer, R J; Mowat, R B; Whittom, R; Hantel, A; Benson, A; Atienza, D; Messino, M; Kindler, H; Venook, A; Innocenti, F; Warren, R S; Bertagnolli, M M; Ogino, S; Giovannucci, E L; Horvath, E; Meyerhardt, J A; Ng, K

    2017-06-01

    Observational studies suggest that higher levels of 25-hydroxyvitamin D3 (25(OH)D) are associated with a reduced risk of colorectal cancer and improved survival of colorectal cancer patients. However, the influence of vitamin D status on cancer recurrence and survival of patients with stage III colon cancer is unknown. We prospectively examined the influence of post-diagnosis predicted plasma 25(OH)D on outcome among 1016 patients with stage III colon cancer who were enrolled in a National Cancer Institute-sponsored adjuvant therapy trial (CALGB 89803). Predicted 25(OH)D scores were computed using validated regression models. We examined the influence of predicted 25(OH)D scores on cancer recurrence and mortality (disease-free survival; DFS) using Cox proportional hazards. Patients in the highest quintile of predicted 25(OH)D score had an adjusted hazard ratio (HR) for colon cancer recurrence or mortality (DFS) of 0.62 (95% confidence interval [CI], 0.44-0.86), compared with those in the lowest quintile (Ptrend = 0.005). Higher predicted 25(OH)D score was also associated with a significant improvement in recurrence-free survival and overall survival (Ptrend = 0.01 and 0.0004, respectively). The benefit associated with higher predicted 25(OH)D score appeared consistent across predictors of cancer outcome and strata of molecular tumor characteristics, including microsatellite instability and KRAS, BRAF, PIK3CA, and TP53 mutation status. Higher predicted 25(OH)D levels after a diagnosis of stage III colon cancer may be associated with decreased recurrence and improved survival. Clinical trials assessing the benefit of vitamin D supplementation in the adjuvant setting are warranted. NCT00003835. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  2. Incidence, Mortality, and Predictive Factors of Hepatocellular Carcinoma in Primary Biliary Cirrhosis

    Directory of Open Access Journals (Sweden)

    Kenichi Hosonuma

    2013-01-01

    Full Text Available Background. The study aims to analyze in detail the incidence, mortality using the standardized incidence ratio (SIR, and standardized mortality ratio (SMR of hepatocellular carcinoma (HCC in primary biliary cirrhosis (PBC, because no large case studies have focused on the detailed statistical analysis of them in Asia. Methods. The study cohorts were consecutively diagnosed at Gunma University and its affiliated hospitals. Age- or sex-specific annual cancer incidence and deaths were obtained from Japanese Cancer Registry and Death Registry as a reference for the comparison of SIR or SMR of HCC. Moreover, univariate analyses and multivariate analyses were performed to clarify predictive factors for the incidence of HCC. Results. The overall 179 patients were followed up for a median of 97 months. HCC had developed in 13 cases. SIR for HCC was 11.6 (95% confidence interval (CI, 6.2–19.8 and SMR for HCC was 11.2 (95% CI, 5.4–20.6 in overall patients. The serum albumin levels were a predictive factor for the incidence of HCC in overall patients. Conclusions. The incidence and mortality of HCC in PBC patients were significantly higher than those in Japanese general population. PBC patients with low serum albumin levels were populations at high risk for HCC.

  3. Spontaneous evolution in bilirubin levels predicts liver-related mortality in patients with alcoholic hepatitis.

    Directory of Open Access Journals (Sweden)

    Minjong Lee

    Full Text Available The accurate prognostic stratification of alcoholic hepatitis (AH is essential for individualized therapeutic decisions. The aim of this study was to develop a new prognostic model to predict liver-related mortality in Asian AH patients. We conducted a hospital-based, retrospective cohort study using 308 patients with AH between 1999 and 2011 (a derivation cohort and 106 patients with AH between 2005 and 2012 (a validation cohort. The Cox proportional hazards model was constructed to select significant predictors of liver-related death from the derivation cohort. A new prognostic model was internally validated using a bootstrap sampling method. The discriminative performance of this new model was compared with those of other prognostic models using a concordance index in the validation cohort. Bilirubin, prothrombin time, creatinine, potassium at admission, and a spontaneous change in bilirubin levels from day 0 to day 7 (SCBL were incorporated into a model for AH to grade the severity in an Asian patient cohort (MAGIC. For risk stratification, four risk groups were identified with cutoff scores of 29, 37, and 46 based on the different survival probabilities (P<0.001. In addition, MAGIC showed better discriminative performance for liver-related mortality than any other scoring system in the validation cohort. MAGIC can accurately predict liver-related mortality in Asian patients hospitalized for AH. Therefore, SCBL may help us decide whether patients with AH urgently require corticosteroid treatment.

  4. Increase in waist circumference over 6 years predicts subsequent cardiovascular disease and total mortality in nordic women

    DEFF Research Database (Denmark)

    Klingberg, Sofia; Mehlig, Kirsten; Lanfer, Anne

    2015-01-01

    -shaped association. Associations between increase in WC and outcomes were restricted to women with normal weight at baseline and to ever-smokers. CONCLUSIONS: In contrast to changes in HC which did not predict mortality and CVD, a 6-year increase in WC is strongly predictive, particularly among initially lean women...... and cardiovascular disease (CVD) mortality in women but that gain or loss in HC was unrelated to these outcomes. This study examines whether a 6-year change in waist circumference (WC) predicts mortality and CVD in the same study sample. METHODS: Baseline WC and 6-year change in WC as predictors of mortality and CVD...... were analyzed in 2,492 women from the Danish MONICA study and the Prospective Population Study of Women in Gothenburg, Sweden. RESULTS: Increase in WC was significantly associated with increased subsequent mortality and CVD adjusting for BMI and other covariates, with some evidence of a J...

  5. Abdominal obesity in Japanese-Brazilians: which measure is best for predicting all-cause and cardiovascular mortality?

    Directory of Open Access Journals (Sweden)

    Marselle Rodrigues Bevilacqua

    Full Text Available This study aimed to verify which anthropometric measure of abdominal obesity was the best predictor of all-cause and cardiovascular mortality in Japanese-Brazilians. The study followed 1,581 subjects for 14 years. Socio-demographic, lifestyle, metabolic, and anthropometric data were collected. The dependent variable was vital status (alive or dead at the end of the study, and the independent variable was presence of abdominal obesity according to different baseline measures. The mortality rate was estimated, and Poisson regression was used to obtain mortality rate ratios with abdominal obesity, adjusted simultaneously for the other variables. The mortality rate was 10.68/thousand person-years. Male gender, age > 60 years, and arterial hypertension were independent risk factors for mortality. The results indicate that prevalence of abdominal obesity was high among Japanese-Brazilians, and that waist/hip ratio was the measure with the greatest capacity to predict mortality (especially cardiovascular mortality in this group.

  6. Proliferative retinopathy and proteinuria predict mortality rate in type 1 diabetic patients from Fyn County, Denmark

    DEFF Research Database (Denmark)

    Grauslund, J; Green, A; Sjølie, A K

    2008-01-01

    AIMS/HYPOTHESIS: We evaluated the effect of diabetic retinopathy on 25 year survival rate among a population-based cohort of type 1 diabetic patients from Fyn County, Denmark. METHODS: In 1973 all diabetic patients from Fyn County, Denmark with onset before the age of 30 years as of 1 July 1973...... were identified (n=727). In 1981, only 627 patients were still alive and resident in Denmark. Of these, 573 (91%) participated in a clinical baseline examination, in which diabetic retinopathy was graded and other markers of diabetes measured. Mortality rate was examined in a 25 year follow....../INTERPRETATION: Proliferative retinopathy and proteinuria predict mortality rate in a population-based cohort of type 1 diabetic patients. In combination they act even more strongly. Non-proliferative diabetic retinopathy did not affect survival rate....

  7. Poor caregiver mental health predicts mortality of patients with neurodegenerative disease.

    Science.gov (United States)

    Lwi, Sandy J; Ford, Brett Q; Casey, James J; Miller, Bruce L; Levenson, Robert W

    2017-07-11

    Dementia and other neurodegenerative diseases cause profound declines in functioning; thus, many patients require caregivers for assistance with daily living. Patients differ greatly in how long they live after disease onset, with the nature and severity of the disease playing an important role. Caregiving can also be extremely stressful, and many caregivers experience declines in mental health. In this study, we investigated the role that caregiver mental health plays in patient mortality. In 176 patient-caregiver dyads, we found that worse caregiver mental health predicted greater patient mortality even when accounting for key risk factors in patients (i.e., diagnosis, age, sex, dementia severity, and patient mental health). These findings highlight the importance of caring for caregivers as well as patients when attempting to improve patients' lives.

  8. Lung Cancer Mortality and Radon Concentration in a Chronically Exposed Neighborhood in Chihuahua, Mexico: A Geospatial Analysis

    Science.gov (United States)

    Hinojosa de la Garza, Octavio R.; Sanín, Luz H.; Montero Cabrera, María Elena; Serrano Ramirez, Korina Ivette; Martínez Meyer, Enrique; Reyes Cortés, Manuel

    2014-01-01

    This study correlated lung cancer (LC) mortality with statistical data obtained from government public databases. In order to asses a relationship between LC deaths and radon accumulation in dwellings, indoor radon concentrations were measured with passive detectors randomly distributed in Chihuahua City. Kriging (K) and Inverse-Distance Weighting (IDW) spatial interpolations were carried out. Deaths were georeferenced and Moran's I correlation coefficients were calculated. The mean values (over n = 171) of the interpolation of radon concentrations of deceased's dwellings were 247.8 and 217.1 Bq/m3, for K and IDW, respectively. Through the Moran's I values obtained, correspondingly equal to 0.56 and 0.61, it was evident that LC mortality was directly associated with locations with high levels of radon, considering a stable population for more than 25 years, suggesting spatial clustering of LC deaths due to indoor radon concentrations. PMID:25165752

  9. CT pulmonary angiography findings that predict 30-day mortality in patients with acute pulmonary embolism

    Energy Technology Data Exchange (ETDEWEB)

    Bach, Andreas Gunter, E-mail: mail@andreas-bach.de [Department of Radiology, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06120 Halle (Germany); Nansalmaa, Baasai; Kranz, Johanna [Department of Radiology, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06120 Halle (Germany); Taute, Bettina-Maria [Department of Internal Medicine, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06120 Halle (Germany); Wienke, Andreas [Institute of Medical Epidemiology, Biostatistics and Informatics, Martin-Luther-University Halle-Wittenberg, Magdeburger-Str. 8, 06112 Halle (Germany); Schramm, Dominik; Surov, Alexey [Department of Radiology, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06120 Halle (Germany)

    2015-02-15

    Highlights: • In patients with acute pulmonary embolism contrast reflux in inferior vena cava is significantly stronger in non-survivors (odds ratio 3.29; p < 0.001). • This finding is independent from the following comorbidities: heart insufficiency and pulmonary hypertension. • Measurement of contrast reflux is a new and robust radiologic method for predicting 30-day mortality in patients with acute pulmonary embolism. • Measurement of contrast reflux is a better predictor of 30-day mortality after acute pulmonary embolism than any other existing radiologic predictor. This includes thrombus distribution, and morphometric measurements of right ventricular dysfunction. - Abstract: Purpose: Standard computed tomography pulmonary angiography (CTPA) can be used to diagnose acute pulmonary embolism. In addition, multiple findings at CTPA have been proposed as potential tools for risk stratification. Therefore, the aim of the present study is to examine the prognostic value of (I) thrombus distribution, (II) morphometric parameters of right ventricular dysfunction, and (III) contrast reflux in inferior vena cava on 30-day mortality. Material and methods: In a retrospective, single-center study from 06/2005 to 01/2010 365 consecutive patients were included. Inclusion criteria were: presence of acute pulmonary embolism, and availability of 30-day follow-up. A review of patient charts and images was performed. Results: There were no significant differences between the group of 326 survivors and 39 non-survivors in (I) thrombus distribution, and (II) morphometric measurements of right ventricular dysfunction. However, (III) contrast reflux in inferior vena cava was significantly stronger in non-survivors (odds ratio 3.29; p < 0.001). Results were independent from comorbidities like heart insufficiency and pulmonary hypertension. Conclusion: Measurement of contrast reflux is a new and robust method for predicting 30-day mortality in patients with acute pulmonary

  10. Accuracy of circulating histones in predicting persistent organ failure and mortality in patients with acute pancreatitis.

    Science.gov (United States)

    Liu, T; Huang, W; Szatmary, P; Abrams, S T; Alhamdi, Y; Lin, Z; Greenhalf, W; Wang, G; Sutton, R; Toh, C H

    2017-08-01

    Early prediction of acute pancreatitis severity remains a challenge. Circulating levels of histones are raised early in mouse models and correlate with disease severity. It was hypothesized that circulating histones predict persistent organ failure in patients with acute pancreatitis. Consecutive patients with acute pancreatitis fulfilling inclusion criteria admitted to Royal Liverpool University Hospital were enrolled prospectively between June 2010 and March 2014. Blood samples were obtained within 48 h of abdominal pain onset and relevant clinical data during the hospital stay were collected. Healthy volunteers were enrolled as controls. The primary endpoint was occurrence of persistent organ failure. The predictive values of circulating histones, clinical scores and other biomarkers were determined. Among 236 patients with acute pancreatitis, there were 156 (66·1 per cent), 57 (24·2 per cent) and 23 (9·7 per cent) with mild, moderate and severe disease respectively, according to the revised Atlanta classification. Forty-seven healthy volunteers were included. The area under the receiver operating characteristic (ROC) curve (AUC) for circulating histones in predicting persistent organ failure and mortality was 0·92 (95 per cent c.i. 0·85 to 0·99) and 0·96 (0·92 to 1·00) respectively; histones were at least as accurate as clinical scores or biochemical markers. For infected pancreatic necrosis and/or sepsis, the AUC was 0·78 (0·62 to 0·94). Histones did not predict or correlate with local pancreatic complications, but correlated negatively with leucocyte cell viability (r = -0·511, P = 0·001). Quantitative assessment of circulating histones in plasma within 48 h of abdominal pain onset can predict persistent organ failure and mortality in patients with acute pancreatitis. Early death of immune cells may contribute to raised circulating histone levels in acute pancreatitis. © 2017 The Authors. BJS published by John Wiley & Sons Ltd on behalf of BJS

  11. Point-of-care testing on admission to the intensive care unit: lactate and glucose independently predict mortality.

    Science.gov (United States)

    Martin, Jan; Blobner, Manfred; Busch, Raymonde; Moser, Norman; Kochs, Eberhard; Luppa, Peter B

    2013-02-01

    The aim of the study was to retrospectively investigate whether parameters of routine point-of-care testing (POCT) predict hospital mortality in critically ill surgical patients on admission to the intensive care unit (ICU). Arterial blood analyses of 1551 patients on admission to the adult surgical ICU of the Technical University Munich were reviewed. POCT was performed on a blood gas analyser. The association between acid-base status and mortality was evaluated. Metabolic acidosis was defined by base excess (BE) lactate >50% of BE, anion gap (AG)-acidosis by AG >16 mmol/L, hyperchloraemic acidosis by chloride >115 mmol/L. Metabolic alkalosis was defined by BE ≥3 mmol/L. Logistic regression analysis identified variables independently associated with mortality. Overall mortality was 8.8%. Mortality was greater in male patients (p=0.012). Mean age was greater in non-survivors (p55 mm Hg (mortality 23.1%). Three hundred and seventy-seven patients presented with acidosis (mortality 11.4%), thereof 163 patients with lactic acidosis (mortality 19%). Mortality for alkalosis (174 patients) was 12.1%. Mean blood glucose level for non-survivors was higher compared to survivors (plactate, glucose, age, male gender as independent predictors of mortality. Lactate and glucose on ICU admission independently predict mortality. BE and AG failed as prognostic markers. Lactic acidosis showed a high mortality rate implying that lactate levels should be obtained on ICU admission. Prevalence of hyperchloraemic acidosis was low. Metabolic alkalosis was associated with an increased mortality. Further studies on this disturbance and its attendant high mortality are warranted.

  12. Mortality Predicted Accuracy for Hepatocellular Carcinoma Patients with Hepatic Resection Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Herng-Chia Chiu

    2013-01-01

    Full Text Available The aim of this present study is firstly to compare significant predictors of mortality for hepatocellular carcinoma (HCC patients undergoing resection between artificial neural network (ANN and logistic regression (LR models and secondly to evaluate the predictive accuracy of ANN and LR in different survival year estimation models. We constructed a prognostic model for 434 patients with 21 potential input variables by Cox regression model. Model performance was measured by numbers of significant predictors and predictive accuracy. The results indicated that ANN had double to triple numbers of significant predictors at 1-, 3-, and 5-year survival models as compared with LR models. Scores of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC of 1-, 3-, and 5-year survival estimation models using ANN were superior to those of LR in all the training sets and most of the validation sets. The study demonstrated that ANN not only had a great number of predictors of mortality variables but also provided accurate prediction, as compared with conventional methods. It is suggested that physicians consider using data mining methods as supplemental tools for clinical decision-making and prognostic evaluation.

  13. Mortality Predicted Accuracy for Hepatocellular Carcinoma Patients with Hepatic Resection Using Artificial Neural Network

    Science.gov (United States)

    Chiu, Herng-Chia; Ho, Te-Wei; Lee, King-Teh; Chen, Hong-Yaw; Ho, Wen-Hsien

    2013-01-01

    The aim of this present study is firstly to compare significant predictors of mortality for hepatocellular carcinoma (HCC) patients undergoing resection between artificial neural network (ANN) and logistic regression (LR) models and secondly to evaluate the predictive accuracy of ANN and LR in different survival year estimation models. We constructed a prognostic model for 434 patients with 21 potential input variables by Cox regression model. Model performance was measured by numbers of significant predictors and predictive accuracy. The results indicated that ANN had double to triple numbers of significant predictors at 1-, 3-, and 5-year survival models as compared with LR models. Scores of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of 1-, 3-, and 5-year survival estimation models using ANN were superior to those of LR in all the training sets and most of the validation sets. The study demonstrated that ANN not only had a great number of predictors of mortality variables but also provided accurate prediction, as compared with conventional methods. It is suggested that physicians consider using data mining methods as supplemental tools for clinical decision-making and prognostic evaluation. PMID:23737707

  14. Using data-driven rules to predict mortality in severe community acquired pneumonia.

    Directory of Open Access Journals (Sweden)

    Chuang Wu

    Full Text Available Prediction of patient-centered outcomes in hospitals is useful for performance benchmarking, resource allocation, and guidance regarding active treatment and withdrawal of care. Yet, their use by clinicians is limited by the complexity of available tools and amount of data required. We propose to use Disjunctive Normal Forms as a novel approach to predict hospital and 90-day mortality from instance-based patient data, comprising demographic, genetic, and physiologic information in a large cohort of patients admitted with severe community acquired pneumonia. We develop two algorithms to efficiently learn Disjunctive Normal Forms, which yield easy-to-interpret rules that explicitly map data to the outcome of interest. Disjunctive Normal Forms achieve higher prediction performance quality compared to a set of state-of-the-art machine learning models, and unveils insights unavailable with standard methods. Disjunctive Normal Forms constitute an intuitive set of prediction rules that could be easily implemented to predict outcomes and guide criteria-based clinical decision making and clinical trial execution, and thus of greater practical usefulness than currently available prediction tools. The Java implementation of the tool JavaDNF will be publicly available.

  15. Dead or Alive? Using Membrane Failure and Chlorophyll a Fluorescence to Predict Plant Mortality from Drought.

    Science.gov (United States)

    Guadagno, Carmela R; Ewers, Brent E; Speckman, Heather N; Aston, Timothy Llewellyn; Huhn, Bridger J; DeVore, Stanley B; Ladwig, Joshua T; Strawn, Rachel N; Weinig, Cynthia

    2017-09-01

    Climate models predict widespread increases in both drought intensity and duration in the next decades. Although water deficiency is a significant determinant of plant survival, limited understanding of plant responses to extreme drought impedes forecasts of both forest and crop productivity under increasing aridity. Drought induces a suite of physiological responses; however, we lack an accurate mechanistic description of plant response to lethal drought that would improve predictive understanding of mortality under altered climate conditions. Here, proxies for leaf cellular damage, chlorophyll a fluorescence, and electrolyte leakage were directly associated with failure to recover from drought upon rewatering in Brassica rapa (genotype R500) and thus define the exact timing of drought-induced death. We validated our results using a second genotype (imb211) that differs substantially in life history traits. Our study demonstrates that whereas changes in carbon dynamics and water transport are critical indicators of drought stress, they can be unrelated to visible metrics of mortality, i.e. lack of meristematic activity and regrowth. In contrast, membrane failure at the cellular scale is the most proximate cause of death. This hypothesis was corroborated in two gymnosperms ( Picea engelmannii and Pinus contorta ) that experienced lethal water stress in the field and in laboratory conditions. We suggest that measurement of chlorophyll a fluorescence can be used to operationally define plant death arising from drought, and improved plant characterization can enhance surface model predictions of drought mortality and its consequences to ecosystem services at a global scale. © 2017 American Society of Plant Biologists. All Rights Reserved.

  16. The pediatric index of mortality 3 score to predict mortality in a pediatric intensive care unit in Palembang, South Sumatera, Indonesia

    Directory of Open Access Journals (Sweden)

    Destiana Sera Puspita Sari

    2017-06-01

    Conclusion In Mohammad Hoesin Hospital, Palembang, South Sumatera, the PIM 3 can be used to predict mortality in PICU patients, but the score should be multiplied by a factor of 2.24. This recalibration is needed due to the presumed lower standard of care at this hospital compared to that of the originating PIM 3 institutions in developed countries.

  17. Prostate-specific antigen and long-term prediction of prostate cancer incidence and mortality in the general population

    DEFF Research Database (Denmark)

    Ørsted, David Dynnes; Nordestgaard, Børge G; Jensen, Gorm B

    2012-01-01

    It is largely unknown whether prostate-specific antigen (PSA) level at first date of testing predicts long-term risk of prostate cancer (PCa) incidence and mortality in the general population.......It is largely unknown whether prostate-specific antigen (PSA) level at first date of testing predicts long-term risk of prostate cancer (PCa) incidence and mortality in the general population....

  18. Comparison of marine dispersion model predictions with environmental radionuclide concentrations

    International Nuclear Information System (INIS)

    Johnson, C.E.; McKay, W.A.

    1988-01-01

    The comparison of marine dispersion model results with measurements is an essential part of model development and testing. The results from two residual flow models are compared with seawater concentrations, and in one case with concentrations measured in marine molluscs. For areas with short turnover times, seawater concentrations respond rapidly to variations in discharge rate and marine currents. These variations are difficult to model, and comparison with concentrations in marine animals provides an alternative and complementary technique for model validation with the advantages that the measurements reflect the mean conditions and frequently form a useful time series. (author)

  19. Effect of wind turbine mortality on noctule bats in Sweden: predictions from a simple population model

    Energy Technology Data Exchange (ETDEWEB)

    Rydell, Jens; Hedenstroem, Anders; Green, Martin

    2011-07-01

    Full text: The noctule bat Nyctalus noctula is apparently the species most seriously affected by wind turbine mortality in northern Europe. It occurs in south Sweden up to about 60oN, although the abundance is much higher in lowland agricultural areas than in forests. We used a recent estimate of 90 000 individuals as the population size in Sweden, and assumed a stable starting population not affected by mortality from wind turbines. In the absence of data from Sweden, we used demographic data and fatality rates at wind turbines (0.9 noctules/turbine/year) obtained in eastern Germany. Population development up to year 2020 was calculated, based on the current estimate of wind farm development in Sweden; ca. 1000 present and 2500 additional turbines within the area of noctule distribution. The results suggest that the additional mortality at wind turbines may affect the noctule bat in Sweden at the population level. However, the effect will probably be small, particularly in comparison with other anthropogenic sources. We are currently using the model to predict the effect on other bat species and birds. (Author)

  20. Flow-Mediated Dilatation and Asymmetric Dimethylarginine Do Not Predict Mortality in Peritoneal Dialysis Patients

    Directory of Open Access Journals (Sweden)

    Sami Uzun

    2017-09-01

    Full Text Available Aim: Asymmetric dimethylarginine (ADMA is associated with increased coronary artery disease risk through endothelial dysfunction in dialysis patients. We aimed to investigate the role of flow-mediated dilatation (FMD, a non-invasive indicator of endothelial function, and ADMA in mortality in peritoneal dialysis (PD patients. Methods: PD patients aged 18-80 years; with dialysis duration of at least three months were included. FMD measurement and ADMA levels were recorded. Outcome of the patients on the third year were analyzed with binary logistic analyses. Results: The mean age of the 55 patients was 53±15 years and the mean follow-up duration was 36 months. Mean FMD and ADMA levels were 10.6±6.4% and 81.8±48.0 mol/L, respectively. Eighteen patients died during follow-up. Age, presence of diabetes mellitus and ischemic heart disease, ultrafiltration amount and serum albumin level were related with mortality while gender, weekly Kt/V and ADMA levels were not. There was no significant relationship between ADMA level and FMD (p=0.873. FMD was negatively correlated with systolic and diastolic blood pressures (p=0.001, p<0.001, respectively. Hypertension was found to be the most important single factor determining FMD (p=0.037. Conclusion: Estimating endothelial function by FMD or measuring serum ADMA levels may not be useful for predicting mortality in PD patients.

  1. Cost and mortality impact of an algorithm-driven sepsis prediction system.

    Science.gov (United States)

    Calvert, Jacob; Hoffman, Jana; Barton, Christopher; Shimabukuro, David; Ries, Michael; Chettipally, Uli; Kerem, Yaniv; Jay, Melissa; Mataraso, Samson; Das, Ritankar

    2017-06-01

    To compute the financial and mortality impact of InSight, an algorithm-driven biomarker, which forecasts the onset of sepsis with minimal use of electronic health record data. This study compares InSight with existing sepsis screening tools and computes the differential life and cost savings associated with its use in the inpatient setting. To do so, mortality reduction is obtained from an increase in the number of sepsis cases correctly identified by InSight. Early sepsis detection by InSight is also associated with a reduction in length-of-stay, from which cost savings are directly computed. InSight identifies more true positive cases of severe sepsis, with fewer false alarms, than comparable methods. For an individual ICU with 50 beds, for example, it is determined that InSight annually saves 75 additional lives and reduces sepsis-related costs by $560,000. InSight performance results are derived from analysis of a single-center cohort. Mortality reduction results rely on a simplified use case, which fixes prediction times at 0, 1, and 2 h before sepsis onset, likely leading to under-estimates of lives saved. The corresponding cost reduction numbers are based on national averages for daily patient length-of-stay cost. InSight has the potential to reduce sepsis-related deaths and to lead to substantial cost savings for healthcare facilities.

  2. Prognostic Importance of Low Admission Serum Creatinine Concentration for Mortality in Hospitalized Patients.

    Science.gov (United States)

    Thongprayoon, Charat; Cheungpasitporn, Wisit; Kittanamongkolchai, Wonngarm; Harrison, Andrew M; Kashani, Kianoush

    2017-05-01

    The study objective was to assess the association between low serum creatinine value at admission and in-hospital mortality in hospitalized patients. This was a retrospective single-center cohort study conducted at a tertiary referral hospital. All hospitalized adult patients between 2011 and 2013 who had an admission creatinine value available were identified for inclusion in this study. Admission creatinine value was categorized into 7 groups: ≤0.4, 0.5 to 0.6, 0.7 to 0.8, 0.9 to 1.0, 1.1 to 1.2, 1.3 to 1.4, and ≥1.5 mg/dL. The primary outcome was in-hospital mortality. Logistic regression analysis was performed to obtain the odds ratio of in-hospital mortality for the various admission creatinine levels, using a creatinine value of 0.7 to 0.8 mg/dL as the reference group in the analysis of all patients and female patients and of 0.9 to 1.0 mg/dL in the analysis of male patients because it was associated with the lowest in-hospital mortality. Of 73,994 included patients, 973 (1.3%) died in the hospital. The association between different categories of admission creatinine value and in-hospital mortality assumed a U-shaped distribution, with both low and high creatinine values associated with higher in-hospital mortality. After adjustment for age, sex, ethnicity, principal diagnosis, and comorbid conditions, very low creatinine value (≤0.4 mg/dL) was significantly associated with increased mortality (odds ratio, 3.29; 95% confidence interval, 2.08-5.00), exceeding the risk related to a markedly increased creatinine value of ≥1.5 mg/dL (odds ratio, 2.56; 95% confidence interval, 2.07-3.17). The association remained significant in the subgroup analysis of male and female patients. Low creatinine value at admission is independently associated with increased in-hospital mortality in hospitalized patients. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Association between serum interleukin-6 concentrations and mortality in older adults: the Rancho Bernardo study.

    Directory of Open Access Journals (Sweden)

    Jeffrey K Lee

    Full Text Available Interleukin-6 (IL-6 may have a protective role in acute liver disease but a detrimental effect in chronic liver disease. It is unknown whether IL-6 is associated with risk of liver-related mortality in humans.To determine if IL-6 is associated with an increased risk of all-cause, cardiovascular disease (CVD, cancer, and liver-related mortality.A prospective cohort study included 1843 participants who attended a research visit in 1984-87. Multiple covariates were ascertained including serum IL-6. Multivariable-adjusted Cox proportional hazards regression analyses were used to examine the association between serum IL-6 as a continuous (log transformed variable with all-cause, CVD, cancer, and liver-related mortality. Patients with prevalent CVD, cancer and liver disease were excluded for cause-specific mortality.The mean (± standard deviation age and body-mass-index (BMI of participants was 68 (± 10.6 years and 25 (± 3.7 Kg/m(2, respectively. During the 25,802 person-years of follow-up, the cumulative all-cause, CVD, cancer, and liver-related mortality were 53.1% (N = 978, 25.5%, 11.3%, and 1.3%, respectively. The median (± IQR length of follow-up was 15.3 ± 10.6 years. In multivariable analyses, adjusted for age, sex, alcohol, BMI, diabetes, hypertension, total cholesterol, HDL, and smoking, one-SD increment in log-transformed serum IL-6 was associated with increased risk of all-cause, CVD, cancer, and liver-related mortality, with hazard ratios of 1.48 (95% CI, 1.33-1.64, 1.38 (95% CI, 1.16-1.65, 1.35 (95% CI, 1.02-1.79, and 1.88 (95% CI, 0.97-3.67, respectively. CRP adjustment attenuated the effects but the association between IL-6 and all-cause and CVD mortality remained statistically significant, independent of CRP levels.In community-dwelling older adults, serum IL-6 is associated with all-cause, CVD, cancer, and liver-related mortality.

  4. [Predictive value of the VMS theme 'Frail elderly': delirium, falling and mortality in elderly hospital patients].

    Science.gov (United States)

    Oud, Frederike M M; de Rooij, Sophia E J A; Schuurman, Truus; Duijvelaar, Karlijn M; van Munster, Barbara C

    2015-01-01

    To determine the predictive value of safety management system (VMS) screening questions for falling, delirium, and mortality, as punt down in the VMS theme 'Frail elderly'. Retrospective observational study. We selected all patients ≥ 70 years who were admitted to non-ICU wards at the Deventer Hospital, the Netherlands, for at least 24 hours between 28 March 2011 and 10 June 2011. On admission, patients were screened with the VMS instrument by a researcher. Delirium and falls were recorded during hospitalisation. Six months after hospitalisation, data on mortality were collected. We included 688 patients with a median age of 78.7 (range: 70.0-97.1); 50.7% was male. The sensitivity of the screening for delirium risk was 82%, the specificity 62%. The sensitivity of the screening for risk of falling was 63%, the specificity 65%. Independent predictors for mortality within 6 months were delirium risk (odds ratio (OR): 2.3; 95% CI 1.1-3.2), malnutrition (OR: 2.1; 95% CI 1.3-3.5), admission to a non-surgical ward (OR: 3.0; 95% CI 1.8-5.1), and older age (OR: 1.1; 95%CI 1.0-1.1). Patients classified by the VMS theme 'Frail elderly' as having more risk factors had a higher risk of dying (p instrument for identifying those elderly people with a high risk of developing this condition; the VMS sensitivity for fall risk is moderate. The number of positive VMS risk factors correlates with mortality and may therefore be regarded as a measure of frailty.

  5. Mini Nutritional Assessment predicts gait status and mortality 6 months after hip fracture.

    Science.gov (United States)

    Gumieiro, David N; Rafacho, Bruna P M; Gonçalves, Andrea F; Tanni, Suzana E; Azevedo, Paula S; Sakane, Daniel T; Carneiro, Carlos A S; Gaspardo, David; Zornoff, Leonardo A M; Pereira, Gilberto J C; Paiva, Sergio A R; Minicucci, Marcos F

    2013-05-01

    The aim of the present study was to evaluate the Mini Nutritional Assessment (MNA), the Nutritional Risk Screening (NRS) 2002 and the American Society of Anesthesiologists Physical Status Score (ASA) as predictors of gait status and mortality 6 months after hip fracture. A total of eighty-eight consecutive patients over the age of 65 years with hip fracture admitted to an orthopaedic unit were prospectively evaluated. Within the first 72 h of admission, each patient's characteristics were recorded, and the MNA, the NRS 2002 and the ASA were performed. Gait status and mortality were evaluated 6 months after hip fracture. Of the total patients, two were excluded because of pathological fractures. The remaining eighty-six patients (aged 80·2 (sd 7·3) years) were studied. Among these patients 76·7 % were female, 69·8 % walked with or without support and 12·8 % died 6 months after the fracture. In a multivariate analysis, only the MNA was associated with gait status 6 months after hip fracture (OR 0·773, 95 % CI 0·663, 0·901; P= 0·001). In the Cox regression model, only the MNA was associated with mortality 6 months after hip fracture (hazard ratio 0·869, 95 % CI 0·757, 0·998; P= 0·04). In conclusion, the MNA best predicts gait status and mortality 6 months after hip fracture. These results suggest that the MNA should be included in the clinical stratification of patients with hip fracture to identify and treat malnutrition in order to improve the outcomes.

  6. Nutritional Status Predicts 10-Year Mortality in Patients with End-Stage Renal Disease on Hemodialysis

    Directory of Open Access Journals (Sweden)

    Shin Sook Kang

    2017-04-01

    Full Text Available Protein-energy wasting (PEW is associated with mortality in patients with end-stage renal disease (ESRD on maintenance hemodialysis. The correct diagnosis of PEW is extremely important in order to predict clinical outcomes. However, it is unclear which parameters should be used to diagnose PEW. Therefore, this retrospective observational study investigated the relationship between mortality and nutritional parameters in ESRD patients on maintenance hemodialysis. A total of 144 patients were enrolled. Nutritional parameters, including body mass index, serum albumin, dietary intake, normalized protein catabolic rate (nPCR, and malnutrition inflammation score (MIS, were measured at baseline. Fifty-three patients died during the study. Survivors had significantly higher nPCR (1.10 ± 0.24 g/kg/day vs. 1.01 ± 0.21 g/kg/day; p = 0.048, energy intake (26.7 ± 5.8 kcal/kg vs. 24.3 ± 4.2 kcal/kg; p = 0.009 and protein intake (0.91 ± 0.21 g/kg vs. 0.82 ± 0.24 g/kg; p = 0.020, and lower MIS (5.2 ± 2.3 vs. 6.1 ± 2.1, p = 0.039. In multivariable analysis, energy intake <25 kcal/kg (HR 1.860, 95% CI 1.018–3.399; p = 0.044 and MIS > 5 (HR 2.146, 95% CI 1.173–3.928; p = 0.013 were independent variables associated with all-cause mortality. These results suggest that higher MIS and lower energy intake are harmful to ESRD patients on maintenance hemodialysis. Optimal energy intake could reduce mortality in these patients.

  7. Sarcopenia predicts 1-year mortality in elderly patients undergoing curative gastrectomy for gastric cancer: a prospective study.

    Science.gov (United States)

    Huang, Dong-Dong; Chen, Xiao-Xi; Chen, Xi-Yi; Wang, Su-Lin; Shen, Xian; Chen, Xiao-Lei; Yu, Zhen; Zhuang, Cheng-Le

    2016-11-01

    One-year mortality is vital for elderly oncologic patients undergoing surgery. Recent studies have demonstrated that sarcopenia can predict outcomes after major abdominal surgeries, but the association of sarcopenia and 1-year mortality has never been investigated in a prospective study. We conducted a prospective study of elderly patients (≥65 years) who underwent curative gastrectomy for gastric cancer from July 2014 to July 2015. Sarcopenia was determined by the measurements of muscle mass, handgrip strength, and gait speed. Univariate and multivariate analyses were used to identify the risk factors associated with 1-year mortality. A total of 173 patients were included, in which 52 (30.1 %) patients were identified as having sarcopenia. Twenty-four (13.9 %) patients died within 1 year of surgery. Multivariate analysis showed that sarcopenia was an independent risk factor for 1-year mortality. Area under the receiver operating characteristic curve demonstrated an increased predictive power for 1-year mortality with the inclusion of sarcopenia, from 0.835 to 0.868. Solely low muscle mass was not predictive of 1-year mortality in the multivariate analysis. Sarcopenia is predictive of 1-year mortality in elderly patients undergoing gastric cancer surgery. The measurement of muscle function is important for sarcopenia as a preoperative assessment tool.

  8. Predicting hospital mortality among frequently readmitted patients: HSMR biased by readmission

    Directory of Open Access Journals (Sweden)

    Kelder Johannes C

    2011-03-01

    Full Text Available Abstract Background Casemix adjusted in-hospital mortality is one of the measures used to improve quality of care. The adjustment currently used does not take into account the effects of readmission, because reliable data on readmission is not readily available through routinely collected databases. We have studied the impact of readmissions by linking admissions of the same patient, and as a result were able to compare hospital mortality among frequently, as opposed to, non-frequently readmitted patients. We also formulated a method to adjust for readmission for the calculation of hospital standardised mortality ratios (HSMRs. Methods We conducted a longitudinal retrospective analysis of routinely collected hospital data of six large non-university teaching hospitals in the Netherlands with casemix adjusted standardised mortality ratios ranging from 65 to 114 and a combined value of 93 over a five-year period. Participants concerned 240662 patients admitted 418566 times in total during the years 2003 - 2007. Predicted deaths by the HSMR model 2008 over a five-year period were compared with observed deaths. Results Numbers of readmissions per patient differ substantially between the six hospitals, up to a factor of 2. A large interaction was found between numbers of admissions per patient and HSMR-predicted risks. Observed deaths for frequently admitted patients were significantly lower than HSMR-predicted deaths, which could be explained by uncorrected factors surrounding readmissions. Conclusions Patients admitted more frequently show lower risks of dying on average per admission. This decline in risk is only partly detected by the current HSMR. Comparing frequently admitted patients to non-frequently admitted patients commits the constant risk fallacy and potentially lowers HSMRs of hospitals treating many frequently admitted patients and increases HSMRs of hospitals treating many non-frequently admitted patients. This misleading effect can

  9. Predicting hospital mortality among frequently readmitted patients: HSMR biased by readmission

    Science.gov (United States)

    2011-01-01

    Background Casemix adjusted in-hospital mortality is one of the measures used to improve quality of care. The adjustment currently used does not take into account the effects of readmission, because reliable data on readmission is not readily available through routinely collected databases. We have studied the impact of readmissions by linking admissions of the same patient, and as a result were able to compare hospital mortality among frequently, as opposed to, non-frequently readmitted patients. We also formulated a method to adjust for readmission for the calculation of hospital standardised mortality ratios (HSMRs). Methods We conducted a longitudinal retrospective analysis of routinely collected hospital data of six large non-university teaching hospitals in the Netherlands with casemix adjusted standardised mortality ratios ranging from 65 to 114 and a combined value of 93 over a five-year period. Participants concerned 240662 patients admitted 418566 times in total during the years 2003 - 2007. Predicted deaths by the HSMR model 2008 over a five-year period were compared with observed deaths. Results Numbers of readmissions per patient differ substantially between the six hospitals, up to a factor of 2. A large interaction was found between numbers of admissions per patient and HSMR-predicted risks. Observed deaths for frequently admitted patients were significantly lower than HSMR-predicted deaths, which could be explained by uncorrected factors surrounding readmissions. Conclusions Patients admitted more frequently show lower risks of dying on average per admission. This decline in risk is only partly detected by the current HSMR. Comparing frequently admitted patients to non-frequently admitted patients commits the constant risk fallacy and potentially lowers HSMRs of hospitals treating many frequently admitted patients and increases HSMRs of hospitals treating many non-frequently admitted patients. This misleading effect can only be demonstrated by an

  10. Simple Scoring System to Predict In-Hospital Mortality After Surgery for Infective Endocarditis.

    Science.gov (United States)

    Gatti, Giuseppe; Perrotti, Andrea; Obadia, Jean-François; Duval, Xavier; Iung, Bernard; Alla, François; Chirouze, Catherine; Selton-Suty, Christine; Hoen, Bruno; Sinagra, Gianfranco; Delahaye, François; Tattevin, Pierre; Le Moing, Vincent; Pappalardo, Aniello; Chocron, Sidney

    2017-07-20

    Aspecific scoring systems are used to predict the risk of death postsurgery in patients with infective endocarditis (IE). The purpose of the present study was both to analyze the risk factors for in-hospital death, which complicates surgery for IE, and to create a mortality risk score based on the results of this analysis. Outcomes of 361 consecutive patients (mean age, 59.1±15.4 years) who had undergone surgery for IE in 8 European centers of cardiac surgery were recorded prospectively, and a risk factor analysis (multivariable logistic regression) for in-hospital death was performed. The discriminatory power of a new predictive scoring system was assessed with the receiver operating characteristic curve analysis. Score validation procedures were carried out. Fifty-six (15.5%) patients died postsurgery. BMI >27 kg/m 2 (odds ratio [OR], 1.79; P =0.049), estimated glomerular filtration rate 55 mm Hg (OR, 1.78; P =0.032), and critical state (OR, 2.37; P =0.017) were independent predictors of in-hospital death. A scoring system was devised to predict in-hospital death postsurgery for IE (area under the receiver operating characteristic curve, 0.780; 95% CI, 0.734-0.822). The score performed better than 5 of 6 scoring systems for in-hospital death after cardiac surgery that were considered. A simple scoring system based on risk factors for in-hospital death was specifically created to predict mortality risk postsurgery in patients with IE. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

  11. Extravasation of contrast (Spot Sign) predicts in-hospital mortality in ruptured arteriovenous malformation.

    Science.gov (United States)

    Ye, Zengpanpan; Ai, Xiaolin; Zheng, Jun; Hu, Xin; You, Chao; Andrew M, Faramand; Fang, Fang

    2017-10-09

    The spot sign is a highly specific and sensitive predictor of hematoma expansion in following primary intracerebral hemorrhage (ICH). Rare cases of the spot sign have been documented in patients with intracranial hemorrhage secondary to arteriovenous malformation (AVM). The purpose of this retrospective study is to assess the accuracy of spot sign in predicting clinical outcomes in patients with ruptured AVM. A retrospective analysis of a prospectively maintained database was performed for patients who presented to West China Hospital with ICH secondary to AVM in the period between January 2009 and September 2016. Two radiologists blinded to the clinical data independently assessed the imaging data, including the presence of spot sign. Statistical analysis using univariate testing, multivariate logistic regression testing, and receiver operating characteristic curve (AUC) analysis was performed. A total of 116 patients were included. Overall, 18.9% (22/116) of subjects had at least 1 spot sign detected by CT angiography, 7% (8/116) died in hospital, and 27% (31/116) of the patients had a poor outcome after 90 days. The spot sign had a sensitivity of 62.5% and specificity of 84.3% for predicting in-hospital mortality (p = .02, AUC 0.734). No correlation detected between the spot sign and 90-day outcomes under multiple logistic regression (p = .19). The spot sign is an independent predictor for in-hospital mortality. The presence of spot sign did not correlate with the 90 day outcomes in this patient cohort. The results of this report suggest that patients with ruptured AVM with demonstrated the spot sign on imaging must receive aggressive treatment early on due to the high risk of mortality.

  12. Darcy’s law predicts widespread forest mortality under climate warming

    Science.gov (United States)

    McDowell, Nate G.; Allen, Craig D.

    2015-01-01

    Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We use a hydraulic corollary to Darcy’s law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy’s law indicates today’s forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy’s corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. Given the robustness of Darcy’s law for predictions of vascular plant function, we conclude with high certainty that today’s forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.

  13. explICU: A web-based visualization and predictive modeling toolkit for mortality in intensive care patients.

    Science.gov (United States)

    Chen, Robert; Kumar, Vikas; Fitch, Natalie; Jagadish, Jitesh; Lifan Zhang; Dunn, William; Duen Horng Chau

    2015-01-01

    Preventing mortality in intensive care units (ICUs) has been a top priority in American hospitals. Predictive modeling has been shown to be effective in prediction of mortality based upon data from patients' past medical histories from electronic health records (EHRs). Furthermore, visualization of timeline events is imperative in the ICU setting in order to quickly identify trends in patient histories that may lead to mortality. With the increasing adoption of EHRs, a wealth of medical data is becoming increasingly available for secondary uses such as data exploration and predictive modeling. While data exploration and predictive modeling are useful for finding risk factors in ICU patients, the process is time consuming and requires a high level of computer programming ability. We propose explICU, a web service that hosts EHR data, displays timelines of patient events based upon user-specified preferences, performs predictive modeling in the back end, and displays results to the user via intuitive, interactive visualizations.

  14. Personalized mortality prediction driven by electronic medical data and a patient similarity metric.

    Directory of Open Access Journals (Sweden)

    Joon Lee

    Full Text Available Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1 to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2 to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made.We deployed a cosine-similarity-based patient similarity metric (PSM to an intensive care unit (ICU database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care.The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR systems, our novel medical data analytics

  15. Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric

    Science.gov (United States)

    Lee, Joon; Maslove, David M.; Dubin, Joel A.

    2015-01-01

    Background Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made. Methods and Findings We deployed a cosine-similarity-based patient similarity metric (PSM) to an intensive care unit (ICU) database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care. Conclusions The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our

  16. Personalized mortality prediction driven by electronic medical data and a patient similarity metric.

    Science.gov (United States)

    Lee, Joon; Maslove, David M; Dubin, Joel A

    2015-01-01

    Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made. We deployed a cosine-similarity-based patient similarity metric (PSM) to an intensive care unit (ICU) database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care. The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our novel medical data analytics contributes to

  17. Predicting the Concentration Characteristics of Itakpe Iron Ore for cut ...

    African Journals Online (AJOL)

    MICHAEL HORSFALL

    ABSTRACT: Concentration characteristics of an ore are very critical to the estimation of cut-off grade of a ... enormous financial cost of laboratory analysis and time required for such .... Arua A.I. (1997) Fundamentals of statistics, Publisher,.

  18. Correlation for predicting aerosol concentration in sodium spray fires

    International Nuclear Information System (INIS)

    Marimuthu, K.

    2001-01-01

    Aerosol behaviour computer codes are reported for the study of time-dependent airborne aerosol concentration in a containment. The use of available computer codes requires a thorough knowledge of the various rate processes employed to describe the aerosol behaviour. The present work describes a simple empirical equation to calculate sodium fire aerosol concentration with respect to time in a containment and is applicable to sodium spray fire conditions. Sodium spray fire aerosol concentration values obtained using this simplified approach agree reasonably well with experimental results. The empirical equation described in the present work is incorporated in the spray fire code NACOM and the code calculated values of aerosol concentration agreement with the sodium spray fire experimental results is reasonably good. (author)

  19. Predicting human epidermal melanin concentrations for different skin tones

    CSIR Research Space (South Africa)

    Smit, Jacoba E

    2011-07-01

    Full Text Available epidermal melanin concentrations for different skin tones JE Smit 1 , AE Karsten 2 , RW Sparrow 1 1 CSIR Biosciences, Pretoria, South Africa 2 CSIR National Laser Centre, Pretoria, South Africa Author e-mail address: KSmit...

  20. Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria

    Directory of Open Access Journals (Sweden)

    Kimmel Marek

    2011-05-01

    Full Text Available Abstract Background Volunteering participants in disease studies tend to be healthier than the general population partially due to specific enrollment criteria. Using modeling to accurately predict outcomes of cohort studies enrolling volunteers requires adjusting for the bias introduced in this way. Here we propose a new method to account for the effect of a specific form of healthy volunteer bias resulting from imposing disease status-related eligibility criteria, on disease-specific mortality, by explicitly modeling the length of the time interval between the moment when the subject becomes ineligible for the study, and the outcome. Methods Using survival time data from 1190 newly diagnosed lung cancer patients at MD Anderson Cancer Center, we model the time from clinical lung cancer diagnosis to death using an exponential distribution to approximate the length of this interval for a study where lung cancer death serves as the outcome. Incorporating this interval into our previously developed lung cancer risk model, we adjust for the effect of disease status-related eligibility criteria in predicting the number of lung cancer deaths in the control arm of CARET. The effect of the adjustment using the MD Anderson-derived approximation is compared to that based on SEER data. Results Using the adjustment developed in conjunction with our existing lung cancer model, we are able to accurately predict the number of lung cancer deaths observed in the control arm of CARET. Conclusions The resulting adjustment was accurate in predicting the lower rates of disease observed in the early years while still maintaining reasonable prediction ability in the later years of the trial. This method could be used to adjust for, or predict the duration and relative effect of any possible biases related to disease-specific eligibility criteria in modeling studies of volunteer-based cohorts.

  1. Validating the Malheur model for predicting ponderosa pine post-fire mortality using 24 fires in the Pacific Northwest, USA

    Science.gov (United States)

    Walter G. Thies; Douglas J. Westlind

    2012-01-01

    Fires, whether intentionally or accidentally set, commonly occur in western interior forests of the US. Following fire, managers need the ability to predict mortality of individual trees based on easily observed characteristics. Previously, a two-factor model using crown scorch and bole scorch proportions was developed with data from 3415 trees for predicting the...

  2. USING TURBIDITY DATA TO PREDICT SUSPENDED SEDIMENT CONCENTRATIONS: POSSIBILITIES, LIMITATIONS, AND PITFALLS

    Science.gov (United States)

    This talk will look at the relationships between turbidity and suspended sediment concentrations in a variety of geographic areas, geomorphic river types, and river sizes; and attempt to give guidance on using existing turbidity data to predict suspended sediment concentrations.

  3. Short-term Prediction of Coronary Heart Disease Mortality in the Czech Republic Based on Data from 1968-2014.

    Czech Academy of Sciences Publication Activity Database

    Reissigová, Jindra; Zvolský, M.

    2018-01-01

    Roč. 26, č. 1 (2018), s. 10-15 ISSN 1210-7778 Institutional support: RVO:67985807 Keywords : mortality * coronary heart diseases * short-term prediction * long-term prediction * national health registries Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Applied mathematics Impact factor: 0.682, year: 2016 https://cejph.szu.cz/artkey/cjp-201801-0002_short-term-prediction-of-coronary- heart -disease-mortality-in-the-czech-republic-based-on-data-from-1968-2014.php

  4. Using daily excessive concentration hours to explore the short-term mortality effects of ambient PM2.5 in Hong Kong

    International Nuclear Information System (INIS)

    Lin, Hualiang; Ma, Wenjun; Qiu, Hong; Wang, Xiaojie; Trevathan, Edwin; Yao, Zhenjiang; Dong, Guang-Hui; Vaughn, Michael G.; Qian, Zhengmin; Tian, Linwei

    2017-01-01

    We developed a novel indicator, daily excessive concentration hours (DECH), to explore the acute mortality impacts of ambient fine particulate matter pollution (PM 2.5 ) in Hong Kong. The DECH of PM 2.5 was calculated as daily concentration-hours >25 μg/m 3 . We applied a generalized additive models to quantify the association between DECH and mortality with adjustment for potential confounders. The results showed that the DECH was significantly associated with mortality. The excess mortality risk for an interquartile range (565 μg/m 3 *hours) increase in DECH of PM 2.5 was 1.65% (95% CI: 1.05%, 2.26%) for all natural mortality at lag 02 day, 2.01% (95% CI: 0.82%, 3.21%) for cardiovascular mortality at lag 03 days, and 1.41% (95% CI: 0.34%, 2.49%) for respiratory mortality at lag 2 day. The associations remained consistent after adjustment for gaseous air pollutants (daily mean concentration of SO 2 , NO 2 and O 3 ) and in alternative model specifications. When compared to the mortality burden of daily mean PM 2.5 , DECH was found to be a relatively conservative indicator. This study adds to the evidence by showing that daily excessive concentration hours of PM 2.5 might be a new predictor of mortality in Hong Kong. - Highlights: • A new indicator, daily excess concentration hours (DECH), was proposed in this study. • DECH of PM 2.5 was associated with cardiovascular mortality in Hong Kong. • DECH of PM 2.5 was associated with respiratory mortality in Hong Kong. - Excessive concentration hours of PM 2.5 , as one new indicator, is significantly associated with increased mortality in Hong Kong.

  5. A Risk Prediction Score for Kidney Failure or Mortality in Rhabdomyolysis

    Science.gov (United States)

    McMahon, Gearoid M.; Zeng, Xiaoxi; Waikar, Sushrut S.

    2016-01-01

    IMPORTANCE Rhabdomyolysis ranges in severity from asymptomatic elevations in creatine phosphokinase levels to a life-threatening disorder characterized by severe acute kidney injury requiring hemodialysis or continuous renal replacement therapy (RRT). OBJECTIVE To develop a risk prediction tool to identify patients at greatest risk of RRT or in-hospital mortality. DESIGN, SETTING, AND PARTICIPANTS Retrospective cohort study of 2371 patients admitted between January 1, 2000, and March 31, 2011, to 2 large teaching hospitals in Boston, Massachusetts, with creatine phosphokinase levels in excess of 5000 U/L within 3 days of admission. The derivation cohort consisted of 1397 patients from Massachusetts General Hospital, and the validation cohort comprised 974 patients from Brigham and Women’s Hospital. MAIN OUTCOMES AND MEASURES The composite of RRT or in-hospital mortality. RESULTS The causes and outcomes of rhabdomyolysis were similar between the derivation and validation cohorts. In total, the composite outcome occurred in 19.0% of patients (8.0% required RRT and 14.1% died during hospitalization). The highest rates of the composite outcome were from compartment syndrome (41.2%), sepsis (39.3%), and following cardiac arrest (58.5%). The lowest rates were from myositis (1.7%), exercise (3.2%), and seizures (6.0%). The independent predictors of the composite outcome were age, female sex, cause of rhabdomyolysis, and values of initial creatinine, creatine phosphokinase, phosphate, calcium, and bicarbonate. We developed a risk-prediction score from these variables in the derivation cohort and subsequently applied it in the validation cohort. The C statistic for the prediction model was 0.82 (95% CI, 0.80–0.85) in the derivation cohort and 0.83 (0.80–0.86) in the validation cohort. The Hosmer-Lemeshow P values were .14 and .28, respectively. In the validation cohort, among the patients with the lowest risk score (10), 61.2% died or needed RRT. CONCLUSIONS AND

  6. Prenatal maternal cortisol concentrations predict neurodevelopment in middle childhood.

    Science.gov (United States)

    Davis, Elysia Poggi; Head, Kevin; Buss, Claudia; Sandman, Curt A

    2017-01-01

    Glucocorticoids (cortisol in humans) are the end product of the hypothalamic-pituitary-adrenocortical (HPA) axis and are proposed as a key mechanism for programming fetal brain development. The present prospective longitudinal study evaluates the association between prenatal maternal cortisol concentrations and child neurodevelopment. Participants included a low risk sample of 91 mother-child pairs. Prenatal maternal plasma cortisol concentrations were measured at 19 and 31 gestational weeks. Brain development and cognitive functioning were assessed when children were 6-9 years of age. Structural magnetic resonance imaging scans were acquired and cortical thickness was determined. Child cognitive functioning was evaluated using standardized measures (Wechsler Intelligence Scale for Children IV and Expressive Vocabulary Test, Second Edition). Higher maternal cortisol concentrations during the third trimester were associated with greater child cortical thickness primarily in frontal regions. No significant associations were observed between prenatal maternal cortisol concentrations and child cortical thinning. Elevated third trimester maternal cortisol additionally was associated with enhanced child cognitive performance. Findings in this normative sample of typically developing children suggest that elevated maternal cortisol during late gestation exert lasting benefits for brain development and cognitive functioning 6-9 years later. The benefits of fetal exposure to higher maternal cortisol during the third trimester for child neurodevelopment are consistent with the role cortisol plays in maturation of the human fetus. It is plausible that more extreme elevations in maternal cortisol concentrations late in gestation, as well as exposure to pharmacological levels of synthetic glucocorticoids, may have neurotoxic effects on the developing fetal brain. Copyright © 2016. Published by Elsevier Ltd.

  7. Systemic inflammation predicts all-cause mortality: a glasgow inflammation outcome study.

    Directory of Open Access Journals (Sweden)

    Michael J Proctor

    Full Text Available Markers of the systemic inflammatory response, including C-reactive protein and albumin (combined to form the modified Glasgow Prognostic Score, as well as neutrophil, lymphocyte and platelet counts have been shown to be prognostic of survival in patients with cancer. The aim of the present study was to examine the prognostic relationship between these markers of the systemic inflammatory response and all-cause, cancer, cardiovascular and cerebrovascular mortality in a large incidentally sampled cohort.Patients (n = 160 481 who had an incidental blood sample taken between 2000 and 2008 were studied for the prognostic value of C-reactive protein (>10mg/l, albumin (>35mg/l, neutrophil (>7.5×109/l lymphocyte and platelet counts. Also, patients (n = 52 091 sampled following the introduction of high sensitivity C-reactive protein (>3mg/l measurements were studied. A combination of these markers, to make cumulative inflammation-based scores, were investigated.In all patients (n = 160 481 C-reactive protein (>10mg/l (HR 2.71, p35mg/l (HR 3.68, p3mg/l (n = 52 091. A combination of high sensitivity C-reactive protein (>3mg/l, albumin and neutrophil count predicted all-cause (HR 7.37, p<0.001, AUC 0.723, cancer (HR 9.32, p<0.001, AUC 0.731, cardiovascular (HR 4.03, p<0.001, AUC 0.650 and cerebrovascular (HR 3.10, p<0.001, AUC 0.623 mortality.The results of the present study showed that an inflammation-based prognostic score, combining high sensitivity C-reactive protein, albumin and neutrophil count is prognostic of all-cause mortality.

  8. Total and cause-specific mortality by moderately and markedly increased ferritin concentrations

    DEFF Research Database (Denmark)

    Ellervik, Christina; Marott, Jacob Louis; Tybjærg-Hansen, Anne

    2014-01-01

    . Stepwise increasing concentrations of ferritin were associated with a stepwise increased risk of premature death overall (log rank, P = 2 × 10(-22)), with median survival of 55 years at ferritin concentrations ≥600 μg/L, 72 years at 400-599 μg/L, 76 years at 200-399 μg/L, and 79 years at ferritin

  9. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality

    DEFF Research Database (Denmark)

    (Tybjaerg-Hansen, A.) The Fibrinogen Studies Collaboration.The Copenhagen City Heart Study; Tybjærg-Hansen, Anne

    2009-01-01

    CONTEXT: Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein-like particle, may be associated with risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationship of Lp(a) concentration with risk of major vascular...

  10. Acute exacerbation of idiopathic pulmonary fibrosis: high-resolution CT scores predict mortality

    International Nuclear Information System (INIS)

    Fujimoto, Kiminori; Taniguchi, Hiroyuki; Kondoh, Yasuhiro; Kataoka, Kensuke; Johkoh, Takeshi; Ichikado, Kazuya; Sumikawa, Hiromitsu; Ogura, Takashi; Endo, Takahiro; Kawaguchi, Atsushi; Mueller, Nestor L.

    2012-01-01

    To determine high-resolution computed tomography (HRCT) findings helpful in predicting mortality in patients with acute exacerbation of idiopathic pulmonary fibrosis (AEx-IPF). Sixty patients with diagnosis of AEx-IPF were reviewed retrospectively. Two groups (two observers each) independently evaluated pattern, distribution, and extent of HRCT findings at presentation and calculated an HRCT score at AEx based on normal attenuation areas and extent of abnormalities, such as areas of ground-glass attenuation and/or consolidation with or without traction bronchiectasis or bronchiolectasis and areas of honeycombing. The correlation between the clinical data including the HRCT score and mortality (cause-specific survival) was evaluated using the univariate and multivariate Cox-regression analyses. Serum KL-6 level, PaCO 2 , and the HRCT score were statistically significant predictors on univariate analysis. Multivariate analysis revealed that the HRCT score was an independently significant predictor of outcome (hazard ratio, 1.13; 95% confidence interval, 1.06-1.19, P = 0.0002). The area under receiver operating characteristics curve for the HRCT score was statistically significant in the classification of survivors or nonsurvivors (0.944; P < 0.0001). Survival in patients with HRCT score ≥245 was worse than those with lower score (log-rank test, P < 0.0001). The HRCT score at AEx is independently related to prognosis in patients with AEx-IPF. (orig.)

  11. Early warning score independently predicts adverse outcome and mortality in patients with acute pancreatitis.

    Science.gov (United States)

    Jones, Michael J; Neal, Christopher P; Ngu, Wee Sing; Dennison, Ashley R; Garcea, Giuseppe

    2017-08-01

    The aim of this study was to compare the prognostic value of established scoring systems with early warning scores in a large cohort of patients with acute pancreatitis. In patients presenting with acute pancreatitis, age, sex, American Society of Anaesthesiologists (ASA) grade, Modified Glasgow Score, Ranson criteria, APACHE II scores and early warning score (EWS) were recorded for the first 72 h following admission. These variables were compared between survivors and non-survivors, between patients with mild/moderate and severe pancreatitis (based on the 2012 Atlanta Classification) and between patients with a favourable or adverse outcome. A total of 629 patients were identified. EWS was the best predictor of adverse outcome amongst all of the assessed variables (area under curve (AUC) values 0.81, 0.84 and 0.83 for days 1, 2 and 3, respectively) and was the most accurate predictor of mortality on both days 2 and 3 (AUC values of 0.88 and 0.89, respectively). Multivariable analysis revealed that an EWS ≥2 was independently associated with severity of pancreatitis, adverse outcome and mortality. This study confirms the usefulness of EWS in predicting the outcome of acute pancreatitis. It should become the mainstay of risk stratification in patients with acute pancreatitis.

  12. Circulating Biologically Active Adrenomedullin (bio-ADM) Predicts Hemodynamic Support Requirement and Mortality During Sepsis.

    Science.gov (United States)

    Caironi, Pietro; Latini, Roberto; Struck, Joachim; Hartmann, Oliver; Bergmann, Andreas; Maggio, Giuseppe; Cavana, Marco; Tognoni, Gianni; Pesenti, Antonio; Gattinoni, Luciano; Masson, Serge

    2017-08-01

    The biological role of adrenomedullin (ADM), a hormone involved in hemodynamic homeostasis, is controversial in sepsis because administration of either the peptide or an antibody against it may be beneficial. Plasma biologically active ADM (bio-ADM) was assessed on days 1, 2, and 7 after randomization of 956 patients with sepsis or septic shock to albumin or crystalloids for fluid resuscitation in the multicenter Albumin Italian Outcome Sepsis trial. We tested the association of bio-ADM and its time-dependent variation with fluid therapy, vasopressor administration, organ failures, and mortality. Plasma bio-ADM on day 1 (median [Q1-Q3], 110 [59-198] pg/mL) was higher in patients with septic shock, associated with 90-day mortality, multiple organ failures and the average extent of hemodynamic support therapy (fluids and vasopressors), and serum lactate time course over the first week. Moreover, it predicted incident cardiovascular dysfunction in patients without shock at enrollment (OR [95% CI], 1.9 [1.4-2.5]; P sepsis, the circulating, biologically active form of ADM may help individualizing hemodynamic support therapy, while avoiding harmful effects. Its possible pathophysiologic role makes bio-ADM a potential candidate for future targeted therapies. ClinicalTrials.gov; No.: NCT00707122. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  13. Acute exacerbation of idiopathic pulmonary fibrosis: high-resolution CT scores predict mortality

    Energy Technology Data Exchange (ETDEWEB)

    Fujimoto, Kiminori [Kurume University School of Medicine, and Center for Diagnostic Imaging, Kurume University Hospital, Department of Radiology, Kurume, Fukuoka (Japan); Taniguchi, Hiroyuki; Kondoh, Yasuhiro; Kataoka, Kensuke [Tosei General Hospital, Department of Respiratory Medicine and Allergy, Seto, Aichi (Japan); Johkoh, Takeshi [Kinki Central Hospital of Mutual Aid Association of Public School Teachers, Department of Radiology, Itami (Japan); Ichikado, Kazuya [Saiseikai Kumamoto Hospital, Division of Respiratory Medicine, Kumamoto (Japan); Sumikawa, Hiromitsu [Osaka University Graduate School of Medicine, Department of Radiology, Suita, Osaka (Japan); Ogura, Takashi; Endo, Takahiro [Kanagawa Cardiovascular and Respiratory Center, Department of Respiratory Medicine, Yokohama, Kanagawa (Japan); Kawaguchi, Atsushi [Kurume University School of Medicine, Biostatistics Center, Kurume (Japan); Mueller, Nestor L. [University of British Columbia and Vancouver General Hospital, Department of Radiology, Vancouver, B.C. (Canada)

    2012-01-15

    To determine high-resolution computed tomography (HRCT) findings helpful in predicting mortality in patients with acute exacerbation of idiopathic pulmonary fibrosis (AEx-IPF). Sixty patients with diagnosis of AEx-IPF were reviewed retrospectively. Two groups (two observers each) independently evaluated pattern, distribution, and extent of HRCT findings at presentation and calculated an HRCT score at AEx based on normal attenuation areas and extent of abnormalities, such as areas of ground-glass attenuation and/or consolidation with or without traction bronchiectasis or bronchiolectasis and areas of honeycombing. The correlation between the clinical data including the HRCT score and mortality (cause-specific survival) was evaluated using the univariate and multivariate Cox-regression analyses. Serum KL-6 level, PaCO{sub 2}, and the HRCT score were statistically significant predictors on univariate analysis. Multivariate analysis revealed that the HRCT score was an independently significant predictor of outcome (hazard ratio, 1.13; 95% confidence interval, 1.06-1.19, P = 0.0002). The area under receiver operating characteristics curve for the HRCT score was statistically significant in the classification of survivors or nonsurvivors (0.944; P < 0.0001). Survival in patients with HRCT score {>=}245 was worse than those with lower score (log-rank test, P < 0.0001). The HRCT score at AEx is independently related to prognosis in patients with AEx-IPF. (orig.)

  14. Association between mortality and replacement solution bicarbonate concentration in continuous renal replacement therapy: A propensity-matched cohort study.

    Directory of Open Access Journals (Sweden)

    Kianoush Kashani

    Full Text Available Given the known deleterious effects seen with bicarbonate supplementation for acidemia, we hypothesized that utilizing high bicarbonate concentration replacement solution in continuous venovenous hemofiltration (CVVH would be independently associated with higher mortality.In a propensity score-matched historical cohort study conducted at a single tertiary care center from December 9, 2006, through December 31, 2009, a total of 287consecutive adult critically ill patients with Stage III acute kidney injury (AKI requiring CVVH were enrolled. We excluded patients on maintenance dialysis, those who received other modalities of continuous renal replacement therapies, and patients that received a mixed of 22 and 32 mEq/L bicarbonate solution pre- and post-filter. The primary outcome was in-hospital and 90-day mortality rates.Among enrollees, 68 were used 32 mEq/L bicarbonate solution, and 219 received 22mEq/L bicarbonate solution for CVVH. Patients on 32 mEq/L bicarbonate solution were more often non-surgical, had lower pH and bicarbonate level but had higher blood potassium and phosphorus levels in comparison with those on 22 mEq/L bicarbonate solution. After adjustment for the baseline characteristics, the use of 32 bicarbonate solution was significantly associated with increased in-hospital (HR = 1.94; 95% CI 1.02-3.79 and 90-day mortality (HR = 1.50; 95% CI 1.03-2.14. There was a significant increase in the hospital (p = .03 and 90-day (p = .04 mortality between the 22 vs. 32 mEq/L bicarbonate solution groups following propensity matching.Our data showed there is a strong association between using high bicarbonate solution and mortality independent of severity of illness and comorbid conditions. These findings need to be evaluated further in prospective studies.

  15. Calculating flux to predict future cave radon concentrations

    Czech Academy of Sciences Publication Activity Database

    Rowberry, Matthew David; Martí, Xavier; Frontera, C.; Van De Wiel, M.J.; Briestenský, Miloš

    2016-01-01

    Roč. 157, JUN (2016), 16-26 ISSN 0265-931X R&D Projects: GA MŠk LM2010008 Institutional support: RVO:67985891 ; RVO:68378271 Keywords : cave radon concentration * cave radon flux * cave ventilation * radioactive decay * fault slip * numerical modelling Subject RIV: DC - Siesmology, Volcanology, Earth Structure; BG - Nuclear, Atomic and Molecular Physics, Colliders (FZU-D) Impact factor: 2.310, year: 2016

  16. Missing Value Imputation Improves Mortality Risk Prediction Following Cardiac Surgery: An Investigation of an Australian Patient Cohort.

    Science.gov (United States)

    Karim, Md Nazmul; Reid, Christopher M; Tran, Lavinia; Cochrane, Andrew; Billah, Baki

    2017-03-01

    The aim of this study was to evaluate the impact of missing values on the prediction performance of the model predicting 30-day mortality following cardiac surgery as an example. Information from 83,309 eligible patients, who underwent cardiac surgery, recorded in the Australia and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) database registry between 2001 and 2014, was used. An existing 30-day mortality risk prediction model developed from ANZSCTS database was re-estimated using the complete cases (CC) analysis and using multiple imputation (MI) analysis. Agreement between the risks generated by the CC and MI analysis approaches was assessed by the Bland-Altman method. Performances of the two models were compared. One or more missing predictor variables were present in 15.8% of the patients in the dataset. The Bland-Altman plot demonstrated significant disagreement between the risk scores (prisk of mortality. Compared to CC analysis, MI analysis resulted in an average of 8.5% decrease in standard error, a measure of uncertainty. The MI model provided better prediction of mortality risk (observed: 2.69%; MI: 2.63% versus CC: 2.37%, Pvalues improved the 30-day mortality risk prediction following cardiac surgery. Copyright © 2016 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

  17. The prediction of in-hospital mortality by mid-upper arm circumference

    DEFF Research Database (Denmark)

    Opio, Martin Otyek; Namujwiga, Teopista; Nakitende, Imaculate

    2018-01-01

    There are few reports of the association of nutritional status with in-hospital mortality of acutely ill medical patients in sub-Saharan Africa. This is a prospective observational study comparing the predictive value of mid-upper arm circumference (MUAC) of 899 acutely ill medical patients...... patients in a resource-poor hospital in sub-Saharan Africa....... admitted to a resource-poor sub-Saharan hospital with mental alertness, mobility and vital signs. Mid-upper arm circumference ranged from 15 cm to 42 cm, and 12 (24%) of the 50 patients with a MUAC less than 20 cm died (OR 4.84, 95% CI 2.23-10.37). Of the 237 patients with a MUAC more than 28 cm only six...

  18. Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

    Directory of Open Access Journals (Sweden)

    Eduardo Arrais Rocha

    2015-01-01

    Full Text Available Abstract Background: 30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes. Objective: This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx at different stages of cardiac resynchronization therapy (CRT. Methods: Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves. Results: The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD, ejection fraction < 25% and use of high doses of diuretics (HDD increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping. Conclusion: We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.

  19. Sarcopenia predicts readmission and mortality in elderly patients in acute care wards: a prospective study.

    Science.gov (United States)

    Yang, Ming; Hu, Xiaoyi; Wang, Haozhong; Zhang, Lei; Hao, Qiukui; Dong, Birong

    2017-04-01

    The aim of this study is to assess the prevalence of sarcopenia and investigate the associations between sarcopenia and long-term mortality and readmission in a population of elderly inpatients in acute care wards. We conducted a prospective observational study in the acute care wards of a teaching hospital in western China. The muscle mass was estimated according to a previously validated anthropometric equation. Handgrip strength was measured with a handheld dynamometer, and physical performance was measured via a 4 m walking test. Sarcopenia was defined according to the recommended diagnostic algorithm of the Asia Working Group for Sarcopenia. The survival status and readmission information were obtained via telephone interviews at 12, 24, and 36 months during the 3 year follow-up period following the baseline investigation. Two hundred and eighty-eight participants (mean age: 81.1 ± 6.6 years) were included. Forty-nine participants (17.0%) were identified as having sarcopenia. This condition was similar in men and women (16.9% vs. 17.5%, respectively, P = 0.915). During the 3 year follow-up period, 49 men (22.7%) and 9 women (16.4%) died (P = 0.307). The mortality of sarcopenic participants was significantly increased compared with non-sarcopenic participants (40.8% vs. 17.1%, respectively, P sarcopenia was an independent predictor of 3 year mortality (adjusted hazard ratio: 2.49; 95% confidential interval: 1.25-4.95) and readmission (adjusted hazard ratio: 1.81; 95% confidential interval: 1.17-2.80). Sarcopenia, which is evaluated by a combination of anthropometric measures, gait speed, and handgrip strength, is valuable to predict hospital readmission and long-term mortality in elderly patients in acute care wards. © 2016 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of the Society on Sarcopenia, Cachexia and Wasting Disorders.

  20. Transthyretin Concentrations in Acute Stroke Patients Predict Convalescent Rehabilitation.

    Science.gov (United States)

    Isono, Naofumi; Imamura, Yuki; Ohmura, Keiko; Ueda, Norihide; Kawabata, Shinji; Furuse, Motomasa; Kuroiwa, Toshihiko

    2017-06-01

    For stroke patients, intensive nutritional management is an important and effective component of inpatient rehabilitation. Accordingly, acute care hospitals must detect and prevent malnutrition at an early stage. Blood transthyretin levels are widely used as a nutritional monitoring index in critically ill patients. Here, we had analyzed the relationship between the transthyretin levels during the acute phase and Functional Independence Measure in stroke patients undergoing convalescent rehabilitation. We investigated 117 patients who were admitted to our hospital with acute ischemic or hemorrhagic stroke from February 2013 to October 2015 and subsequently transferred to convalescent hospitals after receiving acute treatment. Transthyretin concentrations were evaluated at 3 time points as follows: at admission, and 5 and 10 days after admission. After categorizing patients into 3 groups according to the minimum transthyretin level, we analyzed the association between transthyretin and Functional Independence Measure. In our patients, transthyretin levels decreased during the first 5 days after admission and recovered slightly during the subsequent 5 days. Notably, Functional Independence Measure efficiency was significantly associated with the decrease in transthyretin levels during the 5 days after admission. Patients with lower transthyretin levels had poorer Functional Independence Measure outcomes and tended not to be discharged to their own homes. A minimal transthyretin concentration (stroke patients undergoing convalescent rehabilitation. In particular, an early decrease in transthyretin levels suggests restricted rehabilitation efficiency. Accordingly, transthyretin levels should be monitored in acute stroke patients to indicate mid-term rehabilitation prospects. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  1. Predicting arsenic concentrations in porewaters of buried uranium mill tailings

    Energy Technology Data Exchange (ETDEWEB)

    Langmuir, D.; Mahoney, J.; MacDonald, A.; Rowson, J.

    1999-10-01

    The proposed JEB Tailings Management Facility (TMF) to be emplaced below the groundwater table in northern Saskatchewan, Canada, will contain uranium mill tailings from McClean Lake, Midwest and Cigar Lake ore bodies, which are high in arsenic (up to 10%) and nickel (up to 5%). A serious concern is the possibility that high arsenic and nickel concentrations may be released from the buried tailings, contaminating adjacent groundwaters and a nearby lake. Laboratory tests and geochemical modeling were performed to examine ways to reduce the arsenic and nickel concentrations in TMF porewaters so as to minimize such contamination from tailings buried for 50 years and longer. The tests were designed to mimic conditions in the mill neutralization circuit (3 hr tests at 25 C), and in the TMF after burial (5--49 day aging tests). The aging tests were run at 50, 25 and 4 C (the temperature in the TMF). In order to optimize the removal of arsenic by adsorption and precipitation, ferric sulfate was added to tailings raffinates having Fe/As ratios of less than 3--5. The acid raffinates were then neutralized by addition of slaked lime to nominal pH values of 7, 8, or 9. Analysis and modeling of the test results showed that with slaked lime addition to acid tailings raffinates, relatively amorphous scorodite (ferric arsenate) precipitates near pH 1, and is the dominant form of arsenate in slake limed tailings solids except those high in Ni and As and low in Fe, in which cabrerite-annabergite (Ni, Mg, Fe(II) arsenate) may also precipitate near pH 5--6. In addition to the arsenate precipitates, smaller amounts of arsenate are also adsorbed onto tailings solids. The aging tests showed that after burial of the tailings, arsenic concentrations may increase with time from the breakdown of the arsenate phases (chiefly scorodite). However, the tests indicate that the rate of change decreases and approaches zero after 72 hrs at 25 C, and may equal zero at all times in the TMF at 4 C

  2. Prediction on long-term mean and mean square pollutant concentrations in an urban atmosphere

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, S; Lamb, R G; Seinfeld, J H

    1976-01-01

    The general problem of predicting long-term average (say yearly) pollutant concentrations in an urban atmosphere is formulated. The pollutant concentration can be viewed as a random process, the complete description of which requires knowledge of its probability density function, which is unknown. The mean concentration is the first moment of the concentration distribution, and at present there exist a number of models for predicting the long-term mean concentration of an inert pollutant. The second moment, or mean square concentration, indicates additional features of the distribution, such as the level of fluctuations about the mean. In the paper a model proposed by Lamb for the long-term mean concentration is reviewed, and a new model for prediction of the long-term mean square concentration of an inert air pollutant is derived. The properties and uses of the model are discussed, and the equations defining the model are presented in a form for direct application to an urban area.

  3. Risk factors predicting mortality in patients with lung abscess in a public tertiary care center in Karachi, Pakistan.

    Science.gov (United States)

    Ghazal, Shaista; Kumar, Ashok; Shrestha, Binav; Sajid, Sana; Malik, Maria; Rizvi, Nadeen

    2013-01-01

    Lung abscess is a commonly encountered entity in South-East Asia but not much data regarding its outcome is available. The objective of this study was to identify the factors associated with increased mortality in patients diagnosed with lung abscess in a tertiary care center of Karachi, Pakistan. A retrospective case analysis was performed via hospital records, on patients admitted with lung abscess between January 2009 and January 2011 at the largest state-owned tertiary care centre in Karachi, Pakistan. Out of the 41 patients hospitalized, 17 could not survive and were evaluated for clinical, radiological and microbiological factors to determine association with heightened mortality. Mortality due to lung abscess stood at 41.4% (17 of 41 cases). Adult male patients were found to have higher mortality with 13 out of 17 (43%) dead patients being male. A majority (21/41, 51.2%) of the cases belonged to the 41-60 year old age group. Highest mortality was seen in patients200 mg/dL (56%) succumb to disease. Patients with a positive history of smoking, diabetes mellitus, and alcohol intake expressed mortality rates of 44%, 56%, and 50% respectively; while 29.4% of the mortalities were positive for Pseudomonas aeruginosa on sputum culture. A significant association was found with elevated mortality and low haemoglobin levels at time of admission; mortality was 58% (p=0.005) in patients with Hb less than or equal to 10 mg/dL. The risk factors involved with heightened mortality included male gender and history of smoking, diabetes and alcohol intake. High blood sugar levels and detection of Pseudomonas aeruginosa on sputum cultures were also implicated. Anemia (Hb level less than or equal to 10 mg/dl) was statistically significant predictive factor for increased mortality.

  4. Gas Concentration Prediction Based on the Measured Data of a Coal Mine Rescue Robot

    Directory of Open Access Journals (Sweden)

    Xiliang Ma

    2016-01-01

    Full Text Available The coal mine environment is complex and dangerous after gas accident; then a timely and effective rescue and relief work is necessary. Hence prediction of gas concentration in front of coal mine rescue robot is an important significance to ensure that the coal mine rescue robot carries out the exploration and search and rescue mission. In this paper, a gray neural network is proposed to predict the gas concentration 10 meters in front of the coal mine rescue robot based on the gas concentration, temperature, and wind speed of the current position and 1 meter in front. Subsequently the quantum genetic algorithm optimization gray neural network parameters of the gas concentration prediction method are proposed to get more accurate prediction of the gas concentration in the roadway. Experimental results show that a gray neural network optimized by the quantum genetic algorithm is more accurate for predicting the gas concentration. The overall prediction error is 9.12%, and the largest forecasting error is 11.36%; compared with gray neural network, the gas concentration prediction error increases by 55.23%. This means that the proposed method can better allow the coal mine rescue robot to accurately predict the gas concentration in the coal mine roadway.

  5. The predictive value of leucocyte progression for one-week mortality on acutely admitted medical patients to the emergency department

    DEFF Research Database (Denmark)

    Brabrand, Mikkel; Soltau, Matilde Røgilds

    2018-01-01

    female. Using logistic regression, we found significantly lower one-week mortality with falling leucocyte count progression, even when controlling for confounders. A decreasing leucocyte count had a sensitivity for one-week mortality of 65%, specificity of 62%, positive predictive value of 4......%, and negative predictive value of 99%. Difference in admission to the intensive care unit was non-significant between the three groups. Difference in length of stay was significant, but with one day difference, the clinical significance is questionable. CONCLUSION: Leucocyte count progression is not sensitive...... enough to predict one-week mortality, nor specific enough to discount it. It is important for physicians to be aware of this to avoid faulty assessments based on imprecise assumptions....

  6. Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration-based prediction model.

    Science.gov (United States)

    Tanoshima, Reo; Bournissen, Facundo Garcia; Tanigawara, Yusuke; Kristensen, Judith H; Taddio, Anna; Ilett, Kenneth F; Begg, Evan J; Wallach, Izhar; Ito, Shinya

    2014-10-01

    Population pharmacokinetic (pop PK) modelling can be used for PK assessment of drugs in breast milk. However, complex mechanistic modelling of a parent and an active metabolite using both blood and milk samples is challenging. We aimed to develop a simple predictive pop PK model for milk concentration-time profiles of a parent and a metabolite, using data on fluoxetine (FX) and its active metabolite, norfluoxetine (NFX), in milk. Using a previously published data set of drug concentrations in milk from 25 women treated with FX, a pop PK model predictive of milk concentration-time profiles of FX and NFX was developed. Simulation was performed with the model to generate FX and NFX concentration-time profiles in milk of 1000 mothers. This milk concentration-based pop PK model was compared with the previously validated plasma/milk concentration-based pop PK model of FX. Milk FX and NFX concentration-time profiles were described reasonably well by a one compartment model with a FX-to-NFX conversion coefficient. Median values of the simulated relative infant dose on a weight basis (sRID: weight-adjusted daily doses of FX and NFX through breastmilk to the infant, expressed as a fraction of therapeutic FX daily dose per body weight) were 0.028 for FX and 0.029 for NFX. The FX sRID estimates were consistent with those of the plasma/milk-based pop PK model. A predictive pop PK model based on only milk concentrations can be developed for simultaneous estimation of milk concentration-time profiles of a parent (FX) and an active metabolite (NFX). © 2014 The British Pharmacological Society.

  7. Left ventricular ejection fraction to predict early mortality in patients with non-ST-segment elevation acute coronary syndromes.

    Science.gov (United States)

    Bosch, Xavier; Théroux, Pierre

    2005-08-01

    Improvement in risk stratification of patients with non-ST-segment elevation acute coronary syndrome (ACS) is a gateway to a more judicious treatment. This study examines whether the routine determination of left ventricular ejection fraction (EF) adds significant prognostic information to currently recommended stratifiers. Several predictors of inhospital mortality were prospectively characterized in a registry study of 1104 consecutive patients, for whom an EF was determined, who were admitted for an ACS. Multiple regression models were constructed using currently recommended clinical, electrocardiographic, and blood marker stratifiers, and values of EF were incorporated into the models. Age, ST-segment shifts, elevation of cardiac markers, and the Thrombolysis in Myocardial Infarction (TIMI) risk score all predicted mortality (P model improved the prediction of mortality (C statistic 0.73 vs 0.67). The odds of death increased by a factor of 1.042 for each 1% decrement in EF. By receiver operating curves, an EF cutoff of 48% provided the best predictive value. Mortality rates were 3.3 times higher within each TIMI risk score stratum in patients with an EF of 48% or lower as compared with those with higher. The TIMI risk score predicts inhospital mortality in a broad population of patients with ACS. The further consideration of EF adds significant prognostic information.

  8. Application of XGBoost algorithm in hourly PM2.5 concentration prediction

    Science.gov (United States)

    Pan, Bingyue

    2018-02-01

    In view of prediction techniques of hourly PM2.5 concentration in China, this paper applied the XGBoost(Extreme Gradient Boosting) algorithm to predict hourly PM2.5 concentration. The monitoring data of air quality in Tianjin city was analyzed by using XGBoost algorithm. The prediction performance of the XGBoost method is evaluated by comparing observed and predicted PM2.5 concentration using three measures of forecast accuracy. The XGBoost method is also compared with the random forest algorithm, multiple linear regression, decision tree regression and support vector machines for regression models using computational results. The results demonstrate that the XGBoost algorithm outperforms other data mining methods.

  9. Cerebrospinal fluid cytokine profiles predict risk of early mortality and immune reconstitution inflammatory syndrome in HIV-associated cryptococcal meningitis.

    Directory of Open Access Journals (Sweden)

    Joseph N Jarvis

    2015-04-01

    Full Text Available Understanding the host immune response during cryptococcal meningitis (CM is of critical importance for the development of immunomodulatory therapies. We profiled the cerebrospinal fluid (CSF immune-response in ninety patients with HIV-associated CM, and examined associations between immune phenotype and clinical outcome. CSF cytokine, chemokine, and macrophage activation marker concentrations were assayed at disease presentation, and associations between these parameters and microbiological and clinical outcomes were examined using principal component analysis (PCA. PCA demonstrated a co-correlated CSF cytokine and chemokine response consisting primarily of Th1, Th2, and Th17-type cytokines. The presence of this CSF cytokine response was associated with evidence of increased macrophage activation, more rapid clearance of Cryptococci from CSF, and survival at 2 weeks. The key components of this protective immune-response were interleukin (IL-6 and interferon-γ, IL-4, IL-10 and IL-17 levels also made a modest positive contribution to the PC1 score. A second component of co-correlated chemokines was identified by PCA, consisting primarily of monocyte chemotactic protein-1 (MCP-1 and macrophage inflammatory protein-1α (MIP-1α. High CSF chemokine concentrations were associated with low peripheral CD4 cell counts and CSF lymphocyte counts and were predictive of immune reconstitution inflammatory syndrome (IRIS. In conclusion CSF cytokine and chemokine profiles predict risk of early mortality and IRIS in HIV-associated CM. We speculate that the presence of even minimal Cryptococcus-specific Th1-type CD4+ T-cell responses lead to increased recruitment of circulating lymphocytes and monocytes into the central nervous system (CNS, more effective activation of CNS macrophages and microglial cells, and faster organism clearance; while high CNS chemokine levels may predispose to over recruitment or inappropriate recruitment of immune cells to the CNS and

  10. Food chain model to predict westslope cutthroat trout ovary selenium concentrations from water concentrations in the Elk Valley, BC

    International Nuclear Information System (INIS)

    Orr, P.; Wiramanaden, C.; Franklin, W.; Fraser, C.

    2010-01-01

    The 5 coal mines operated by Teck Coal Ltd. in British Columbia's Elk River watershed release selenium during weathering of mine waste rock. Since 1966, several field studies have been conducted in which selenium concentrations in biota were measured. They revealed that tissue concentrations are higher in aquatic biota sampled in lentic compared to lotic habitats of the watershed with similar water selenium concentrations. Two food chain models were developed based on the available data. The models described dietary selenium accumulation in the ovaries of lotic versus lentic westslope cutthroat trout (WCT), a valued aquatic resource in the Elk River system. The following 3 trophic transfer relationships were characterized for each model: (1) water to base of the food web, (2) base of the food web to benthic invertebrates, and (3) benthic invertebrates to WCT ovaries. The lotic and lentic models combined the resulting equations for each trophic transfer relationships to predict WCT ovary concentrations from water concentrations. The models were in very good agreement with the available data, despite fish movement and the fact that composite benthic invertebrate sample data were only an approximation of the feeding preferences of individual fish. Based on the observed rates of increase in water selenium concentrations throughout the watershed, the models predicted very small/slow increases in WCT ovary concentrations with time.

  11. Heterogeneous postsurgical data analytics for predictive modeling of mortality risks in intensive care units.

    Science.gov (United States)

    Yun Chen; Hui Yang

    2014-01-01

    The rapid advancements of biomedical instrumentation and healthcare technology have resulted in data-rich environments in hospitals. However, the meaningful information extracted from rich datasets is limited. There is a dire need to go beyond current medical practices, and develop data-driven methods and tools that will enable and help (i) the handling of big data, (ii) the extraction of data-driven knowledge, (iii) the exploitation of acquired knowledge for optimizing clinical decisions. This present study focuses on the prediction of mortality rates in Intensive Care Units (ICU) using patient-specific healthcare recordings. It is worth mentioning that postsurgical monitoring in ICU leads to massive datasets with unique properties, e.g., variable heterogeneity, patient heterogeneity, and time asyncronization. To cope with the challenges in ICU datasets, we developed the postsurgical decision support system with a series of analytical tools, including data categorization, data pre-processing, feature extraction, feature selection, and predictive modeling. Experimental results show that the proposed data-driven methodology outperforms traditional approaches and yields better results based on the evaluation of real-world ICU data from 4000 subjects in the database. This research shows great potentials for the use of data-driven analytics to improve the quality of healthcare services.

  12. Prediction of hospital mortality by changes in the estimated glomerular filtration rate (eGFR).

    LENUS (Irish Health Repository)

    Berzan, E

    2015-03-01

    Deterioration of physiological or laboratory variables may provide important prognostic information. We have studied whether a change in estimated glomerular filtration rate (eGFR) value calculated using the (Modification of Diet in Renal Disease (MDRD) formula) over the hospital admission, would have predictive value. An analysis was performed on all emergency medical hospital episodes (N = 61964) admitted between 1 January 2002 and 31 December 2011. A stepwise logistic regression model examined the relationship between mortality and change in renal function from admission to discharge. The fully adjusted Odds Ratios (OR) for 5 classes of GFR deterioration showed a stepwise increased risk of 30-day death with OR\\'s of 1.42 (95% CI: 1.20, 1.68), 1.59 (1.27, 1.99), 2.71 (2.24, 3.27), 5.56 (4.54, 6.81) and 11.9 (9.0, 15.6) respectively. The change in eGFR during a clinical episode, following an emergency medical admission, powerfully predicts the outcome.

  13. Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks.

    Science.gov (United States)

    Coiera, Enrico; Wang, Ying; Magrabi, Farah; Concha, Oscar Perez; Gallego, Blanca; Runciman, William

    2014-05-21

    Current prognostic models factor in patient and disease specific variables but do not consider cumulative risks of hospitalization over time. We developed risk models of the likelihood of death associated with cumulative exposure to hospitalization, based on time-varying risks of hospitalization over any given day, as well as day of the week. Model performance was evaluated alone, and in combination with simple disease-specific models. Patients admitted between 2000 and 2006 from 501 public and private hospitals in NSW, Australia were used for training and 2007 data for evaluation. The impact of hospital care delivered over different days of the week and or times of the day was modeled by separating hospitalization risk into 21 separate time periods (morning, day, night across the days of the week). Three models were developed to predict death up to 7-days post-discharge: 1/a simple background risk model using age, gender; 2/a time-varying risk model for exposure to hospitalization (admission time, days in hospital); 3/disease specific models (Charlson co-morbidity index, DRG). Combining these three generated a full model. Models were evaluated by accuracy, AUC, Akaike and Bayesian information criteria. There was a clear diurnal rhythm to hospital mortality in the data set, peaking in the evening, as well as the well-known 'weekend-effect' where mortality peaks with weekend admissions. Individual models had modest performance on the test data set (AUC 0.71, 0.79 and 0.79 respectively). The combined model which included time-varying risk however yielded an average AUC of 0.92. This model performed best for stays up to 7-days (93% of admissions), peaking at days 3 to 5 (AUC 0.94). Risks of hospitalization vary not just with the day of the week but also time of the day, and can be used to make predictions about the cumulative risk of death associated with an individual's hospitalization. Combining disease specific models with such time varying- estimates appears to

  14. Predictive values of urine paraquat concentration, dose of poison, arterial blood lactate and APACHE II score in the prognosis of patients with acute paraquat poisoning.

    Science.gov (United States)

    Liu, Xiao-Wei; Ma, Tao; Li, Lu-Lu; Qu, Bo; Liu, Zhi

    2017-07-01

    The present study investigated the predictive values of urine paraquat (PQ) concentration, dose of poison, arterial blood lactate and Acute Physiology and Chronic Health Evaluation (APACHE) II score in the prognosis of patients with acute PQ poisoning. A total of 194 patients with acute PQ poisoning, hospitalized between April 2012 and January 2014 at the First Affiliated Hospital of P.R. China Medical University (Shenyang, China), were selected and divided into survival and mortality groups. Logistic regression analysis, receiver operator characteristic (ROC) curve analysis and Kaplan-Meier curve were applied to evaluate the values of urine paraquat (PQ) concentration, dose of poison, arterial blood lactate and (APACHE) II score for predicting the prognosis of patients with acute PQ poisoning. Initial urine PQ concentration (C0), dose of poison, arterial blood lactate and APACHE II score of patients in the mortality group were significantly higher compared with the survival group (all Ppoison and arterial blood lactate correlated with mortality risk of acute PQ poisoning (all Ppoison, arterial blood lactate and APACHE II score in predicting the mortality of patients within 28 days were 0.921, 0.887, 0.808 and 0.648, respectively. The AUC of C0 for predicting early and delayed mortality were 0.890 and 0.764, respectively. The AUC values of urine paraquat concentration the day after poisoning (Csec) and the rebound rate of urine paraquat concentration in predicting the mortality of patients within 28 days were 0.919 and 0.805, respectively. The 28-day survival rate of patients with C0 ≤32.2 µg/ml (42/71; 59.2%) was significantly higher when compared with patients with C0 >32.2 µg/ml (38/123; 30.9%). These results suggest that the initial urine PQ concentration may be the optimal index for predicting the prognosis of patients with acute PQ poisoning. Additionally, dose of poison, arterial blood lactate, Csec and rebound rate also have referential significance.

  15. Circulating Markers of Endothelial Dysfunction Interact With Proteinuria in Predicting Mortality in Renal Transplant Recipients

    NARCIS (Netherlands)

    van Ree, Rutger M.; Oterdoom, Leendert H.; de Vries, Aiko P.J.; Homan van der Heide, Jaap J.; van Son, Willem J.; Navis, Gerjan; Gans, Reinold O.B.; Bakker, Stephan J L

    2008-01-01

    BACKGROUND: Proteinuria is associated with endothelial dysfunction (ED) and increased mortality. We investigated whether urinary protein excretion (UPE) is correlated with markers of ED and whether these markers affect the association of proteinuria with mortality in renal transplant recipients

  16. Circulating markers of endothelial dysfunction interact with proteinuria in predicting mortality in renal transplant recipients

    NARCIS (Netherlands)

    van Ree, Rutger M.; Oterdoom, Leendert H.; de Vries, Aiko P. J.; Homan van der Heide, Jaap J.; van Son, Willem J.; Navis, Gerjan; Gans, Reinold O. B.; Bakker, Stephan J. L.

    2008-01-01

    Proteinuria is associated with endothelial dysfunction (ED) and increased mortality. We investigated whether urinary protein excretion (UPE) is correlated with markers of ED and whether these markers affect the association of proteinuria with mortality in renal transplant recipients (RTR). Six

  17. Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong

    OpenAIRE

    Zhang, Jiangshe; Ding, Weifu

    2017-01-01

    With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The e...

  18. [Reliability of the PROFUND index to predict 4-year mortality in polypathological patients].

    Science.gov (United States)

    Díez-Manglano, Jesús; Del Corral Beamonte, Esther; Ramos Ibáñez, Rosa; Lambán Aranda, María Pilar; Toyas Miazza, Carla; Rodero Roldán, María Del Mar; Ortiz Domingo, Concepción; Munilla López, Eulalia; de Escalante Yangüela, Begoña

    2016-09-16

    To determine the usefullness of the PROFUND index to assess the risk of global death after 4 years in polypathological patients. Multicenter prospective cohort (Internal Medicine and Geriatrics) study. Polypathological patients admitted between March 1st and June 30th 2011 were included. For each patient, data concerning age, sex, living at home or in a nursing residence, polypathology categories, Charlson, Barthel and Lawton-Brody indexes, Pfeiffer questionnaire, socio-familial Gijon scale, delirium, number of drugs, hemoglobin and creatinine values were gathered, and the PROFUND index was calculated. The follow-up lasted 4 years. We included 441 patients, 324 from Internal Medicine and 117 from Geriatrics, with a mean age of 80.9 (8.7) years. Of them, 245 (55.6%) were women. Heart (62.7%), neurological (41.4%) and respiratory (37.3%) diseases were the most frequent. Geriatrics inpatients were older and more dependants and presented greater cognitive deterioration. After 4 years, 335 (76%) patients died. Mortality was associated with age, dyspnoea, Barthel index<60, delirium, advanced neoplasia and≥4 admissions in the last year. The area under the curve of the PROFUND index was 0.748, 95% CI 0.689-0.806, P<.001 in Internal Medicine and 0.517, 95% CI 0.369-0.666, P=.818 in Geriatrics patients, respectively. The PROFUND index is a reliable tool for predicting long-term global mortality in polypathological patients from Internal Medicine but not from Geriatrics departments. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

  19. High mortality of the larvae of the common mussel at low concentrations of tributyltin

    Energy Technology Data Exchange (ETDEWEB)

    Beaumont, A.R.; Budd, M.D.

    1984-11-01

    Laboratory reared veliger larvae of the common mussel Mytilus edulis were grown for 15 days in filtered seawater containing 10 ..mu..g l/sup -1/, 1 ..mu..g l/sup -1/ and 0.1 ..mu..g l/sup -1/ tributyltin oxide, (TBTO), the biocide in recent antifouling paint formulations. No larvae survived longer than 5 days in 10 ..mu..g l/sup -1/ TBTO. Approximately half the larvae subjected to 0.1 ..mu..g/sup -1/ TBTO were dead by day 15 (approximately 15 day LC/sub 50/ = 0.1 ..sqrt..g l/sup -1/ TBTO) and most of the surviving larvae were moribund and had grown significantly more slowly than controls. It is noted that current recorded levels of TBT at several UK estuarine sites are higher than 0.1 ..mu..g l/sup -1/ and there has therefore probably been a high mortality of mussel larvae at such sites. The results are discussed in relation to the reported short-term toxicity of organotins to other marine organisms and the value of carrying out longer term tests at low levels of TBT is pointed out.

  20. Mortality prediction to hospitalized patients with influenza pneumonia: PO2 /FiO2 combined lymphocyte count is the answer.

    Science.gov (United States)

    Shi, Shu Jing; Li, Hui; Liu, Meng; Liu, Ying Mei; Zhou, Fei; Liu, Bo; Qu, Jiu Xin; Cao, Bin

    2017-05-01

    Community-acquired pneumonia (CAP) severity scores perform well in predicting mortality of CAP patients, but their applicability in influenza pneumonia is powerless. The aim of our research was to test the efficiency of PO 2 /FiO 2 and CAP severity scores in predicting mortality and intensive care unit (ICU) admission with influenza pneumonia patients. We reviewed all patients with positive influenza virus RNA detection in Beijing Chao-Yang Hospital during the 2009-2014 influenza seasons. Outpatients, inpatients with no pneumonia and incomplete data were excluded. We used receiver operating characteristic curves (ROCs) to verify the accuracy of severity scores or indices as mortality predictors in the study patients. Among 170 hospitalized patients with influenza pneumonia, 30 (17.6%) died. Among those who were classified as low-risk (predicted mortality 0.1%-2.1%) by pneumonia severity index (PSI) or confusion, urea, respiratory rate, blood pressure, age ≥65 year (CURB-65), the actual mortality ranged from 5.9 to 22.1%. Multivariate logistic regression indicated that hypoxia (PO 2 /FiO 2  ≤ 250) and lymphopenia (peripheral blood lymphocyte count pneumonia confirmed a similar pattern and PO 2 /FiO 2 combined lymphocyte count was also the best predictor for predicting ICU admission. In conclusion, we found that PO 2 /FiO 2 combined lymphocyte count is simple and reliable predictor of hospitalized patients with influenza pneumonia in predicting mortality and ICU admission. When PO 2 /FiO 2  ≤ 250 or peripheral blood lymphocyte count pneumonia. © 2015 The Authors. The Clinical Respiratory Journal published by John Wiley & Sons Ltd.

  1. Trauma and Injury Severity Score in Predicting Mortality of Polytrauma Patients

    Directory of Open Access Journals (Sweden)

    Bambang Gunawan

    2018-01-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE Abstract TRISS (Trauma and Injury Severity Score is one of the most commonly used trauma score. Currently, there is no data about using TRISS in the care of polytrauma patients at emergency department of dr. Cipto Mangunkusumo Hospital (CMH. This research was intended to evaluate whether TRISS can predict the mortality of polytrauma patients at CMH. This was an analytic descriptive study with retrospective cohort design. Data was collected from medical records of polytrauma patients who were admitted to emergency department of CMH from 2011-201 4 then we analyzed the relationship between TRISS and patient’s prognosis. Furthermore, we conducted bivariate and multivariate analysis by SPSS 20 software. Seventy medical records were included in this study. The majority of patients were male (65% in young age. There were 69 patients who experienced blunt trauma, with the majority (94.3% were caused by motor vehicle accident. After receiving trauma care, there were 26 deaths, while other 44 patients survived. From bivariate and multivariate analysis, we found a significant difference between TRISS and patient’s prognosis. TRISS strongly predicts polytrauma patient’s mortality (AUC 0,899; IK95% 0,824-0,975. TRISS has 84,6% sensitivity and 81.8% specificity with optimal intersection point ≤ 90,5. TRISS is able to predict the mortality of polytrauma patients at CMH. TRISS untuk Memprediksi Mortalitas Pasien Politrauma Abstrak TRISS merupakan salah satu penilaian trauma yang paling sering digunakan. Namun, saat ini belum ada data penggunaan TRISS dalam penanganan pasien politrauma di Instalasi Gawat Darurat (IGD Rumah Sakit Umum Pusat Nasional dr. Cipto Mangunkusumo (RSUPNCM. Penelitian ini bertujuan untuk mengetahui kemampuan TRISS dalam memprediksi mortalitas pasien politrauma di IGD RSUPNCM. Penelitian ini adalah studi analitik deskriptif dengan menggunakan desain kohort retrospektif. Data diambil

  2. Serial evaluation of the MODS, SOFA and LOD scores to predict ICU mortality in mixed critically ill patients.

    Science.gov (United States)

    Khwannimit, Bodin

    2008-09-01

    To perform a serial assessment and compare ability in predicting the intensive care unit (ICU) mortality of the multiple organ dysfunction score (MODS), sequential organ failure assessment (SOFA) and logistic organ dysfunction (LOD) score. The data were collected prospectively on consecutive ICU admissions over a 24-month period at a tertiary referral university hospital. The MODS, SOFA, and LOD scores were calculated on initial and repeated every 24 hrs. Two thousand fifty four patients were enrolled in the present study. The maximum and delta-scores of all the organ dysfunction scores correlated with ICU mortality. The maximum score of all models had better ability for predicting ICU mortality than initial or delta score. The areas under the receiver operating characteristic curve (AUC) for maximum scores was 0.892 for the MODS, 0.907 for the SOFA, and 0.92for the LOD. No statistical difference existed between all maximum scores and Acute Physiology and Chronic Health Evaluation II (APACHE II) score. Serial assessment of organ dysfunction during the ICU stay is reliable with ICU mortality. The maximum scores is the best discrimination comparable with APACHE II score in predicting ICU mortality.

  3. The New York State risk score for predicting in-hospital/30-day mortality following percutaneous coronary intervention.

    Science.gov (United States)

    Hannan, Edward L; Farrell, Louise Szypulski; Walford, Gary; Jacobs, Alice K; Berger, Peter B; Holmes, David R; Stamato, Nicholas J; Sharma, Samin; King, Spencer B

    2013-06-01

    This study sought to develop a percutaneous coronary intervention (PCI) risk score for in-hospital/30-day mortality. Risk scores are simplified linear scores that provide clinicians with quick estimates of patients' short-term mortality rates for informed consent and to determine the appropriate intervention. Earlier PCI risk scores were based on in-hospital mortality. However, for PCI, a substantial percentage of patients die within 30 days of the procedure after discharge. New York's Percutaneous Coronary Interventions Reporting System was used to develop an in-hospital/30-day logistic regression model for patients undergoing PCI in 2010, and this model was converted into a simple linear risk score that estimates mortality rates. The score was validated by applying it to 2009 New York PCI data. Subsequent analyses evaluated the ability of the score to predict complications and length of stay. A total of 54,223 patients were used to develop the risk score. There are 11 risk factors that make up the score, with risk factor scores ranging from 1 to 9, and the highest total score is 34. The score was validated based on patients undergoing PCI in the previous year, and accurately predicted mortality for all patients as well as patients who recently suffered a myocardial infarction (MI). The PCI risk score developed here enables clinicians to estimate in-hospital/30-day mortality very quickly and quite accurately. It accurately predicts mortality for patients undergoing PCI in the previous year and for MI patients, and is also moderately related to perioperative complications and length of stay. Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  4. Admission hyperglycemia predicts inhospital mortality and major adverse cardiac events after primary percutaneous coronary intervention in patients without diabetes mellitus.

    Science.gov (United States)

    Ekmekci, Ahmet; Cicek, Gokhan; Uluganyan, Mahmut; Gungor, Baris; Osman, Faizel; Ozcan, Kazim Serhan; Bozbay, Mehmet; Ertas, Gokhan; Zencirci, Aycan; Sayar, Nurten; Eren, Mehmet

    2014-02-01

    Admission hyperglycemia is associated with high inhospital and long-term adverse events in patients that undergo primary percutaneous coronary intervention (PCI). We aimed to evaluate whether hyperglycemia predicts inhospital mortality. We prospectively analyzed 503 consecutive patients. The patients were divided into tertiles according to the admission glucose levels. Tertile I: glucose 145 mg/dL (n = 169). Inhospital mortality was 0 in tertile I, 2 in tertile II, and 9 in tertile III (P < .02). Cardiogenic shock occurred more frequently in tertile III compared to tertiles I and II (10% vs 4.1% and 0.6%, respectively, P = .01). Multivariate logistic regression analysis revealed that patients in tertile III had significantly higher risk of inhospital major adverse cardiac events compared to patients in tertile I (odds ratio: 9.55, P < .02). Admission hyperglycemia predicts inhospital adverse cardiac events in mortality and acute ST-segment elevation myocardial infarction in patients that underwent primary PCI.

  5. A rapid method of predicting radiocaesium concentrations in sheep from activity levels in faeces

    International Nuclear Information System (INIS)

    McGee, E.J.; Synnott, H.J.; Colgan, P.A.; Keatinge, M.J.

    1994-01-01

    The use of faecal samples taken from sheep flocks as a means of predicting radiocaesium concentrations in live animals was studied. Radiocaesium levels in 1726 sheep from 29 flocks were measured using in vivo techniques and a single faecal sample taken from each flock was also analysed. A highly significant relationship was found to exist between mean flock activity and activity in the corresponding faecal samples. Least-square regression yielded a simple model for predicting mean flock radiocaesium concentrations based on activity levels in faecal samples. A similar analysis of flock maxima and activity levels in faeces provides an alternative model for predicting the expected within-flock maximum radiocaesium concentration. (Author)

  6. GYM score: 30-day mortality predictive model in elderly patients attended in the emergency department with infection.

    Science.gov (United States)

    González Del Castillo, Juan; Escobar-Curbelo, Luis; Martínez-Ortíz de Zárate, Mikel; Llopis-Roca, Ferrán; García-Lamberechts, Jorge; Moreno-Cuervo, Álvaro; Fernández, Cristina; Martín-Sánchez, Francisco Javier

    2017-06-01

    To determine the validity of the classic sepsis criteria or systemic inflammatory response syndrome (heart rate, respiratory rate, temperature, and leukocyte count) and the modified sepsis criteria (systemic inflammatory response syndrome criteria plus glycemia and altered mental status), and the validity of each of these variables individually to predict 30-day mortality, as well as develop a predictive model of 30-day mortality in elderly patients attended for infection in emergency departments (ED). A prospective cohort study including patients at least 75 years old attended in three Spanish university ED for infection during 2013 was carried out. Demographic variables and data on comorbidities, functional status, hemodynamic sepsis diagnosis variables, site of infection, and 30-day mortality were collected. A total of 293 patients were finally included, mean age 84.0 (SD 5.5) years, and 158 (53.9%) were men. Overall, 185 patients (64%) fulfilled the classic sepsis criteria and 224 patients (76.5%) fulfilled the modified sepsis criteria. The all-cause 30-day mortality was 13.0%. The area under the curve of the classic sepsis criteria was 0.585 [95% confidence interval (CI) 0.488-0.681; P=0.106], 0.594 for modified sepsis criteria (95% CI: 0.502-0.685; P=0.075), and 0.751 (95% CI: 0.660-0.841; P20 bpm; Morbidity-Charlson index ≥3) to predict 30-day mortality, with statistically significant differences (P=0.004 and Pcapacity than the classic and the modified sepsis criteria to predict 30-day mortality in elderly patients attended for infection in the ED.

  7. Performance Evaluation of Five Different Disseminated Intravascular Coagulation (DIC) Diagnostic Criteria for Predicting Mortality in Patients with Complicated Sepsis.

    Science.gov (United States)

    Ha, Sang Ook; Park, Sang Hyuk; Hong, Sang Bum; Jang, Seongsoo

    2016-11-01

    Disseminated intravascular coagulation (DIC) is a major complication in sepsis patients. We compared the performance of five DIC diagnostic criteria, focusing on the prediction of mortality. One hundred patients with severe sepsis or septic shock admitted to intensive care unit (ICU) were enrolled. Routine DIC laboratory tests were performed over the first 4 days after admission. The overall ICU and 28-day mortality in DIC patients diagnosed from five criteria (International Society on Thrombosis and Haemostasis [ISTH], the Japanese Association for Acute Medicine [JAAM], the revised JAAM [R-JAAM], the Japanese Ministry of Health and Welfare [JMHW] and the Korean Society on Thrombosis and Hemostasis [KSTH]) were compared. Both KSTH and JMHW criteria showed superior performance than ISTH, JAAM and R-JAAM criteria in the prediction of overall ICU mortality in DIC patients (odds ratio 3.828 and 5.181, P = 0.018 and 0.006, 95% confidence interval 1.256-11.667 and 1.622-16.554, respectively) when applied at day 1 after admission, and survival analysis demonstrated significant prognostic impact of KSTH and JMHW criteria on the prediction of 28-day mortality (P = 0.007 and 0.049, respectively) when applied at day 1 after admission. In conclusion, both KSTH and JMHW criteria would be more useful than other three criteria in predicting prognosis in DIC patients with severe sepsis or septic shock.

  8. Plasma glucose and not hemoglobin or renal function predicts mortality in patients with STEMI complicated with cardiogenic shock

    NARCIS (Netherlands)

    Vis, Marije M.; Engström, Annemarie E.; Sjauw, Krischan D.; Tjong, Fleur Vy; Baan, Jan; Koch, Karel T.; de Vries, Hans J.; Tijssen, Jan Gp; de Winter, Robbert J.; Piek, Jan J.; Henriques, José Ps

    2010-01-01

    Objective To assess the predictive value of three biomarkers for mortality in ST-segment elevation myocardial infarction (STEMI) with cardiogenic shock. Background STEMI complicated by cardiogenic shock accounts for the majority of STEMI related deaths. Patients with STEMI and hyperglycemia, anemia

  9. Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

    Science.gov (United States)

    Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

    2012-01-01

    In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

  10. A modified Elixhauser score for predicting in-hospital mortality in internal medicine admissions.

    Science.gov (United States)

    Fabbian, Fabio; De Giorgi, Alfredo; Maietti, Elisa; Gallerani, Massimo; Pala, Marco; Cappadona, Rosaria; Manfredini, Roberto; Fedeli, Ugo

    2017-05-01

    In-hospital mortality (IHM) is an indicator of the quality of care provided. The two most widely used scores for predicting IHM by International Classification of Diseases (ICD) codes are the Elixhauser (EI) and the Charlson Comorbidity indexes. Our aim was to obtain new measures based on internal medicine ICD codes for the original EI, to detect risk for IHM. This single-center retrospective study included hospital admissions for any cause in the department of internal medicine between January 1, 2000, and December 31, 2013, recorded in the hospital database. The EI was calculated for evaluation of comorbidity, then we added age, gender and diagnosis of ischemic heart disease. IHM was our outcome. Only predictors positively associated with IHM were taken into consideration and the Sullivan's method was applied in order to modify the parameter estimates of the regression model into an index. We analyzed 75,586 admissions (53.4% females) and mean age was 72.7±16.3years. IHM was 7.9% and mean score was 12.1±7.6. The points assigned to each condition ranged from 0 to 16, and the possible range of the score varied between 0 and 89. In our population the score ranged from 0 to 54, and it was higher in the deceased group. Receiver operating characteristic curve of the new score was 0.721 (95% CI 0.714-0.727, pInternal Medicine. Published by Elsevier B.V. All rights reserved.

  11. Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro.

    Directory of Open Access Journals (Sweden)

    Niels Hadrup

    Full Text Available Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA, independent action (IA and generalized concentration addition (GCA models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot

  12. Child Mortality as Predicted by Nutritional Status and Recent Weight Velocity in Children under Two in Rural Africa.

    LENUS (Irish Health Repository)

    2012-01-31

    WHO has released prescriptive child growth standards for, among others, BMI-for-age (BMI-FA), mid-upper arm circumference-for-age, and weight velocity. The ability of these indices to predict child mortality remains understudied, although growth velocity prognostic value underlies current growth monitoring programs. The study aims were first to assess, in children under 2, the independent and combined ability of these indices and of stunting to predict all-cause mortality within 3 mo, and second, the comparative abilities of weight-for-length (WFL) and BMI-FA to predict short-term (<3 mo) mortality. We used anthropometry and survival data from 2402 children aged between 0 and 24 mo in a rural area of the Democratic Republic of Congo with high malnutrition and mortality rates and limited nutritional rehabilitation. Analyses used Cox proportional hazard models and receiver operating characteristic curves. Univariate analysis and age-adjusted analysis showed predictive ability of all indices. Multivariate analysis without age adjustment showed that only very low weight velocity [HR = 3.82 (95%CI = 1.91, 7.63); P < 0.001] was independently predictive. With age adjustment, very low weight velocity [HR = 3.61 (95%CI = 1.80, 7.25); P < 0.001] was again solely retained as an independent predictor. There was no evidence for a difference in predictive ability between WFL and BMI-FA. This paper shows the value of attained BMI-FA, a marker of wasting status, and recent weight velocity, a marker of the wasting process, in predicting child death using the WHO child growth standards. WFL and BMI-FA appear equivalent as predictors.

  13. External validation of a biomarker and clinical prediction model for hospital mortality in acute respiratory distress syndrome.

    Science.gov (United States)

    Zhao, Zhiguo; Wickersham, Nancy; Kangelaris, Kirsten N; May, Addison K; Bernard, Gordon R; Matthay, Michael A; Calfee, Carolyn S; Koyama, Tatsuki; Ware, Lorraine B

    2017-08-01

    Mortality prediction in ARDS is important for prognostication and risk stratification. However, no prediction models have been independently validated. A combination of two biomarkers with age and APACHE III was superior in predicting mortality in the NHLBI ARDSNet ALVEOLI trial. We validated this prediction tool in two clinical trials and an observational cohort. The validation cohorts included 849 patients from the NHLBI ARDSNet Fluid and Catheter Treatment Trial (FACTT), 144 patients from a clinical trial of sivelestat for ARDS (STRIVE), and 545 ARDS patients from the VALID observational cohort study. To evaluate the performance of the prediction model, the area under the receiver operating characteristic curve (AUC), model discrimination, and calibration were assessed, and recalibration methods were applied. The biomarker/clinical prediction model performed well in all cohorts. Performance was better in the clinical trials with an AUC of 0.74 (95% CI 0.70-0.79) in FACTT, compared to 0.72 (95% CI 0.67-0.77) in VALID, a more heterogeneous observational cohort. The AUC was 0.73 (95% CI 0.70-0.76) when FACTT and VALID were combined. We validated a mortality prediction model for ARDS that includes age, APACHE III, surfactant protein D, and interleukin-8 in a variety of clinical settings. Although the model performance as measured by AUC was lower than in the original model derivation cohort, the biomarker/clinical model still performed well and may be useful for risk assessment for clinical trial enrollment, an issue of increasing importance as ARDS mortality declines, and better methods are needed for selection of the most severely ill patients for inclusion.

  14. Charlson comorbidity index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients

    Directory of Open Access Journals (Sweden)

    Stavem K

    2017-06-01

    Full Text Available Knut Stavem,1–3 Henrik Hoel,4 Stein Arve Skjaker,5 Rolf Haagensen6 1Institute of Clinical Medicine, University of Oslo, Oslo, 2Department of Pulmonary Medicine, Medical Division, 3Health Services Research Unit, Akershus University Hospital, Lørenskog, 4Department of Surgery, Sykehuset Innlandet Kongsvinger, Kongsvinger, 5Section of Orthopaedic Emergency, Department of Orthopaedic Surgery, Oslo University Hospital, Oslo, 6Department of Anaesthesiology, Surgical Division, Akershus University Hospital, Lørenskog, Norway Purpose: This study compared the Charlson comorbidity index (CCI information derived from chart review and administrative systems to assess the completeness and agreement between scores, evaluate the capacity to predict 30-day and 1-year mortality in intensive care unit (ICU patients, and compare the predictive capacity with that of the Simplified Acute Physiology Score (SAPS II model.Patients and methods: Using data from 959 patients admitted to a general ICU in a Norwegian university hospital from 2007 to 2009, we compared the CCI score derived from chart review and administrative systems. Agreement was assessed using % agreement, kappa, and weighted kappa. The capacity to predict 30-day and 1-year mortality was assessed using logistic regression, model discrimination with the c-statistic, and calibration with a goodness-of-fit statistic.Results: The CCI was complete (n=959 when calculated from chart than from administrative data (n=839. Agreement was good, with a weighted kappa of 0.667 (95% confidence interval: 0.596–0.714. The c-statistics for categorized CCI scores from charts and administrative data were similar in the model that included age, sex, and type of admission: 0.755 and 0.743 for 30-day mortality, respectively, and 0.783 and 0.775, respectively, for 1-year mortality. Goodness-of-fit statistics supported the model fit.Conclusion: The CCI scores from chart review and administrative data showed good agreement

  15. Predictive score for mortality in patients with COPD exacerbations attending hospital emergency departments

    Science.gov (United States)

    2014-01-01

    Background Limited information is available about predictors of short-term outcomes in patients with exacerbation of chronic obstructive pulmonary disease (eCOPD) attending an emergency department (ED). Such information could help stratify these patients and guide medical decision-making. The aim of this study was to develop a clinical prediction rule for short-term mortality during hospital admission or within a week after the index ED visit. Methods This was a prospective cohort study of patients with eCOPD attending the EDs of 16 participating hospitals. Recruitment started in June 2008 and ended in September 2010. Information on possible predictor variables was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up. Main short-term outcomes were death during hospital admission or within 1 week of discharge to home from the ED, as well as at death within 1 month of the index ED visit. Multivariate logistic regression models were developed in a derivation sample and validated in a validation sample. The score was compared with other published prediction rules for patients with stable COPD. Results In total, 2,487 patients were included in the study. Predictors of death during hospital admission, or within 1 week of discharge to home from the ED were patient age, baseline dyspnea, previous need for long-term home oxygen therapy or non-invasive mechanical ventilation, altered mental status, and use of inspiratory accessory muscles or paradoxical breathing upon ED arrival (area under the curve (AUC) = 0.85). Addition of arterial blood gas parameters (oxygen and carbon dioxide partial pressures (PO2 and PCO2)) and pH) did not improve the model. The same variables were predictors of death at 1 month (AUC = 0.85). Compared with other commonly used tools for predicting the severity of COPD in stable patients, our rule was significantly better

  16. Comparison of Two Predictive Models for Short-Term Mortality in Patients after Severe Traumatic Brain Injury.

    Science.gov (United States)

    Kesmarky, Klara; Delhumeau, Cecile; Zenobi, Marie; Walder, Bernhard

    2017-07-15

    The Glasgow Coma Scale (GCS) and the Abbreviated Injury Score of the head region (HAIS) are validated prognostic factors in traumatic brain injury (TBI). The aim of this study was to compare the prognostic performance of an alternative predictive model including motor GCS, pupillary reactivity, age, HAIS, and presence of multi-trauma for short-term mortality with a reference predictive model including motor GCS, pupil reaction, and age (IMPACT core model). A secondary analysis of a prospective epidemiological cohort study in Switzerland including patients after severe TBI (HAIS >3) with the outcome death at 14 days was performed. Performance of prediction, accuracy of discrimination (area under the receiver operating characteristic curve [AUROC]), calibration, and validity of the two predictive models were investigated. The cohort included 808 patients (median age, 56; interquartile range, 33-71), median GCS at hospital admission 3 (3-14), abnormal pupil reaction 29%, with a death rate of 29.7% at 14 days. The alternative predictive model had a higher accuracy of discrimination to predict death at 14 days than the reference predictive model (AUROC 0.852, 95% confidence interval [CI] 0.824-0.880 vs. AUROC 0.826, 95% CI 0.795-0.857; p predictive model had an equivalent calibration, compared with the reference predictive model Hosmer-Lemeshow p values (Chi2 8.52, Hosmer-Lemeshow p = 0.345 vs. Chi2 8.66, Hosmer-Lemeshow p = 0.372). The optimism-corrected value of AUROC for the alternative predictive model was 0.845. After severe TBI, a higher performance of prediction for short-term mortality was observed with the alternative predictive model, compared with the reference predictive model.

  17. Comparison of early thallium-201 scintigraphy and gated blood pool imaging for predicting mortality in patients with acute myocardial infarction

    International Nuclear Information System (INIS)

    Becker, L.C.; Silverman, K.J.; Bulkley, B.H.; Kallman, C.H.; Mellits, E.D.; Weisfeldt, M.

    1983-01-01

    The extent of abnormality in early thallium-201 and gated cardiac blood pool scintigrams has been reported to be useful for predicting mortality in patients with acute myocardial infarction (AMI). To compare the two techniques, 91 patients admitted consecutively with evident or strongly suspected AMI underwent both imaging studies within 15 hours of the onset of symptoms. Patients with pulmonary edema or shock were excluded. AMI developed in 84% of patients, and 6-month mortality for the entire group was 16%. A thallium defect score of 7.0 or greater identified a subgroup of 14 patients with 64% 6-month mortality rate. Similarly, a left ventricular ejection fraction of 35% or less identified a high-risk subgroup of 10 patients with a 6-month mortality of 60%. Mortality in the remaining patients was 8% for thallium score less than 7 and 11% for ejection fraction greater than 35%. The mortality rate was highest among patients who had concordant high-risk scintigrams (five of six, 83%), lowest in those with concordant low-risk studies (five of 64, 8%) and intermediate in those with discordant results (four of 11, 36%). Of a number of clinical variables, only the appearance of Q waves, peak creatine kinase greater than 1000 IU/I, and history of infarction were significantly associated with mortality. High-risk thallium or blood pool scintigraphic results were significantly more predictive and a thallium score of 7 or greater was more sensitive for detecting nonsurvivors than ejection fraction 35% or less at a similar level of specificity

  18. A predictive model for early mortality after surgical treatment of heart valve or prosthesis infective endocarditis. The EndoSCORE.

    Science.gov (United States)

    Di Mauro, Michele; Dato, Guglielmo Mario Actis; Barili, Fabio; Gelsomino, Sandro; Santè, Pasquale; Corte, Alessandro Della; Carrozza, Antonio; Ratta, Ester Della; Cugola, Diego; Galletti, Lorenzo; Devotini, Roger; Casabona, Riccardo; Santini, Francesco; Salsano, Antonio; Scrofani, Roberto; Antona, Carlo; Botta, Luca; Russo, Claudio; Mancuso, Samuel; Rinaldi, Mauro; De Vincentiis, Carlo; Biondi, Andrea; Beghi, Cesare; Cappabianca, Giangiuseppe; Tarzia, Vincenzo; Gerosa, Gino; De Bonis, Michele; Pozzoli, Alberto; Nicolini, Francesco; Benassi, Filippo; Rosato, Francesco; Grasso, Elena; Livi, Ugolino; Sponga, Sandro; Pacini, Davide; Di Bartolomeo, Roberto; De Martino, Andrea; Bortolotti, Uberto; Onorati, Francesco; Faggian, Giuseppe; Lorusso, Roberto; Vizzardi, Enrico; Di Giammarco, Gabriele; Marinelli, Daniele; Villa, Emmanuel; Troise, Giovanni; Picichè, Marco; Musumeci, Francesco; Paparella, Domenico; Margari, Vito; Tritto, Francesco; Damiani, Girolamo; Scrascia, Giuseppe; Zaccaria, Salvatore; Renzulli, Attilio; Serraino, Giuseppe; Mariscalco, Giovanni; Maselli, Daniele; Foschi, Massimiliano; Parolari, Alessandro; Nappi, Giannantonio

    2017-08-15

    The aim of this large retrospective study was to provide a logistic risk model along an additive score to predict early mortality after surgical treatment of patients with heart valve or prosthesis infective endocarditis (IE). From 2000 to 2015, 2715 patients with native valve endocarditis (NVE) or prosthesis valve endocarditis (PVE) were operated on in 26 Italian Cardiac Surgery Centers. The relationship between early mortality and covariates was evaluated with logistic mixed effect models. Fixed effects are parameters associated with the entire population or with certain repeatable levels of experimental factors, while random effects are associated with individual experimental units (centers). Early mortality was 11.0% (298/2715); At mixed effect logistic regression the following variables were found associated with early mortality: age class, female gender, LVEF, preoperative shock, COPD, creatinine value above 2mg/dl, presence of abscess, number of treated valve/prosthesis (with respect to one treated valve/prosthesis) and the isolation of Staphylococcus aureus, Fungus spp., Pseudomonas Aeruginosa and other micro-organisms, while Streptococcus spp., Enterococcus spp. and other Staphylococci did not affect early mortality, as well as no micro-organisms isolation. LVEF was found linearly associated with outcomes while non-linear association between mortality and age was tested and the best model was found with a categorization into four classes (AUC=0.851). The following study provides a logistic risk model to predict early mortality in patients with heart valve or prosthesis infective endocarditis undergoing surgical treatment, called "The EndoSCORE". Copyright © 2017. Published by Elsevier B.V.

  19. The Surgical Mortality Probability Model: derivation and validation of a simple risk prediction rule for noncardiac surgery.

    Science.gov (United States)

    Glance, Laurent G; Lustik, Stewart J; Hannan, Edward L; Osler, Turner M; Mukamel, Dana B; Qian, Feng; Dick, Andrew W

    2012-04-01

    To develop a 30-day mortality risk index for noncardiac surgery that can be used to communicate risk information to patients and guide clinical management at the "point-of-care," and that can be used by surgeons and hospitals to internally audit their quality of care. Clinicians rely on the Revised Cardiac Risk Index to quantify the risk of cardiac complications in patients undergoing noncardiac surgery. Because mortality from noncardiac causes accounts for many perioperative deaths, there is also a need for a simple bedside risk index to predict 30-day all-cause mortality after noncardiac surgery. Retrospective cohort study of 298,772 patients undergoing noncardiac surgery during 2005 to 2007 using the American College of Surgeons National Surgical Quality Improvement Program database. The 9-point S-MPM (Surgical Mortality Probability Model) 30-day mortality risk index was derived empirically and includes three risk factors: ASA (American Society of Anesthesiologists) physical status, emergency status, and surgery risk class. Patients with ASA physical status I, II, III, IV or V were assigned either 0, 2, 4, 5, or 6 points, respectively; intermediate- or high-risk procedures were assigned 1 or 2 points, respectively; and emergency procedures were assigned 1 point. Patients with risk scores less than 5 had a predicted risk of mortality less than 0.50%, whereas patients with a risk score of 5 to 6 had a risk of mortality between 1.5% and 4.0%. Patients with a risk score greater than 6 had risk of mortality more than 10%. S-MPM exhibited excellent discrimination (C statistic, 0.897) and acceptable calibration (Hosmer-Lemeshow statistic 13.0, P = 0.023) in the validation data set. Thirty-day mortality after noncardiac surgery can be accurately predicted using a simple and accurate risk score based on information readily available at the bedside. This risk index may play a useful role in facilitating shared decision making, developing and implementing risk

  20. Hourly peak concentration measuring the PM2.5-mortality association: Results from six cities in the Pearl River Delta study

    Science.gov (United States)

    Lin, Hualiang; Ratnapradipa, Kendra; Wang, Xiaojie; Zhang, Yonghui; Xu, Yanjun; Yao, Zhenjiang; Dong, Guanghui; Liu, Tao; Clark, Jessica; Dick, Rebecca; Xiao, Jianpeng; Zeng, Weilin; Li, Xing; Qian, Zhengmin (Min); Ma, Wenjun

    2017-07-01

    Compared with daily mean concentration of air pollution, hourly peak concentration may be more directly relevant to the acute health effects due to the high concentration levels, however, few have analyzed the acute mortality effects of hourly peak levels of air pollution. We examined the associations of hourly peak concentration of fine particulate matter air pollution (PM2.5) with mortality in six cities in Pearl River Delta, China. We used generalized additive Poisson models to examine the associations with adjustment for potential confounders in each city. We further applied random-effects meta-analyses to estimate the regional overall effects. We further estimated the mortality burden attributable to hourly peak and daily mean PM2.5. We observed significant associations between hourly peak PM2.5 and mortality. Each 10 μg/m3 increase in 4-day averaged (lag03) hourly peak PM2.5 corresponded to a 0.9% [95% confidence interval (CI): 0.7%, 1.1%] increase in total mortality, 1.2% (95% CI: 1.0%, 1.5%) in cardiovascular mortality, and 0.7% (95% CI: 0.2%, 1.1%) in respiratory mortality. We observed a greater mortality burden using hourly peak PM2.5 than daily mean PM2.5, with an estimated 12915 (95% CI: 9922, 15949) premature deaths attributable to hourly peak PM2.5, and 7951 (95% CI: 5067, 10890) to daily mean PM2.5 in the Pearl River Delta (PRD) region during the study period. This study suggests that hourly peak PM2.5 might be one important risk factor of mortality in PRD region of China; the finding provides important information for future air pollution management and epidemiological studies.

  1. Mastication and prescribed fire influences on tree mortality and predicted fire behavior in ponderosa pine

    Science.gov (United States)

    Alicia L. Reiner; Nicole M. Vaillant; Scott N. Dailey

    2012-01-01

    The purpose of this study was to provide land managers with information on potential wildfire behavior and tree mortality associated with mastication and masticated/fire treatments in a plantation. Additionally, the effect of pulling fuels away from tree boles before applying fire treatment was studied in relation to tree mortality. Fuel characteristics and tree...

  2. MR-proANP improves prediction of mortality and cardiovascular events in patients with STEMI

    DEFF Research Database (Denmark)

    Lindberg, Søren; Jensen, Jan Skov; Pedersen, Sune H

    2015-01-01

    drawn immediately before PCI. Plasma MR-proANP was measured using an automated processing assay. Endpoints were all-cause mortality (n = 137) and the combined endpoint (n = 170) of major adverse cardiovascular events (MACE) defined as cardiovascular mortality and admission due to recurrent MI, ischaemic...

  3. Cerebrospinal fluid neurofilament light concentration in motor neuron disease and frontotemporal dementia predicts survival.

    Science.gov (United States)

    Skillbäck, Tobias; Mattsson, Niklas; Blennow, Kaj; Zetterberg, Henrik

    2017-08-01

    To aid diagnostics, patient stratification and studies seeking to find treatments for the related diseases motor neuron disease (MND) and frontotemporal dementia (FTD), there is a need to establish a way to assess disease severity and the amount of ongoing neurodegeneration. Previous studies have suggested that cerebrospinal fluid (CSF) neurofilament light (NFL) may serve this purpose. We cross-referenced the Swedish mortality registry with the laboratory database at Sahlgrenska University Hospital to produce a dataset of CSF NFL concentrations and mortality information for 715 MND patients, 87 FTD patients, and 107 healthy controls. Biomarker concentrations were analysed in relation to recorded cause of death and time of death. MND patients had significantly higher CSF NFL concentrations than FTD patients. Both groups had significantly higher concentrations than the healthy controls (mean 709% increase in MND and 307% increase in FTD). Higher concentrations of CSF NFL were associated with shorter survival in both MND and FTD. The results of this study strengthen the notion of CSF NFL as a useful tool for determining disease intensity in MND and FTD patients. Further studies in patient cohorts with clinically subtyped and genetically classified diagnoses are needed.

  4. Validation of the Glasgow-Blatchford Scoring System to predict mortality in patients with upper gastrointestinal bleeding in a hospital of Lima, Peru (June 2012-December 2013)

    OpenAIRE

    Cassana, Alessandra; Scialom, Silvia; Segura, Eddy R.; Chacaltana, Alfonso

    2015-01-01

    Background and aim: Upper gastrointestinal bleeding is a major cause of hospitalization and the most prevalent emergency worldwide, with a mortality rate of up to 14%. In Peru, there have not been any studies on the use of the Glasgow-Blatchford Scoring System to predict mortality in upper gastrointestinal bleeding. The aim of this study is to perform an external validation of the Glasgow-Blatchford Scoring System and to establish the best cutoff for predicting mortality in upper gastrointest...

  5. Hybrid ATDL-gamma distribution model for predicting area source acid gas concentrations

    Energy Technology Data Exchange (ETDEWEB)

    Jakeman, A J; Taylor, J A

    1985-01-01

    An air quality model is developed to predict the distribution of concentrations of acid gas in an urban airshed. The model is hybrid in character, combining reliable features of a deterministic ATDL-based model with statistical distributional approaches. The gamma distribution was identified from a range of distributional models as the best model. The paper shows that the assumptions of a previous hybrid model may be relaxed and presents a methodology for characterizing the uncertainty associated with model predictions. Results are demonstrated for the 98-percentile predictions of 24-h average data over annual periods at six monitoring sites. This percentile relates to the World Health Organization goal for acid gas concentrations.

  6. Acute kidney injury and renal replacement therapy independently predict mortality in neonatal and pediatric noncardiac patients on extracorporeal membrane oxygenation.

    Science.gov (United States)

    Askenazi, David J; Ambalavanan, Namasivayam; Hamilton, Kiya; Cutter, Gary; Laney, Debbie; Kaslow, Richard; Georgeson, Keith; Barnhart, Douglas C; Dimmitt, Reed A

    2011-01-01

    To determine the independent impact of acute kidney injury (AKI) and renal replacement therapy (RRT) in infants and children who receive extracorporeal membrane oxygenation. Despite continued expertise/technological advancement, patients who receive extracorporeal membrane oxygenation have high mortality. AKI and RRT portend poor outcomes independent of comorbidities and illness severity in several critically ill populations. Retrospective cohort study. The primary variables explored are AKI (categorical complication code for serum creatinine > 1.5 mg/dL or International Statistical Classification of Diseases and Related Health Problems, Revision 9 for acute renal failure), and RRT (complication/Current Procedural Terminology code for dialysis or hemofiltration). Multiple variables previously associated with mortality in this population were controlled, using logistic stepwise regression. Decision tree modeling was performed to determine optimal variables and cut points to predict mortality. Critically ill neonates (0-30 days old) and children (> 30 days but optimizing the timing/delivery of RRT may positively impact survival.

  7. Low Transvalvular Flow Rate Predicts Mortality in Patients With Low-Gradient Aortic Stenosis Following Aortic Valve Intervention.

    Science.gov (United States)

    Vamvakidou, Anastasia; Jin, Wenying; Danylenko, Oleksandr; Chahal, Navtej; Khattar, Rajdeep; Senior, Roxy

    2018-03-09

    This study aimed to assess the value of low transvalvular flow rate (FR) for the prediction of mortality compared with low stroke volume index (SVi) in patients with low-gradient (mean gradient: gradient AS who had undergone valve intervention. We retrospectively followed prospectively assessed consecutive patients with low-gradient, low aortic valve area AS who underwent aortic valve intervention between 2010 and 2014 for all-cause mortality. Of the 218 patients with mean age 75 ± 12 years, 102 (46.8%) had low stroke volume index (SVi) (gradient, low valve area aortic stenosis undergoing aortic valve intervention, low FR, not low SVi, was an independent predictor of medium-term mortality. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  8. Serum Phosphate Predicts Early Mortality among Underweight Adults Starting ART in Zambia: A Novel Context for Refeeding Syndrome?

    Science.gov (United States)

    Koethe, John R.; Blevins, Meridith; Nyirenda, Christopher K.; Kabagambe, Edmond K.; Chiasera, Janelle M.; Shepherd, Bryan E.; Zulu, Isaac; Heimburger, Douglas C.

    2013-01-01

    Background. Low body mass index (BMI) at antiretroviral therapy (ART) initiation is associated with early mortality, but the etiology is not well understood. We hypothesized that low pretreatment serum phosphate, a critical cellular metabolism intermediate primarily stored in skeletal muscle, may predict mortality within the first 12 weeks of ART. Methods. We prospectively studied 352 HIV-infected adults initiating ART in Lusaka, Zambia to estimate the odds of death for each 0.1 mmol/L decrease in baseline phosphate after adjusting for established predictors of mortality. Results. The distribution of phosphate values was similar across BMI categories (median value 1.2 mmol/L). Among the 145 participants with BMI refeeding syndrome. Further studies of cellular metabolism in this population are needed. PMID:23691292

  9. Characterization of acute-on-chronic liver failure and prediction of mortality in Asian patients with active alcoholism.

    Science.gov (United States)

    Kim, Hwi Young; Chang, Young; Park, Jae Yong; Ahn, Hongkeun; Cho, Hyeki; Han, Seung Jun; Oh, Sohee; Kim, Donghee; Jung, Yong Jin; Kim, Byeong Gwan; Lee, Kook Lae; Kim, Won

    2016-02-01

    Alcoholic liver diseases often evolve to acute-on-chronic liver failure (ACLF), which increases the risk of (multi-)organ failure and death. We investigated the development and characteristics of alcohol-related ACLF and evaluated prognostic scores for prediction of mortality in Asian patients with active alcoholism. A total of 205 patients who were hospitalized with severe alcoholic liver disease were included in this retrospective cohort study, after excluding those with serious cardiovascular diseases, malignancy, or co-existing viral hepatitis. The Chronic Liver Failure (CLIF) Consortium Organ Failure score was used in the diagnosis and grading of ACLF, and the CLIF Consortium ACLF score (CLIF-C ACLFs) was used to predict mortality. Patients with ACLF had higher Maddrey discriminant function, model for end-stage liver disease (MELD), and MELD-sodium scores than those without ACLF. Infections were more frequently documented in patients with ACLF (33.3% vs 53.0%; P = 0.004). Predictive factors for ACLF development were systemic inflammatory response syndrome (odds ratio [OR], 2.239; P alcohol-related ACLF in Asian patients with active alcoholism. The CLIF-C ACLFs may be more useful for predicting mortality in ACLF cases than liver-specific scoring systems. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  10. Usefulness of a semi-quantitative procalcitonin test and the A-DROP Japanese prognostic scale for predicting mortality among adults hospitalized with community-acquired pneumonia.

    Science.gov (United States)

    Kasamatsu, Yu; Yamaguchi, Toshimasa; Kawaguchi, Takashi; Tanaka, Nagaaki; Oka, Hiroko; Nakamura, Tomoyuki; Yamagami, Keiko; Yoshioka, Katsunobu; Imanishi, Masahito

    2012-02-01

    The solid-phase immunoassay, semi-quantitative procalcitonin (PCT) test (B R A H M S PCT-Q) can be used to rapidly categorize PCT levels into four grades. However, the usefulness of this kit for determining the prognosis of adult patients with community-acquired pneumonia (CAP) is unclear. A prospective study was conducted in two Japanese hospitals to evaluate the usefulness of this PCT test in determining the prognosis of adult patients with CAP. The accuracy of the age, dehydration, respiratory failure, orientation disturbance, pressure (A-DROP) scale proposed by the Japanese Respiratory Society for prediction of mortality due to CAP was also investigated. Hospitalized CAP patients (n = 226) were enrolled in the study. Comprehensive examinations were performed to determine PCT and CRP concentrations, disease severity based on the A-DROP, pneumonia severity index (PSI) and confusion, urea, respiratory rate, blood pressure, age ≥65 (CURB-65) scales and the causative pathogens. The usefulness of the biomarkers and prognostic scales for predicting each outcome were then examined. Twenty of the 170 eligible patients died. PCT levels were strongly positively correlated with PSI (ρ = 0.56, P scale were found to be useful for predicting mortality in adult patients with CAP. © 2011 The Authors. Respirology © 2011 Asian Pacific Society of Respirology.

  11. Biodynamic modelling and the prediction of accumulated trace metal concentrations in the polychaete Arenicola marina

    International Nuclear Information System (INIS)

    Casado-Martinez, M. Carmen; Smith, Brian D.; DelValls, T. Angel; Luoma, Samuel N.; Rainbow, Philip S.

    2009-01-01

    The use of biodynamic models to understand metal uptake directly from sediments by deposit-feeding organisms still represents a special challenge. In this study, accumulated concentrations of Cd, Zn and Ag predicted by biodynamic modelling in the lugworm Arenicola marina have been compared to measured concentrations in field populations in several UK estuaries. The biodynamic model predicted accumulated field Cd concentrations remarkably accurately, and predicted bioaccumulated Ag concentrations were in the range of those measured in lugworms collected from the field. For Zn the model showed less but still good comparability, accurately predicting Zn bioaccumulation in A. marina at high sediment concentrations but underestimating accumulated Zn in the worms from sites with low and intermediate levels of Zn sediment contamination. Therefore, it appears that the physiological parameters experimentally derived for A. marina are applicable to the conditions encountered in these environments and that the assumptions made in the model are plausible. - Biodynamic modelling predicts accumulated field concentrations of Ag, Cd and Zn in the deposit-feeding polychaete Arenicola marina.

  12. Diagnostic performance of initial serum albumin level for predicting in-hospital mortality among aspiration pneumonia patients.

    Science.gov (United States)

    Kim, Hyosun; Jo, Sion; Lee, Jae Baek; Jin, Youngho; Jeong, Taeoh; Yoon, Jaechol; Lee, Jeong Moon; Park, Boyoung

    2018-01-01

    The predictive value of serum albumin in adult aspiration pneumonia patients remains unknown. Using data collected during a 3-year retrospective cohort of hospitalized adult patients with aspiration pneumonia, we evaluated the predictive value of serum albumin level at ED presentation for in-hospital mortality. 248 Patients were enrolled; of these, 51 cases died (20.6%). The mean serum albumin level was 3.4±0.7g/dL and serum albumin levels were significantly lower in the non-survivor group than in the survivor group (3.0±0.6g/dL vs. 3.5±0.6g/dL). In the multivariable logistic regression model, albumin was associated with in-hospital mortality significantly (adjusted odds ratio 0.30, 95% confidential interval (CI) 0.16-0.57). The area under the receiver operating characteristics (AUROC) for in-hospital survival was 0.72 (95% CI 0.64-0.80). The Youden index was 3.2g/dL and corresponding sensitivity, specificity, positive predictive value, negative predictive value, positive and negative likelihood ratio were 68.6%, 66.5%, 34.7%, 89.1%, 2.05 and 0.47, respectively. High sensitivity (98.0%) was shown at albumin level of 4.0g/dL and high specificity (94.9%) was shown at level of 2.5g/dL. Initial serum albumin levels were independently associated with in-hospital mortality among adult patients hospitalized with aspiration pneumonia and demonstrated fair discriminative performance in the prediction of in-hospital mortality. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. The Low Fall as a Surrogate Marker of Frailty Predicts Long-Term Mortality in Older Trauma Patients.

    Directory of Open Access Journals (Sweden)

    Ting Hway Wong

    Full Text Available Frailty is associated with adverse outcomes including disability, mortality and risk of falls. Trauma registries capture a broad range of injuries. However, frail patients who fall comprise a large proportion of the injuries occurring in ageing populations and are likely to have different outcomes compared to non-frail injured patients. The effect of frail fallers on mortality is under-explored but potentially significant. Currently, many trauma registries define low falls as less than three metres, a height that is likely to include non-frailty falls. We hypothesized that the low fall from less than 0.5 metres, including same-level falls, is a surrogate marker of frailty and predicts long-term mortality in older trauma patients.Using data from the Singapore National Trauma Registry, 2011-2013, matched till September 2014 to the death registry, we analysed adults aged over 45 admitted via the emergency department in public hospitals sustaining blunt injuries with an injury severity score (ISS of 9 or more, excluding isolated hip fractures from same-level falls in the over 65. Patients injured by a low fall were compared to patients injured by high fall and other blunt mechanisms. Logistic regression was used to analyze 12-month mortality, controlling for mechanism of injury, ISS, revised trauma score (RTS, co-morbidities, gender, age and age-gender interaction. Different low fall height definitions, adjusting for injury regions, and analyzing the entire adult cohort were used in sensitivity analyses and did not change our findings.Of the 8111 adults in our cohort, patients who suffered low falls were more likely to die of causes unrelated to their injuries (p<0.001, compared to other blunt trauma and higher fall heights. They were at higher risk of 12-month mortality (OR 1.75, 95% CI 1.18-2.58, p = 0.005, independent of ISS, RTS, age, gender, age-gender interaction and co-morbidities. Falls that were higher than 0.5m did not show this pattern

  14. Nutritional parameters predicting pressure ulcers and short-term mortality in patients with minimal conscious state as a result of traumatic and non-traumatic acquired brain injury.

    Science.gov (United States)

    Montalcini, Tiziana; Moraca, Marta; Ferro, Yvelise; Romeo, Stefano; Serra, Sebastiano; Raso, Maria Girolama; Rossi, Francesco; Sannita, Walter G; Dolce, Giuliano; Pujia, Arturo

    2015-09-17

    The association between malnutrition and worse outcomes as pressure ulcers and mortality is well established in a variety of setting. Currently none investigation was conducted in patients with long-term consequences of the acquired brain injury in which recovery from brain injury could be influenced by secondary complications. The aim of this study was to investigate the association between various nutritional status parameters (in particular albumin) and pressure ulcers formation and short-term mortality in minimal conscious state patients. In this prospective, observational study of 5-months duration, a 30 patients sample admitted to a Neurological Institute was considered. All patients underwent a complete medical examination. Anthropometric parameters like mid-arm circumference and mid-arm muscle circumference and nutritional parameters as serum albumin and blood hemoglobin concentration were assessed. At univariate and logistic regression analysis, mid-arm circumference (p = 0.04; beta = -0.89), mid-arm muscle circumference (p = 0.050; beta = -1.29), hemoglobin (p = 0.04, beta -1.1) and albumin (p = 0.04, beta -7.91) were inversely associated with pressure ulcers. The area under the ROC curve for albumin to predict sores was 0.76 (p = 0.02) and mortality was 0.83 (p = 0.03). Patient with lower albumin had significantly higher short-term mortality than those with higher serum albumin (p = 0.03; χ(2) test = 6.47). Albumin, haemoglobin and mid-arm circumference are inversely associated with pressure ulcers. Albumin is a prognostic index in MCS patients. Since albumin and haemoglobin could be affected by a variety of factors, this association suggests to optimize nutrition and investigate on other mechanism leading to mortality and pressure ulcers.

  15. Worldwide trends in gastric cancer mortality (1980-2011), with predictions to 2015, and incidence by subtype.

    Science.gov (United States)

    Ferro, Ana; Peleteiro, Bárbara; Malvezzi, Matteo; Bosetti, Cristina; Bertuccio, Paola; Levi, Fabio; Negri, Eva; La Vecchia, Carlo; Lunet, Nuno

    2014-05-01

    Gastric cancer incidence and mortality decreased substantially over the last decades in most countries worldwide, with differences in the trends and distribution of the main topographies across regions. To monitor recent mortality trends (1980-2011) and to compute short-term predictions (2015) of gastric cancer mortality in selected countries worldwide, we analysed mortality data provided by the World Health Organization. We also analysed incidence of cardia and non-cardia cancers using data from Cancer Incidence in Five Continents (2003-2007). The joinpoint regression over the most recent calendar periods gave estimated annual percent changes (EAPC) around -3% for the European Union (EU) and major European countries, as well as in Japan and Korea, and around -2% in North America and major Latin American countries. In the United States of America (USA), EU and other major countries worldwide, the EAPC, however, were lower than in previous years. The predictions for 2015 show that a levelling off of rates is expected in the USA and a few other countries. The relative contribution of cardia and non-cardia gastric cancers to the overall number of cases varies widely, with a generally higher proportion of cardia cancers in countries with lower gastric cancer incidence and mortality rates (e.g. the USA, Canada and Denmark). Despite the favourable mortality trends worldwide, in some countries the declines are becoming less marked. There still is the need to control Helicobacter pylori infection and other risk factors, as well as to improve diagnosis and management, to further reduce the burden of gastric cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Symptoms of depression and anxiety predict mortality in patients undergoing oral anticoagulation: Results from the thrombEVAL study program.

    Science.gov (United States)

    Michal, Matthias; Prochaska, Jürgen H; Keller, Karsten; Göbel, Sebastian; Coldewey, Meike; Ullmann, Alexander; Schulz, Andreas; Lamparter, Heidrun; Münzel, Thomas; Reiner, Iris; Beutel, Manfred E; Wild, Philipp S

    2015-01-01

    Depression and anxiety are highly prevalent in cardiovascular patients. Therefore, we examined whether the 4-item Patient Health Questionnaire (PHQ-4, measuring symptoms of depression and anxiety) predicts all-cause mortality in outpatients with long-term oral anticoagulation (OAC). The sample comprised n=1384 outpatients from a regular medical care setting receiving long-term OAC with vitamin K antagonists. At baseline, symptoms of anxiety and depression were assessed with the PHQ-4 and the past medical history was taken. The outcome was all-cause mortality in the 24 month observation period. The median follow-up time was 13.3 months. N=191 patients from n=1384 died (death rate 13.8%). Each point increase in the PHQ-4 score was associated with a 10% increase in mortality (hazard ratio [HR] 1.10, 95% confidence interval [95% CI] 1.05-1.16) after adjustment for age, sex, high school graduation, partnership, smoking, obesity, frailty according to the Barthel Index, Charlson Comorbidity Index and CHA2DS2-VASc score. The depression component (PHQ-2) increased mortality by 22% and anxiety (GAD-2) by 11% respectively. Neither medical history of any mental disorder, nor intake of antidepressants, anxiolytics or hypnotics predicted excess mortality. Elevated symptoms of depression and, to a lesser degree, symptoms of anxiety are independently associated with all-cause mortality in OAC outpatients. The PHQ-4 questionnaire provides valuable prognostic information. These findings emphasize the need for implementing regular screening procedures and the development and evaluation of appropriate psychosocial treatment approaches for OAC patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  17. Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

    Science.gov (United States)

    Aksoy, A.; Yuzugullu, O.

    2017-12-01

    Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

  18. Uric acid predicts mortality and ischaemic stroke in subjects with diastolic dysfunction: the Tromsø Study 1994-2013.

    Science.gov (United States)

    Norvik, Jon V; Schirmer, Henrik; Ytrehus, Kirsti; Storhaug, Hilde M; Jenssen, Trond G; Eriksen, Bjørn O; Mathiesen, Ellisiv B; Løchen, Maja-Lisa; Wilsgaard, Tom; Solbu, Marit D

    2017-05-01

    To investigate whether serum uric acid predicts adverse outcomes in persons with indices of diastolic dysfunction in a general population. We performed a prospective cohort study among 1460 women and 1480 men from 1994 to 2013. Endpoints were all-cause mortality, incident myocardial infarction, and incident ischaemic stroke. We stratified the analyses by echocardiographic markers of diastolic dysfunction, and uric acid was the independent variable of interest. Hazard ratios (HR) were estimated per 59 μmol/L increase in baseline uric acid. Multivariable adjusted Cox proportional hazards models showed that uric acid predicted all-cause mortality in subjects with E/A ratio 1.5 (HR 1.51, 95% CI 1.09-2.09, P for interaction between E/A ratio category and uric acid = 0.02). Elevated uric acid increased mortality risk in persons with E-wave deceleration time 220 ms (HR 1.46, 95% CI 1.01-2.12 and HR 1.13, 95% CI 1.02-1.26, respectively; P for interaction = 0.04). Furthermore, in participants with isovolumetric relaxation time ≤60 ms, mortality risk was higher with increasing uric acid (HR 4.98, 95% CI 2.02-12.26, P for interaction = 0.004). Finally, elevated uric acid predicted ischaemic stroke in subjects with severely enlarged left atria (HR 1.62, 95% CI 1.03-2.53, P for interaction = 0.047). Increased uric acid was associated with higher all-cause mortality risk in subjects with echocardiographic indices of diastolic dysfunction, and with higher ischaemic stroke risk in persons with severely enlarged left atria.

  19. Development and validation of a predictive risk model for all-cause mortality in type 2 diabetes.

    Science.gov (United States)

    Robinson, Tom E; Elley, C Raina; Kenealy, Tim; Drury, Paul L

    2015-06-01

    Type 2 diabetes is common and is associated with an approximate 80% increase in the rate of mortality. Management decisions may be assisted by an estimate of the patient's absolute risk of adverse outcomes, including death. This study aimed to derive a predictive risk model for all-cause mortality in type 2 diabetes. We used primary care data from a large national multi-ethnic cohort of patients with type 2 diabetes in New Zealand and linked mortality records to develop a predictive risk model for 5-year risk of mortality. We then validated this model using information from a separate cohort of patients with type 2 diabetes. 26,864 people were included in the development cohort with a median follow up time of 9.1 years. We developed three models initially using demographic information and then progressively more clinical detail. The final model, which also included markers of renal disease, proved to give best prediction of all-cause mortality with a C-statistic of 0.80 in the development cohort and 0.79 in the validation cohort (7610 people) and was well calibrated. Ethnicity was a major factor with hazard ratios of 1.37 for indigenous Maori, 0.41 for East Asian and 0.55 for Indo Asian compared with European (P<0.001). We have developed a model using information usually available in primary care that provides good assessment of patient's risk of death. Results are similar to models previously published from smaller cohorts in other countries and apply to a wider range of patient ethnic groups. Copyright © 2015. Published by Elsevier Ireland Ltd.

  20. Serum Phosphate Predicts Early Mortality among Underweight Adults Starting ART in Zambia: A Novel Context for Refeeding Syndrome?

    Directory of Open Access Journals (Sweden)

    John R. Koethe

    2013-01-01

    Full Text Available Background. Low body mass index (BMI at antiretroviral therapy (ART initiation is associated with early mortality, but the etiology is not well understood. We hypothesized that low pretreatment serum phosphate, a critical cellular metabolism intermediate primarily stored in skeletal muscle, may predict mortality within the first 12 weeks of ART. Methods. We prospectively studied 352 HIV-infected adults initiating ART in Lusaka, Zambia to estimate the odds of death for each 0.1 mmol/L decrease in baseline phosphate after adjusting for established predictors of mortality. Results. The distribution of phosphate values was similar across BMI categories (median value 1.2 mmol/L. Among the 145 participants with BMI <18.5 kg/m2, 28 (19% died within 12 weeks. Lower pretreatment serum phosphate was associated with increased mortality (odds ratio (OR 1.24 per 0.1 mmol/L decrement, 95% CI: 1.05 to 1.47; P=0.01 after adjusting for sex, age, and CD4+ lymphocyte count. A similar relationship was not observed among participants with BMI ≥18.5 kg/m2 (OR 0.96, 95% CI: 0.76 to 1.21; P=0.74. Conclusions. The association of low pretreatment serum phosphate level and early ART mortality among undernourished individuals may represent a variant of the refeeding syndrome. Further studies of cellular metabolism in this population are needed.

  1. Alternative Measures of Self-Rated Health for Predicting Mortality Among Older People: Is Past or Future Orientation More Important?

    Science.gov (United States)

    Ferraro, Kenneth F; Wilkinson, Lindsay R

    2015-10-01

    The purpose of this study was to compare the prognostic validity of alternative measures of health ratings, including those that tap temporal reflections, on adult mortality. The study uses a national sample of 1,266 Americans 50-74 years old in 1995, with vital status tracked through 2005, to compare the effect of 3 types of health ratings on mortality: conventional indicator of self-rated health (SRH), age comparison form of SRH, and health ratings that incorporate temporal dimensions. Logistic regression was used to estimate the odds of mortality associated with alternative health ratings while adjusting for health conditions, lifestyle factors, and status characteristics and resources. Self-rated health was a consistent predictor of mortality, but the respondent's expected health rating-10 years in the future-was an independent predictor. Future health expectations were more important than past (recalled change) in predicting mortality risk: People with more negative expectations of future health were less likely to survive. The findings reveal the importance of future time perspective for older people and suggest that it is more useful to query older people about their future health expectations than about how their health has changed. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  2. Heart Rate Variability Density Analysis (Dyx) and Prediction of Long-Term Mortality after Acute Myocardial Infarction

    DEFF Research Database (Denmark)

    Jørgensen, Rikke Mørch; Abildstrøm, Steen Z; Levitan, Jacob

    2016-01-01

    AIMS: The density HRV parameter Dyx is a new heart rate variability (HRV) measure based on multipole analysis of the Poincaré plot obtained from RR interval time series, deriving information from both the time and frequency domain. Preliminary results have suggested that the parameter may provide...... new predictive information on mortality in survivors of acute myocardial infarction (MI). This study compares the prognostic significance of Dyx to that of traditional linear and nonlinear measures of HRV. METHODS AND RESULTS: In the Nordic ICD pilot study, patients with an acute MI were screened...... with 2D echocardiography and 24-hour Holter recordings. The study was designed to assess the power of several HRV measures to predict mortality. Dyx was tested in a subset of 206 consecutive Danish patients with analysable Holter recordings. After a median follow-up of 8.5 years 70 patients had died...

  3. Music therapy-induced changes in salivary cortisol level are predictive of cardiovascular mortality in patients under maintenance hemodialysis.

    Science.gov (United States)

    Hou, Yi-Chou; Lin, Yen-Ju; Lu, Kuo-Cheng; Chiang, Han-Sun; Chang, Chia-Chi; Yang, Li-King

    2017-01-01

    Music therapy has been applied in hemodialysis (HD) patients for relieving mental stress. Whether the stress-relieving effect by music therapy is predictive of clinical outcome in HD patients is still unclear. We recruited a convenience sample of 99 patients on maintenance HD and randomly assigned them to the experimental (n=49) or control (n=50) group. The experimental group received relaxing music therapy for 1 week, whereas the control group received no music therapy. In the experimental group, we compared cardiovascular mortality in the patients with and without cortisol changes. The salivary cortisol level was lowered after 1 week of music therapy in the experimental group (-2.41±3.08 vs 1.66±2.11 pg/mL, P 0.6 pg/mL (83.8% vs 63.6%, P predict cardiovascular mortality in patients under maintenance HD.

  4. The Impact of climate change on heat-related mortality in six major cities, South Korea, under representative concentration pathways (RCPs

    Directory of Open Access Journals (Sweden)

    Youngmin eKim

    2014-02-01

    Full Text Available Background: We aimed to quantify the excess mortality associated with increased temperature due to climate change in six major Korean cities under Representative Concentration Pathways (RCPs which are new emission scenarios designed for the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC. Methods: We first examined the association between daily mean temperature and mortality in each during the summertime (June to September from 2001 to 2008. This was done using a generalized linear Poisson model with adjustment for a long-term time trend, relative humidity, air pollutants, and day of the week. We then computed heat-related mortality attributable to future climate change using estimated mortality risks, projected future populations, and temperature increments for both future years 2041-2070 and 2071-2100 under RCP 4.5 and 8.5. We considered effects from added days with high temperatures over thresholds and shifted effects from high to higher temperature.Results: Estimated excess all-cause mortalities for six cities in Korea ranged from 500 (95% CI: 313-703 for 2041-2070 to 2,320 (95% CI: 1,430-3,281 deaths per year for 2071-2100 under two RCPs. Excess cardiovascular mortality was estimated to range from 192 (95% CI: 41-351 to 896 (95% CI: 185-1,694 deaths per year, covering about 38.5% of all-cause excess mortality. Increased rates of heat-related mortality were higher in cities located at relatively lower latitude than cities with higher latitude. Estimated excess mortality under RCP 8.5, a fossil fuel-intensive emission scenario, was more than twice as high compared with RCP 4.5, low to medium emission scenario.Conclusions: Excess mortality due to climate change is expected to be profound in the future showing spatial variation. Efforts to mitigate climate change can cause substantial health benefits via reducing heat-related mortality.

  5. Adipose tissue and muscle attenuation as novel biomarkers predicting mortality in patients with extremity sarcomas

    International Nuclear Information System (INIS)

    Veld, Joyce; Vossen, Josephina A.; Torriani, Martin; Bredella, Miriam A.; De Amorim Bernstein, Karen; Halpern, Elkan F.

    2016-01-01

    To assess CT-attenuation of abdominal adipose tissue and psoas muscle as predictors of mortality in patients with sarcomas of the extremities. Our study was IRB approved and HIPAA compliant. The study group comprised 135 patients with history of extremity sarcoma (mean age: 53 ± 17 years) who underwent whole body PET/CT. Abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle attenuation (HU) was assessed on non-contrast, attenuation-correction CT. Clinical information including survival, tumour stage, sarcoma type, therapy and pre-existing comorbidities were recorded. Cox proportional hazard models were used to determine longitudinal associations between adipose tissue and muscle attenuation and mortality. There were 47 deaths over a mean follow-up period of 20 ± 17 months. Higher SAT and lower psoas attenuation were associated with increased mortality (p = 0.03 and p = 0.005, respectively), which remained significant after adjustment for age, BMI, sex, tumor stage, therapy, and comorbidities (p = 0.002 and p = 0.02, respectively). VAT attenuation was not associated with mortality. Attenuation of SAT and psoas muscle, assessed on non-contrast CT, are predictors of mortality in patients with extremity sarcomas, independent of other established prognostic factors, suggesting that adipose tissue and muscle attenuation could serve as novel biomarkers for mortality in patients with sarcomas. (orig.)

  6. Adipose tissue and muscle attenuation as novel biomarkers predicting mortality in patients with extremity sarcomas

    Energy Technology Data Exchange (ETDEWEB)

    Veld, Joyce; Vossen, Josephina A.; Torriani, Martin; Bredella, Miriam A. [Massachusetts General Hospital and Harvard Medical School, Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Boston, MA (United States); De Amorim Bernstein, Karen [Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Francis H Burr Proton Therapy Center, Boston, MA (United States); Halpern, Elkan F. [Massachusetts General Hospital and Harvard Medical School, Institute of Technology Assessment, Boston, MA (United States)

    2016-12-15

    To assess CT-attenuation of abdominal adipose tissue and psoas muscle as predictors of mortality in patients with sarcomas of the extremities. Our study was IRB approved and HIPAA compliant. The study group comprised 135 patients with history of extremity sarcoma (mean age: 53 ± 17 years) who underwent whole body PET/CT. Abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle attenuation (HU) was assessed on non-contrast, attenuation-correction CT. Clinical information including survival, tumour stage, sarcoma type, therapy and pre-existing comorbidities were recorded. Cox proportional hazard models were used to determine longitudinal associations between adipose tissue and muscle attenuation and mortality. There were 47 deaths over a mean follow-up period of 20 ± 17 months. Higher SAT and lower psoas attenuation were associated with increased mortality (p = 0.03 and p = 0.005, respectively), which remained significant after adjustment for age, BMI, sex, tumor stage, therapy, and comorbidities (p = 0.002 and p = 0.02, respectively). VAT attenuation was not associated with mortality. Attenuation of SAT and psoas muscle, assessed on non-contrast CT, are predictors of mortality in patients with extremity sarcomas, independent of other established prognostic factors, suggesting that adipose tissue and muscle attenuation could serve as novel biomarkers for mortality in patients with sarcomas. (orig.)

  7. Use of Life Course Work–Family Profiles to Predict Mortality Risk Among US Women

    Science.gov (United States)

    Guevara, Ivan Mejía; Glymour, M. Maria; Berkman, Lisa F.

    2015-01-01

    Objectives. We examined relationships between US women’s exposure to midlife work–family demands and subsequent mortality risk. Methods. We used data from women born 1935 to 1956 in the Health and Retirement Study to calculate employment, marital, and parenthood statuses for each age between 16 and 50 years. We used sequence analysis to identify 7 prototypical work–family trajectories. We calculated age-standardized mortality rates and hazard ratios (HRs) for mortality associated with work–family sequences, with adjustment for covariates and potentially explanatory later-life factors. Results. Married women staying home with children briefly before reentering the workforce had the lowest mortality rates. In comparison, after adjustment for age, race/ethnicity, and education, HRs for mortality were 2.14 (95% confidence interval [CI] = 1.58, 2.90) among single nonworking mothers, 1.48 (95% CI = 1.06, 1.98) among single working mothers, and 1.36 (95% CI = 1.02, 1.80) among married nonworking mothers. Adjustment for later-life behavioral and economic factors partially attenuated risks. Conclusions. Sequence analysis is a promising exposure assessment tool for life course research. This method permitted identification of certain lifetime work–family profiles associated with mortality risk before age 75 years. PMID:25713976

  8. High levels of cynical distrust partly predict premature mortality in middle-aged to ageing men.

    Science.gov (United States)

    Šmigelskas, Kastytis; Joffė, Roza; Jonynienė, Jolita; Julkunen, Juhani; Kauhanen, Jussi

    2017-08-01

    The aim of this study was to evaluate the effect of cynical distrust on mortality in middle-aged and aging men. The analysis is based on Kuopio Ischemic Heart Disease study, follow-up from 1984 to 2011. Sample consisted of 2682 men, aged 42-61 years at baseline. Data on mortality was provided by the National Death Registry, causes of death were classified by the National Center of Statistics of Finland. Cynical distrust was measured at baseline using Cynical Distrust Scale. Survival analyses were conducted using Cox regression models. In crude estimates after 28 years of follow-up, high cynical distrust was associated with 1.5-1.7 higher hazards for earlier death compared to low cynical distrust. Adjusted for conventional risk factors, high cynical distrust was significantly associated regarding CVD-free men and CVD mortality, while non-CVD mortality in study sample was consistently but not significantly associated. The risk effects were more expressed after 12-20 years rather than in earlier or later follow-up. To conclude, high cynical distrust associates with increased risk of CVD mortality in CVD-free men. The associations with non-CVD mortality are weaker and not reach statistical significance.

  9. Bone mineral density at the hip predicts mortality in elderly men.

    Science.gov (United States)

    Trivedi, D P; Khaw, K T

    2001-01-01

    Low bone density as assessed by calcaneal ultrasound has been associated with mortality in elderly men and women. We examined the relationship between bone density measured at the hip and all cause and cardiovascular mortality in elderly men. Men aged 65-76 years from the general community were recruited from general practices in Cambridge between 1991 and 1995. At baseline survey, data collection included health questionnaires, measures of anthropometry and cardiovascular risk factors, as well as bone mineral density (BMD) measured using dual energy X-ray absorptiometry. All men have been followed up for vital status up to December 1999. BMD was significantly inversely related to mortality from all causes and cardiovascular disease, with decreasing rates with increasing bone density quartile, and an approximate halving of risk between the bottom and top quartile (p risk (95% CI 0.66-0.91) for all-cause mortality and 0.76 relative risk (95% CI 0.62-0.93) for cardiovascular disease mortality. The association remained significant after adjusting for age, body mass index, cigarette smoking status, serum cholesterol, systolic blood pressure, past history of heart attack, stroke or cancer and other lifestyle factors which included use of alcohol, physical activity and general health status. Low bone density at the hip is thus a strong and independent predictor of all-cause and cardiovascular mortality in older men.

  10. Use of life course work-family profiles to predict mortality risk among US women.

    Science.gov (United States)

    Sabbath, Erika L; Guevara, Ivan Mejía; Glymour, M Maria; Berkman, Lisa F

    2015-04-01

    We examined relationships between US women's exposure to midlife work-family demands and subsequent mortality risk. We used data from women born 1935 to 1956 in the Health and Retirement Study to calculate employment, marital, and parenthood statuses for each age between 16 and 50 years. We used sequence analysis to identify 7 prototypical work-family trajectories. We calculated age-standardized mortality rates and hazard ratios (HRs) for mortality associated with work-family sequences, with adjustment for covariates and potentially explanatory later-life factors. Married women staying home with children briefly before reentering the workforce had the lowest mortality rates. In comparison, after adjustment for age, race/ethnicity, and education, HRs for mortality were 2.14 (95% confidence interval [CI] = 1.58, 2.90) among single nonworking mothers, 1.48 (95% CI = 1.06, 1.98) among single working mothers, and 1.36 (95% CI = 1.02, 1.80) among married nonworking mothers. Adjustment for later-life behavioral and economic factors partially attenuated risks. Sequence analysis is a promising exposure assessment tool for life course research. This method permitted identification of certain lifetime work-family profiles associated with mortality risk before age 75 years.

  11. Diet Quality Scores and Prediction of All-Cause, Cardiovascular and Cancer Mortality in a Pan-European Cohort Study.

    Directory of Open Access Journals (Sweden)

    Camille Lassale

    Full Text Available Scores of overall diet quality have received increasing attention in relation to disease aetiology; however, their value in risk prediction has been little examined. The objective was to assess and compare the association and predictive performance of 10 diet quality scores on 10-year risk of all-cause, CVD and cancer mortality in 451,256 healthy participants to the European Prospective Investigation into Cancer and Nutrition, followed-up for a median of 12.8y. All dietary scores studied showed significant inverse associations with all outcomes. The range of HRs (95% CI in the top vs. lowest quartile of dietary scores in a composite model including non-invasive factors (age, sex, smoking, body mass index, education, physical activity and study centre was 0.75 (0.72-0.79 to 0.88 (0.84-0.92 for all-cause, 0.76 (0.69-0.83 to 0.84 (0.76-0.92 for CVD and 0.78 (0.73-0.83 to 0.91 (0.85-0.97 for cancer mortality. Models with dietary scores alone showed low discrimination, but composite models also including age, sex and other non-invasive factors showed good discrimination and calibration, which varied little between different diet scores examined. Mean C-statistic of full models was 0.73, 0.80 and 0.71 for all-cause, CVD and cancer mortality. Dietary scores have poor predictive performance for 10-year mortality risk when used in isolation but display good predictive ability in combination with other non-invasive common risk factors.

  12. Echocardiographic findings predict in-hospital and 1-year mortality in left-sided native valve Staphylococcus aureus endocarditis

    DEFF Research Database (Denmark)

    Lauridsen, Trine K.; Park, Lawrence; Tong, Steven Y C

    2015-01-01

    BACKGROUND: Staphylococcus aureus left-sided native valve infective endocarditis (LNVIE) has higher complication and mortality rates compared with endocarditis from other pathogens. Whether echocardiographic variables can predict prognosis in S aureus LNVIE is unknown. METHODS AND RESULTS......: Consecutive patients with LNVIE, enrolled between January 2000 and September 2006, in the International Collaboration on Endocarditis were identified. Subjects without S aureus IE were matched to those with S aureus IE by the propensity of having S aureus. Survival differences were determined using log...

  13. Short Term Prediction of PM10 Concentrations Using Seasonal Time Series Analysis

    Directory of Open Access Journals (Sweden)

    Hamid Hazrul Abdul

    2016-01-01

    Full Text Available Air pollution modelling is one of an important tool that usually used to make short term and long term prediction. Since air pollution gives a big impact especially to human health, prediction of air pollutants concentration is needed to help the local authorities to give an early warning to people who are in risk of acute and chronic health effects from air pollution. Finding the best time series model would allow prediction to be made accurately. This research was carried out to find the best time series model to predict the PM10 concentrations in Nilai, Negeri Sembilan, Malaysia. By considering two seasons which is wet season (north east monsoon and dry season (south west monsoon, seasonal autoregressive integrated moving average model were used to find the most suitable model to predict the PM10 concentrations in Nilai, Negeri Sembilan by using three error measures. Based on AIC statistics, results show that ARIMA (1, 1, 1 × (1, 0, 012 is the most suitable model to predict PM10 concentrations in Nilai, Negeri Sembilan.

  14. The sequential trauma score - a new instrument for the sequential mortality prediction in major trauma*

    Directory of Open Access Journals (Sweden)

    Huber-Wagner S

    2010-05-01

    Full Text Available Abstract Background There are several well established scores for the assessment of the prognosis of major trauma patients that all have in common that they can be calculated at the earliest during intensive care unit stay. We intended to develop a sequential trauma score (STS that allows prognosis at several early stages based on the information that is available at a particular time. Study design In a retrospective, multicenter study using data derived from the Trauma Registry of the German Trauma Society (2002-2006, we identified the most relevant prognostic factors from the patients basic data (P, prehospital phase (A, early (B1, and late (B2 trauma room phase. Univariate and logistic regression models as well as score quality criteria and the explanatory power have been calculated. Results A total of 2,354 patients with complete data were identified. From the patients basic data (P, logistic regression showed that age was a significant predictor of survival (AUCmodel p, area under the curve = 0.63. Logistic regression of the prehospital data (A showed that blood pressure, pulse rate, Glasgow coma scale (GCS, and anisocoria were significant predictors (AUCmodel A = 0.76; AUCmodel P + A = 0.82. Logistic regression of the early trauma room phase (B1 showed that peripheral oxygen saturation, GCS, anisocoria, base excess, and thromboplastin time to be significant predictors of survival (AUCmodel B1 = 0.78; AUCmodel P +A + B1 = 0.85. Multivariate analysis of the late trauma room phase (B2 detected cardiac massage, abbreviated injury score (AIS of the head ≥ 3, the maximum AIS, the need for transfusion or massive blood transfusion, to be the most important predictors (AUCmodel B2 = 0.84; AUCfinal model P + A + B1 + B2 = 0.90. The explanatory power - a tool for the assessment of the relative impact of each segment to mortality - is 25% for P, 7% for A, 17% for B1 and 51% for B2. A spreadsheet for the easy calculation of the sequential trauma

  15. High serum uric acid concentration predicts poor survival in patients with breast cancer.

    Science.gov (United States)

    Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

    2017-10-01

    Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Assessment of performance and utility of mortality prediction models in a single Indian mixed tertiary intensive care unit.

    Science.gov (United States)

    Sathe, Prachee M; Bapat, Sharda N

    2014-01-01

    To assess the performance and utility of two mortality prediction models viz. Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) in a single Indian mixed tertiary intensive care unit (ICU). Secondary objectives were bench-marking and setting a base line for research. In this observational cohort, data needed for calculation of both scores were prospectively collected for all consecutive admissions to 28-bedded ICU in the year 2011. After excluding readmissions, discharges within 24 h and age <18 years, the records of 1543 patients were analyzed using appropriate statistical methods. Both models overpredicted mortality in this cohort [standardized mortality ratio (SMR) 0.88 ± 0.05 and 0.95 ± 0.06 using APACHE II and SAPS II respectively]. Patterns of predicted mortality had strong association with true mortality (R (2) = 0.98 for APACHE II and R (2) = 0.99 for SAPS II). Both models performed poorly in formal Hosmer-Lemeshow goodness-of-fit testing (Chi-square = 12.8 (P = 0.03) for APACHE II, Chi-square = 26.6 (P = 0.001) for SAPS II) but showed good discrimination (area under receiver operating characteristic curve 0.86 ± 0.013 SE (P < 0.001) and 0.83 ± 0.013 SE (P < 0.001) for APACHE II and SAPS II, respectively). There were wide variations in SMRs calculated for subgroups based on International Classification of Disease, 10(th) edition (standard deviation ± 0.27 for APACHE II and 0.30 for SAPS II). Lack of fit of data to the models and wide variation in SMRs in subgroups put a limitation on utility of these models as tools for assessing quality of care and comparing performances of different units without customization. Considering comparable performance and simplicity of use, efforts should be made to adapt SAPS II.

  17. Comparison of severity of illness scoring systems in the prediction of hospital mortality in severe sepsis and septic shock

    Directory of Open Access Journals (Sweden)

    Crowe Colleen

    2010-01-01

    Full Text Available Background : New scoring systems, including the Rapid Emergency Medicine Score (REMS, the Mortality in Emergency Department Sepsis (MEDS score, and the confusion, urea nitrogen, respiratory rate, blood pressure, 65 years and older (CURB-65 score, have been developed for emergency department (ED use in various patient populations. Increasing use of early goal directed therapy (EGDT for the emergent treatment of sepsis introduces a growing population of patients in which the accuracy of these scoring systems has not been widely examined. Objectives : To evaluate the ability of the REMS, MEDS score, and CURB-65 score to predict mortality in septic patients treated with modified EGDT. Materials and Methods : Secondary analysis of data from prospectively identified patients treated with modified EGDT in a large tertiary care suburban community hospital with over 85,000 ED visits annually and 700 inpatient beds, from May 2007 through May 2008. We included all patients with severe sepsis or septic shock, who were treated with our modified EGDT protocol. Our major outcome was in-hospital mortality. The performance of the scores was compared by area under the ROC curves (AUCs. Results : A total of 216 patients with severe sepsis or septic shock were treated with modified EGDT during the study period. Overall mortality was 32.9%. Calculated AUCs were 0.74 [95% confidence interval (CI: 0.67-0.81] for the MEDS score, 0.62 (95% CI: 0.54-0.69 for the REMS, and 0.59 (95% CI: 0.51-0.67 for the CURB-65 score. Conclusion : We found that all three ED-based systems for scoring severity of illness had low to moderate predictive capability. The MEDS score demonstrated the largest AUC of the studied scoring systems for the outcome of mortality, although the CIs on point estimates of the AUC of the REMS and CURB-65 scores all overlap.

  18. Index to Predict In-hospital Mortality in Older Adults after Non-traumatic Emergency Department Intubations

    Directory of Open Access Journals (Sweden)

    Kei Ouchi

    2017-04-01

    Full Text Available Introduction: Our goal was to develop and validate an index to predict in-hospital mortality in older adults after non-traumatic emergency department (ED intubations. Methods: We used Vizient administrative data from hospitalizations of 22,374 adults ≥75 years who underwent non-traumatic ED intubation from 2008–2015 at nearly 300 U.S. hospitals to develop and validate an index to predict in-hospital mortality. We randomly selected one half of participants for the development cohort and one half for the validation cohort. Considering 25 potential predictors, we developed a multivariable logistic regression model using least absolute shrinkage and selection operator method to determine factors associated with in-hospital mortality. We calculated risk scores using points derived from the final model’s beta coefficients. To evaluate calibration and discrimination of the final model, we used Hosmer-Lemeshow chi-square test and receiver-operating characteristic analysis and compared mortality by risk groups in the development and validation cohorts. Results: Death during the index hospitalization occurred in 40% of cases. The final model included six variables: history of myocardial infarction, history of cerebrovascular disease, history of metastatic cancer, age, admission diagnosis of sepsis, and admission diagnosis of stroke/ intracranial hemorrhage. Those with low-risk scores (10 had 58% risk of in-hospital mortality. The Hosmer-Lemeshow chi-square of the model was 6.47 (p=0.09, and the c-statistic was 0.62 in the validation cohort. Conclusion: The model may be useful in identifying older adults at high risk of death after ED intubation.

  19. Studying morbidity and predicting mortality in patients with blunt chest trauma using a novel clinical score

    Directory of Open Access Journals (Sweden)

    Priyadarshini Manay

    2017-01-01

    Full Text Available Background: A departmental audit in March 2015 revealed significant mortality rate of 40% in blunt chest trauma patients (much greater than the global 25%. A study was thus planned to study morbidity and predictors of mortality in blunt chest trauma patients admitted to our hospital. Methods: This study was a prospective observational study of 139 patients with a history of blunt chest trauma between June 2015 and November 2015 after the Institutional Ethics Committee approval in April 2015. The sample size was calculated from the prevalence rate in our institute from the past medical records. Results: The morbidity factors following blunt chest injuries apart from pain were need for Intensive Care Unit stay, mechanical ventilation, and pneumonia/acute respiratory distress syndrome. Significant predictors of mortality in our study were SpO2 16, and need for mechanical ventilation. By calculating the likelihood ratios of each respiratory sign, a clinical score was devised. Conclusion: The modifiable factors affecting morbidity and mortality were identified. Mild to moderate chest injury due to blunt trauma is difficult to diagnose. The restoration of respiratory physiology has not only significant implications on recovery from chest injury but also all other injuries. It is our sincere hope that the score we have formulated will help reduce mortality and morbidity after further trials.

  20. Pre-transplant reversible pulmonary hypertension predicts higher risk for mortality after cardiac transplantation.

    Science.gov (United States)

    Butler, Javed; Stankewicz, Mark A; Wu, Jack; Chomsky, Don B; Howser, Renee L; Khadim, Ghazanfar; Davis, Stacy F; Pierson, Richard N; Wilson, John R

    2005-02-01

    Pre-transplant fixed pulmonary hypertension is associated with higher post-transplant mortality. In this study, we assessed the significance of pre-transplant reversible pulmonary hypertension in patients undergoing cardiac transplantation. Overall, we studied 182 patients with baseline normal pulmonary pressures or reversible pulmonary hypertension, defined as a decrease in pulmonary vascular resistance (PVR) to 50 mm Hg had a higher risk of death (odds ratio [OR] 5.96, 95% confidence interval [CI] 1.46 to 19.84 as compared with PAS 4.0 WU, but patients with TPG > or =16 had a higher risk of mortality (OR 4.93, 95% CI 1.84 to 13.17). PAS pressure was an independent predictor of mortality (OR 1.04, 95% CI 1.02 to 1.06). Recipient body mass index, history of sternotomy; and donor ischemic time were the other independent predictors of mortality. Pre-transplant pulmonary hypertension, even when reversible to a PVR of < or =2.5 WU, is associated with a higher mortality post-transplant.

  1. Analysis of predicted and measured performance of an integrated compound parabolic concentrator (ICPC)

    Energy Technology Data Exchange (ETDEWEB)

    Winston, R.; O' Gallagher, J.J.; Muschaweck, J.; Mahoney, A.R.; Dudley, V.

    1999-07-01

    A variety of configurations of evacuated Integrated Compound Parabolic Concentrator (ICPC) tubes have been under development for many years. A particularly favorable optical design corresponds to the unit concentration limit for a fin CPC solution which is then coupled to a practical, thin, wedge-shaped absorber. Prototype collector modules using tubes with two different fin orientations (horizontal and vertical) have been fabricated and tested. Comprehensive measurements of the optical characteristics of the reflector and absorber have been used together with a detailed ray trace analysis to predict the optical performance characteristics of these designs. The observed performance agrees well with the predicted performance.

  2. Intercomparison of model predictions of tritium concentrations in soil and foods following acute airborne HTO exposure

    International Nuclear Information System (INIS)

    Barry, P.J.; Watkins, B.M.; Belot, Y.; Davis, P.A.; Edlund, O.; Galeriu, D.; Raskob, W.; Russell, S.; Togawa, O.

    1998-01-01

    This paper describes the results of a model intercomparision exercise for predicting tritium transport through foodchains. Modellers were asked to assume that farmland was exposed for one hour to an average concentration in air of 10 4 MBq tritium m -3 . They were given the initial soil moisture content and 30 days of hourly averaged historical weather and asked to predict HTO and OBT concentrations in foods at selected times up to 30 days later when crops were assumed to be harvested. Two fumigations were postulated, one at 10.00 h (i.e., in day-light), and the other at 24.00 h (i.e., in darkness).Predicted environmental media concentrations after the daytime exposure agreed within an order of magnitude in most cases. Important sources of differences were variations in choices of numerical values for transport parameters. The different depths of soil layers used in the models appeared to make important contributions to differences in predictions for the given scenario. Following the night-time exposure, however, greater differences in predicted concentrations appeared. These arose largely because of different ways key processes were assumed to be affected by darkness. Uptake of HTO by vegetation and the rate it is converted to OBT were prominent amongst these processes. Further research, experimental data and modelling intercomparisons are required to resolve some of these issues. (Copyright (c) 1998 Elsevier Science B.V., Amsterdam. All rights reserved.)

  3. Investigation of stillbirths, perinatal mortality and weakness in beef calves with low-selenium whole blood concentrations

    Directory of Open Access Journals (Sweden)

    Anthony J. Davis

    2016-07-01

    Full Text Available In this on-farm investigation, we report on stillbirths, weakness and perinatal mortality seen in calves on a commercial beef farm in the Roossenekal area, Mpumalanga province, South Africa. Post-mortem examination of these calves and histopathological examination of organ and tissue samples did not indicate an infectious aetiology. Affected calves had marginal to deficient whole blood selenium concentrations. Whole blood samples collected from adult cattle on this farm and five neighbouring farms were deficient in selenium. The potential contributions of other minerals to the symptoms seen are a subject of ongoing investigation, but selenium deficiency was marked in this herd and required urgent correction. Methods to correct the deficiency included the use of injectable products, and an oral selenium supplement chelated to methionine. Selenium availability to plants is primarily determined by the selenium content of the parent bedrock, the presence of other minerals and the pH of the soil. The apparent sudden onset of this problem implicates a soil factor as being responsible for reducing selenium’s bioavailability in this area. Selenium deficiency can have a significant impact on human health. HIV and/or AIDS, various forms of cancer and several specific clinical syndromes are associated with selenium deficiency in humans, and the impact on human health in this area also requires further investigation. Keywords: vitamin E; selenium deficiency; cattle; one-health; Mpumalanga Province; soil pH; acid rain; stillbirths; white muscle disease; HIV

  4. Low plasma adiponectin concentrations do not predict weight gain in humans

    DEFF Research Database (Denmark)

    Vozarova, Barbora; Stefan, Norbert; Lindsay, Robert S

    2002-01-01

    Low concentrations of plasma adiponectin, the most abundant adipose-specific protein, are observed in obese individuals and predict the development of type 2 diabetes. Administration of adiponectin to rodents prevented diet-induced weight gain, suggesting a potential etiologic role of hypoadipone......Low concentrations of plasma adiponectin, the most abundant adipose-specific protein, are observed in obese individuals and predict the development of type 2 diabetes. Administration of adiponectin to rodents prevented diet-induced weight gain, suggesting a potential etiologic role...... of hypoadiponectinemia in the development of obesity. Our aim was to prospectively examine whether low plasma adiponectin concentrations predict future weight gain in Pima Indians, explaining the predictive effect of adiponectin on the development of type 2 diabetes. We measured plasma adiponectin concentrations in 219...... nondiabetic Pima Indians (112 M/107 F, age 31 +/- 9 years, body weight 96 +/- 20 kg [mean +/- SD]) in whom body weight and height were measured and BMI calculated at baseline and follow-up. Cross-sectionally, plasma adiponectin concentrations were negatively associated with body weight (r = -0.28, P = 0...

  5. Delirium symptoms during hospitalization predict long-term mortality in patients with severe pneumonia.

    Science.gov (United States)

    Aliberti, Stefano; Bellelli, Giuseppe; Belotti, Mauro; Morandi, Alessandro; Messinesi, Grazia; Annoni, Giorgio; Pesci, Alberto

    2015-08-01

    Delirium is common in critically ill patients and impact in-hospital mortality in patients with pneumonia. The aim of the study was to evaluate the prevalence of delirium symptoms during hospitalization in patients with severe pneumonia and their impact on one-year mortality. This was an observational, retrospective, cohort study of consecutive patients admitted to the respiratory high dependency unit of the San Gerardo University Hospital, Monza, Italy, between January 2009 and December 2012 with a diagnosis of severe pneumonia. A search through the charts looking for ten key words associated with delirium (confusion, disorientation, altered mental status, delirium, agitation, inappropriate behavior, mental status change, inattention, hallucination, lethargy) was performed by a multidisciplinary team. The primary endpoint was mortality at one-year follow-up. Secondary endpoint was in-hospital mortality. A total of 172 patients were enrolled (78 % males; median age 75 years). At least one delirium symptom was detected in 53 patients (31 %) during hospitalization. The prevalence of delirium symptoms was higher among those who died during hospitalization vs. those who survived (44 vs. 27 %, p = 0.049, respectively). Seventy-one patients (46 %) died during the one-year follow-up. The prevalence of at least one delirium symptom was higher among those who died than those who survived during the one-year follow-up (39 vs. 21 %, p = 0.014, respectively). At the multivariable logistic regression analysis, after adjustment for age, comorbidities and severe sepsis, the presence of at least one delirium symptom during hospitalization was an independent predictor of one-year mortality (OR 2.35; 95 % CI 1.13-4.90; p = 0.023). Delirium symptoms are independent predictors of one-year mortality in hospitalized patients with severe pneumonia. Further studies should confirm our results using prospective methods of collecting data.

  6. Global Longitudinal Strain to Predict Mortality in Patients With Acute Heart Failure.

    Science.gov (United States)

    Park, Jin Joo; Park, Jun-Bean; Park, Jae-Hyeong; Cho, Goo-Yeong

    2018-05-08

    Heart failure (HF) is currently classified according to left ventricular ejection fraction (LVEF); however, the prognostic value of LVEF is controversial. Myocardial strain is a prognostic factor independently of LVEF. The authors sought to evaluate the prognostic value of global longitudinal strain (GLS) in patients with HF. GLS was measured in 4,172 consecutive patients with acute HF. Patients were categorized as either HF with reduced (LVEF 12.6%), moderately (8.1% < GLS <12.5%), or severely (GLS ≤8.0%) reduced strain. The primary endpoint was 5-year all-cause mortality. Mean GLS was 10.8%, and mean LVEF was 40%. Overall, 1,740 (40.4%) patients had died at 5 years. Patients with reduced ejection fraction had slightly higher mortality than those with midrange or preserved ejection fraction (41%, 38%, and 39%, respectively; log-rank p = 0.031), whereas patients with reduced strain had significantly higher mortality (severely reduced GLS, 49%; moderately reduced GLS, 38%; mildly reduced GLS, 34%; log-rank p < 0.001). In multivariable analysis, each 1% increase in GLS was associated with a 5% decreased risk for mortality (p < 0.001). Patients with moderate (hazard ratio: 1.31; 95% confidence interval: 1.13 to 1.53) and severe GLS reductions (hazard ratio: 1.61; 95% confidence interval: 1.36 to 1.91) had higher mortality, but LVEF was not associated with mortality. In patients with acute HF, GLS has greater prognostic value than LVEF. Therefore, the authors suggest that GLS should be considered as the standard measurement in all patients with HF. This new concept needs validation in further studies. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  7. Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-hospital Mortality.

    Science.gov (United States)

    Lee, Christine K; Hofer, Ira; Gabel, Eilon; Baldi, Pierre; Cannesson, Maxime

    2018-04-17

    The authors tested the hypothesis that deep neural networks trained on intraoperative features can predict postoperative in-hospital mortality. The data used to train and validate the algorithm consists of 59,985 patients with 87 features extracted at the end of surgery. Feed-forward networks with a logistic output were trained using stochastic gradient descent with momentum. The deep neural networks were trained on 80% of the data, with 20% reserved for testing. The authors assessed improvement of the deep neural network by adding American Society of Anesthesiologists (ASA) Physical Status Classification and robustness of the deep neural network to a reduced feature set. The networks were then compared to ASA Physical Status, logistic regression, and other published clinical scores including the Surgical Apgar, Preoperative Score to Predict Postoperative Mortality, Risk Quantification Index, and the Risk Stratification Index. In-hospital mortality in the training and test sets were 0.81% and 0.73%. The deep neural network with a reduced feature set and ASA Physical Status classification had the highest area under the receiver operating characteristics curve, 0.91 (95% CI, 0.88 to 0.93). The highest logistic regression area under the curve was found with a reduced feature set and ASA Physical Status (0.90, 95% CI, 0.87 to 0.93). The Risk Stratification Index had the highest area under the receiver operating characteristics curve, at 0.97 (95% CI, 0.94 to 0.99). Deep neural networks can predict in-hospital mortality based on automatically extractable intraoperative data, but are not (yet) superior to existing methods.

  8. Personality Predicts Mortality Risk: An Integrative Data Analysis of 15 International Longitudinal Studies.

    Science.gov (United States)

    Graham, Eileen K; Rutsohn, Joshua P; Turiano, Nicholas A; Bendayan, Rebecca; Batterham, Philip J; Gerstorf, Denis; Katz, Mindy J; Reynolds, Chandra A; Sharp, Emily S; Yoneda, Tomiko B; Bastarache, Emily D; Elleman, Lorien G; Zelinski, Elizabeth M; Johansson, Boo; Kuh, Diana; Barnes, Lisa L; Bennett, David A; Deeg, Dorly J H; Lipton, Richard B; Pedersen, Nancy L; Piccinin, Andrea M; Spiro, Avron; Muniz-Terrera, Graciela; Willis, Sherry L; Schaie, K Warner; Roan, Carol; Herd, Pamela; Hofer, Scott M; Mroczek, Daniel K

    2017-10-01

    This study examined the Big Five personality traits as predictors of mortality risk, and smoking as a mediator of that association. Replication was built into the fabric of our design: we used a Coordinated Analysis with 15 international datasets, representing 44,094 participants. We found that high neuroticism and low conscientiousness, extraversion, and agreeableness were consistent predictors of mortality across studies. Smoking had a small mediating effect for neuroticism. Country and baseline age explained variation in effects: studies with older baseline age showed a pattern of protective effects (HReffects for extraversion. This study demonstrated coordinated analysis as a powerful approach to enhance replicability and reproducibility, especially for aging-related longitudinal research.

  9. Insulin Resistance Predicts Mortality in Nondiabetic Individuals in the U.S.

    OpenAIRE

    Ausk, Karlee J.; Boyko, Edward J.; Ioannou, George N.

    2010-01-01

    OBJECTIVE Insulin resistance is a suspected causative factor in a wide variety of diseases. We aimed to determine whether insulin resistance, estimated by the homeostasis model assessment for insulin resistance (HOMA-IR), is associated with all-cause or disease-specific mortality among nondiabetic persons in the U.S. RESEARCH DESIGN AND METHODS We determined the association between HOMA-IR and death certificate–based mortality among 5,511 nondiabetic, adult participants of the third U.S. Nati...

  10. Osteoprotegerin independently predicts mortality in patients with stable coronary artery disease: the CLARICOR trial

    DEFF Research Database (Denmark)

    Bjerre, Mette; Hilden, Jørgen; Kastrup, Jens

    2014-01-01

    OBJECTIVES: To elucidate the prognostic power of serum osteoprotegerin (OPG) in patients with stable coronary artery disease (CAD). METHODS: Serum OPG levels were measured in the CLARICOR trial cohort of 4063 patients with stable CAD on blood samples drawn at randomization. The follow-up was 2...... predictor for all-cause mortality. Importantly, OPG remained an independent predictor of mortality even after adjustment for both clinical and conventional cardiovascular risk markers (HR 2.5 [95% CI 1.6-3.9, p power as to all...

  11. Global concentration additivity and prediction of mixture toxicities, taking nitrobenzene derivatives as an example.

    Science.gov (United States)

    Li, Tong; Liu, Shu-Shen; Qu, Rui; Liu, Hai-Ling

    2017-10-01

    The toxicity of a mixture depends not only on the mixture concentration level but also on the mixture ratio. For a multiple-component mixture (MCM) system with a definite chemical composition, the mixture toxicity can be predicted only if the global concentration additivity (GCA) is validated. The so-called GCA means that the toxicity of any mixture in the MCM system is the concentration additive, regardless of what its mixture ratio and concentration level. However, many mixture toxicity reports have usually employed one mixture ratio (such as the EC 50 ratio), the equivalent effect concentration ratio (EECR) design, to specify several mixtures. EECR mixtures cannot simulate the concentration diversity and mixture ratio diversity of mixtures in the real environment, and it is impossible to validate the GCA. Therefore, in this paper, the uniform design ray (UD-Ray) was used to select nine mixture ratios (rays) in the mixture system of five nitrobenzene derivatives (NBDs). The representative UD-Ray mixtures can effectively and rationally describe the diversity in the NBD mixture system. The toxicities of the mixtures to Vibrio qinghaiensis sp.-Q67 were determined by the microplate toxicity analysis (MTA). For each UD-Ray mixture, the concentration addition (CA) model was used to validate whether the mixture toxicity is additive. All of the UD-Ray mixtures of five NBDs are global concentration additive. Afterwards, the CA is employed to predict the toxicities of the external mixtures from three EECR mixture rays with the NOEC, EC 30 , and EC 70 ratios. The predictive toxicities are in good agreement with the experimental toxicities, which testifies to the predictability of the mixture toxicity of the NBDs. Copyright © 2017. Published by Elsevier Inc.

  12. Prediction of Mortality with A Body Shape Index in Young Asians: Comparison with Body Mass Index and Waist Circumference.

    Science.gov (United States)

    Lee, Da-Young; Lee, Mi-Yeon; Sung, Ki-Chul

    2018-06-01

    This paper investigated the impact of A Body Shape Index (ABSI) on the risk of all-cause mortality compared with the impact of waist circumference (WC) and body mass index (BMI). This paper reviewed data of 213,569 Korean adults who participated in health checkups between 2002 and 2012 at Kangbuk Samsung Hospital in Seoul, Korea. A multivariate Cox proportional hazard analysis was performed on the BMI, WC, and ABSI z score continuous variables as well as quintiles. During 1,168,668.7 person-years, 1,107 deaths occurred. As continuous variables, a significant positive relationship with the risk of all-cause death was found only in ABSI z scores after adjustment for age, sex, current smoking, alcohol consumption, regular exercise, presence of diabetes or hypertension, and history of cardiovascular diseases. In Cox analysis of quintiles, quintile 5 of the ABSI z score showed significantly increased hazard ratios (HRs) for mortality risk (HR [95% CI] was 1.32 [1.05-1.66]), whereas the risk for all-cause mortality, on the other hand, decreased in quintiles 3 through 5 of BMI and WC compared with their first quintiles after adjusting for several confounders. This study showed that the predictive value of ABSI for mortality risk was strong for a sample of young Asian participants and that its usefulness was better than BMI or WC. © 2018 The Obesity Society.

  13. Ascites Neutrophil Gelatinase-Associated Lipocalin Identifies Spontaneous Bacterial Peritonitis and Predicts Mortality in Hospitalized Patients with Cirrhosis.

    Science.gov (United States)

    Cullaro, Giuseppe; Kim, Grace; Pereira, Marcus R; Brown, Robert S; Verna, Elizabeth C

    2017-12-01

    Neutrophil gelatinase-associated lipocalin (NGAL) is a marker of both tissue injury and infection. Urine NGAL levels strongly predict acute kidney injury and mortality in patients with cirrhosis, but ascites NGAL is not well characterized. We hypothesized that ascites NGAL level is a marker of spontaneous bacterial peritonitis (SBP) and mortality risk in patients with cirrhosis. Hospitalized patients with cirrhosis and ascites undergoing diagnostic paracentesis were prospectively enrolled and followed until death or discharge. Patients with secondary peritonitis, prior transplantation, or active colitis were excluded. NGAL was measured in the ascites and serum. Ascites NGAL level was evaluated as a marker of SBP (defined as ascites absolute neutrophil count > 250 cells/mm 3 ) and predictor of in-patient mortality. A total of 146 patients were enrolled, and of these, 29 patients (20%) had SBP. Baseline characteristics were similar between subjects with and without SBP. Median (IQR) ascites NGAL was significantly higher in patients with SBP compared to those without SBP (221.3 [145.9-392.9] vs. 139.2 [73.9-237.2], p peritonitis in hospitalized patient with cirrhosis and an independent predictor of short-term in-hospital mortality, even controlling for SBP and MELD.

  14. Prediction and Observation of Electron Instabilities and Phase Space Holes Concentrated in the Lunar Plasma Wake

    Science.gov (United States)

    Hutchinson, Ian H.; Malaspina, David M.

    2018-05-01

    Recent theory and numerical simulation predicts that the wake of the solar wind flow past the Moon should be the site of electrostatic instabilities that give rise to electron holes. These play an important role in the eventual merging of the wake with the background solar wind. Analysis of measurements from the ARTEMIS satellites, orbiting the Moon at distances from 1.2 to 11 RM, detects holes highly concentrated in the wake, in agreement with prediction. The theory also predicts that the hole flux density observed should be hollow, peaking away from the wake axis. Observation statistics qualitatively confirm this hollowness, lending extra supporting evidence for the identification of their generation mechanism.

  15. Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

    Science.gov (United States)

    Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

    2012-08-01

    Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

  16. Predictive factors of neurological complications and one-month mortality after liver transplantation

    Directory of Open Access Journals (Sweden)

    Katherine eFu

    2014-12-01

    Full Text Available Background: Neurological complications are common after orthotopic liver transplantation (OLT. We aimed to characterize the risk factors associated with neurological complications and mortality among patients who underwent OLT in the post-model for end-stage liver disease (MELD era.Methods: In a retrospective review, we evaluated 227 consecutive patients at the Keck Hospital of the University of Southern California before and after OLT to define the type and frequency of and risk factors for neurological complications and mortality.Results: Neurological complications were common (n=98, with encephalopathy being most frequent (56.8%, followed by tremor (26.5%, hallucinations (11.2%, and seizure (8.2%. Factors associated with neurological complications after OLT included preoperative dialysis, hepatorenal syndrome, renal insufficiency, intra-operative dialysis, preoperative encephalopathy, preoperative mechanical ventilation, and infection. Preoperative infection was an independent predictor of neurological complications (OR 2.83, 1.47 – 5.44. One-month mortality was 8.8% and was independently associated with urgent re-transplant, preoperative intubation, intraoperative arrhythmia, and intraoperative use of multiple pressors.Conclusion: Neurological complications are common in patients undergoing OLT in the post-MELD era, with encephalopathy being most frequent. An improved understanding of the risk factors related to both neurological complications and one-month mortality post-transplantation can better guide perioperative care and help improve outcomes among OLT patients.

  17. External validation of the Emergency Trauma Score for early prediction of mortality in trauma patients

    NARCIS (Netherlands)

    Joosse, Pieter; de Jong, Willem-Jan J.; Reitsma, Johannes B.; Wendt, Klaus W.; Schep, Niels W.; Goslings, J. Carel

    2014-01-01

    The Emergency Trauma Score has been developed for early estimation of mortality risk in adult trauma patients with an Injury Severity Score of 16 or higher. Emergency Trauma Score combines four early predictors available at the trauma resuscitation room: age, Glasgow Coma Scale, base excess, and

  18. External Validation of the Emergency Trauma Score for Early Prediction of Mortality in Trauma Patients

    NARCIS (Netherlands)

    Joosse, Pieter; de Jong, Willem-Jan J.; Wendt, Klaus W.; Schep, Niels W.; Goslings, J. Carel; Reitsma, J.

    Objectives: The Emergency Trauma Score has been developed for early estimation of mortality risk in adult trauma patients with an Injury Severity Score of 16 or higher. Emergency Trauma Score combines four early predictors available at the trauma resuscitation room: age, Glasgow Coma Scale, base

  19. Mortality is predicted by Comorbidity Polypharmacy score but not Charlson Comorbidity Index in geriatric trauma patients.

    Science.gov (United States)

    Nossaman, Vaughn E; Larsen, Brett E; DiGiacomo, Jody C; Manuelyan, Zara; Afram, Renee; Shukry, Sally; Kang, Amiee Luan; Munnangi, Swapna; Angus, L D George

    2017-09-19

    Increased life expectancy has resulted in more older patients at trauma centers. Traditional assessments of injuries alone may not be sufficient; age, comorbidities, and medications should be considered. 446 older trauma patients were analyzed in two groups, 45-65 years and <65, using Injury Severity Score (ISS), the Charlson Comorbidity Index (CCI), and Comorbidity-Polypharmacy Score (CPS). CCI and CPS were associated with HLOS in patients <65. In patients aged 45-65, only CPS was associated with HLOS. CPS was inversely associated with in-hospital mortality in patients <65, but not patients aged 45-65. CCI score was not associated with in-hospital mortality in either group. Increased CCI and CPS were associated with increased HLOS. In patients over 65, increased CPS was associated with decreased mortality. This could be due to return toward physiologic normalcy in treated patients not seen in their peers with undiagnosed or untreated comorbidities. TABLE OF CONTENTS SUMMARY: In an analysis of 446 older trauma patients, the Charlson Comorbidity Index (CCI) and Comorbidity-Polypharmacy Score (CPS) were associated with increased hospital length of stay. In patients ≥65, increased CPS had a lower mortality, possibly due to a greater return toward physiologic normalcy not present in their untreated peers. Published by Elsevier Inc.

  20. A risk score for predicting mortality in patients with asymptomatic mild to moderate aortic stenosis

    DEFF Research Database (Denmark)

    Holme, Ingar; Pedersen, Terje R; Boman, Kurt

    2012-01-01

    BackgroundPrognostic information for asymptomatic patients with aortic stenosis (AS) from prospective studies is scarce and there is no risk score available to assess mortality.ObjectivesTo develop an easily calculable score, from which clinicians could stratify patients into high and lower risk...

  1. The predictive value of fatigue for nonfatal ischemic heart disease and all-cause mortality

    DEFF Research Database (Denmark)

    Ekmann, Anette; Osler, Merete; Avlund, Kirsten

    2012-01-01

    IHD were asked if they felt fatigued. Information on IHD diagnosis and all-cause mortality was register based. The Cox proportional hazard model was used to test the association at 4-year follow-up. Results Fatigue was associated with hospitalization for nonfatal IHD (hazard ratio [HR] = 1.98, 95...

  2. Orosomucoid in urine predicts cardiovascular and over-all mortality in patients with Type II diabetes

    DEFF Research Database (Denmark)

    Christiansen, Merete S; Hommel, E; Magid, E

    2002-01-01

    urinary orosomucoid excretion rate at baseline (odds ratios adjusted for age, sex, duration of diabetes, cardiovascular diseases, weight, medication, HbA1 c, plasma creatinine and urinary albumin excretion rate). Urinary albumin excretion rate was an independent predictor of all-cause mortality when...

  3. Predicting hospital mortality among frequently readmitted patients: HSMR biased by readmission

    NARCIS (Netherlands)

    van den Bosch, W.F.; Kelder, J.C.; Wagner, C.

    2011-01-01

    Background: Casemix adjusted in-hospital mortality is one of the measures used to improve quality of care. The adjustment currently used does not take into account the effects of readmission, because reliable data on readmission is not readily available through routinely collected databases. We have

  4. Predicting hospital mortality among frequently readmitted patients: HSMR biased by readmission.

    NARCIS (Netherlands)

    Bosch, W.F. van den; Kelder, J.C.; Wagner, C.

    2011-01-01

    BACKGROUND: Casemix adjusted in-hospital mortality is one of the measures used to improve quality of care. The adjustment currently used does not take into account the effects of readmission, because reliable data on readmission is not readily available through routinely collected databases. We have

  5. A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations

    Directory of Open Access Journals (Sweden)

    P. Koutrakis

    2011-08-01

    Full Text Available Epidemiological studies investigating the human health effects of PM2.5 are susceptible to exposure measurement errors, a form of bias in exposure estimates, since they rely on data from a limited number of PM2.5 monitors within their study area. Satellite data can be used to expand spatial coverage, potentially enhancing our ability to estimate location- or subject-specific exposures to PM2.5, but some have reported poor predictive power. A new methodology was developed to calibrate aerosol optical depth (AOD data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS. Subsequently, this method was used to predict ground daily PM2.5 concentrations in the New England region. 2003 MODIS AOD data corresponding to the New England region were retrieved, and PM2.5 concentrations measured at 26 US Environmental Protection Agency (EPA PM2.5 monitoring sites were used to calibrate the AOD data. A mixed effects model which allows day-to-day variability in daily PM2.5-AOD relationships was used to predict location-specific PM2.5 levels. PM2.5 concentrations measured at the monitoring sites were compared to those predicted for the corresponding grid cells. Both cross-sectional and longitudinal comparisons between the observed and predicted concentrations suggested that the proposed new calibration approach renders MODIS AOD data a potentially useful predictor of PM2.5 concentrations. Furthermore, the estimated PM2.5 levels within the study domain were examined in relation to air pollution sources. Our approach made it possible to investigate the spatial patterns of PM2.5 concentrations within the study domain.

  6. Malnutrition: a highly predictive risk factor of short-term mortality in elderly presenting to the emergency department.

    Science.gov (United States)

    Gentile, S; Lacroix, O; Durand, A C; Cretel, E; Alazia, M; Sambuc, R; Bonin-Guillaume, S

    2013-04-01

    To identify independent risk factors of mortality among elderly patients in the 3 months after their visit (T3) to an emergency department (ED). Prospective cohort study. University hospital ED in an urban setting in France. One hundred seventy-three patients aged 75 and older were admitted to the ED over two weeks (18.7% of the 924 ED visits). Of these, 164 patients (94.8%) were included in our study, and 157 (95.7%) of them were followed three months after their ED visit. During the inclusion period (T0), a standardized questionnaire was used to collect data on socio-demographic and environmental characteristics, ED visit circumstances, medical conditions and geriatric assessment including functional and nutritional status. Three months after the ED visits (T3), patients or their caregivers were interviewed to collect data on vital status, and ED return or hospitalization. Among the 157 patients followed at T3, 14.6% had died, 19.9% had repeated ED visits, and 63.1% had been hospitalized. The two independent predictive factors for mortality within the 3 months after ED visit were: malnutrition screened by the Mini Nutritional Assessment short-form (MNA-SF) (OR=20.2; 95% CI: 5.74-71.35; pMalnutrition is the strongest independent risk factor predicting short-term mortality in elderly patients visiting the ED, and it was easily detected by MNA-SF and supported from the ED visit.

  7. Macrophage activation markers predict mortality in patients with liver cirrhosis without or with acute-on-chronic liver failure (ACLF)

    DEFF Research Database (Denmark)

    Grønbæk, Henning; Rødgaard-Hansen, Sidsel; Aagaard, Niels Kristian

    2016-01-01

    BACKGROUND & AIMS: Activation of liver macrophages plays a key role in liver and systemic inflammation and may be involved in development and prognosis of acute-on-chronic liver failure (ACLF). We therefore measured the circulating macrophage activation markers soluble sCD163 and mannose receptor......-C ACLF and CLIF-C AD scores. Addition of the macrophage markers to the clinical scores improved the prognostic efficacy: In ACLF patients sCD163 improved prediction of short-term mortality (C-index: 0.74 (0.67-0.80)) and in patients without ACLF sMR improved prediction of long-term mortality (C-index: 0.......80 (0.76-0.85)). CONCLUSIONS: The severity related increase in sCD163 and sMR and close association with mortality suggest a primary importance of inflammatory activation of liver macrophages in the emergence and course of ACLF. Accordingly, supplementation of the macrophage biomarkers to the platform...

  8. Comparison of four contemporary risk models at predicting mortality after aortic valve replacement.

    Science.gov (United States)

    Wang, Tom Kai Ming; Choi, David H M; Stewart, Ralph; Gamble, Greg; Haydock, David; Ruygrok, Peter

    2015-02-01

    Risk stratification for aortic valve replacement (AVR) is desirable given the increased demand for intervention and the introduction of transcatheter aortic valve implantation. We compared the prognostic utility of the European System for Cardiac Operative Risk Evaluation (EuroSCORE), EuroSCORE II, Society of Thoracic Surgeons (STS) score, and an Australasian model (Aus-AVR score) for AVR. We retrospectively calculated the 4 risk scores for patients undergoing isolated AVR at Auckland City Hospital from 2005 to 2012 and assessed their discrimination and calibration for short- and long-term mortality. A total of 620 patients were followed up for 3.8 ± 2.4 years, with an operative mortality of 2.9% (n = 18). The mean EuroSCORE, EuroSCORE II, STS score, and Aus-AVR score was 8.7% ± 8.3%, 3.8% ± 4.7%, 2.8% ± 2.7%, and 3.2% ± 4.8%, respectively. The corresponding C-statistics for operative mortality were 0.752 (95% confidence interval [CI], 0.652-0.852), 0.711 (95% CI, 0.607-0.815), 0.716 (95% CI, 0.593-0.837), and 0.684 (95% CI, 0.557-0.811). The corresponding Hosmer-Lemeshow test P and chi-square values for calibration were .007 and 21.1, .125 and 12.6, .753 and 5.0, and .468 and 7.7. The corresponding Brier scores were 0.0348, 0.0278, 0.0276, and 0.0294. Independent predictors of operative mortality included critical preoperative state, atrial fibrillation, extracardiac arteriopathy, and mitral stenosis. The log-rank test P values were all <.001 for mortality during follow-up for all 4 scores, stratified by quintile. All 4 risk scores discriminated operative mortality after isolated AVR. The EuroSCORE had poor calibration, overestimating operative mortality, although the other 3 scores fitted well with contemporary outcomes. The STS score was the best calibrated in the highest quintile of operative risk. Copyright © 2015 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  9. Oxidative Stress Predicts All-Cause Mortality in HIV-Infected Patients.

    Directory of Open Access Journals (Sweden)

    Mar Masiá

    Full Text Available We aimed to assess whether oxidative stress is a predictor of mortality in HIV-infected patients.We conducted a nested case-control study in CoRIS, a contemporary, multicentre cohort of HIV-infected patients, antiretroviral-naïve at entry, launched in 2004. Cases were patients who died with available stored plasma samples collected. Two age and sex-matched controls for each case were selected. We measured F2-isoprostanes (F2-IsoPs and malondialdehyde (MDA plasma levels in the first blood sample obtained after cohort engagement.54 cases and 93 controls were included. Median F2-IsoPs and MDA levels were significantly higher in cases than in controls. When adjustment was performed for age, HIV-transmission category, CD4 cell count and HIV viral load at cohort entry, and subclinical inflammation measured with highly-sensitive C-reactive protein (hsCRP, the association of F2-IsoPs with mortality remained significant (adjusted OR per 1 log10 increase, 2.34 [1.23-4.47], P = 0.009. The association of MDA with mortality was attenuated after adjustment: adjusted OR (95% CI per 1 log10 increase, 2.05 [0.91-4.59], P = 0.080. Median hsCRP was also higher in cases, and it also proved to be an independent predictor of mortality in the adjusted analysis: OR (95% CI per 1 log10 increase, 1.39 (1.01-1.91, P = 0.043; and OR (95% CI per 1 log10 increase, 1.46 (1.07-1.99, P = 0.014, respectively, when adjustment included F2-IsoPs and MDA.Oxidative stress is a predictor of all-cause mortality in HIV-infected patients. For plasma F2-IsoPs, this association is independent of HIV-related factors and subclinical inflammation.

  10. [Risk Prediction Using Routine Data: Development and Validation of Multivariable Models Predicting 30- and 90-day Mortality after Surgical Treatment of Colorectal Cancer].

    Science.gov (United States)

    Crispin, Alexander; Strahwald, Brigitte; Cheney, Catherine; Mansmann, Ulrich

    2018-06-04

    Quality control, benchmarking, and pay for performance (P4P) require valid indicators and statistical models allowing adjustment for differences in risk profiles of the patient populations of the respective institutions. Using hospital remuneration data for measuring quality and modelling patient risks has been criticized by clinicians. Here we explore the potential of prediction models for 30- and 90-day mortality after colorectal cancer surgery based on routine data. Full census of a major statutory health insurer. Surgical departments throughout the Federal Republic of Germany. 4283 and 4124 insurants with major surgery for treatment of colorectal cancer during 2013 and 2014, respectively. Age, sex, primary and secondary diagnoses as well as tumor locations as recorded in the hospital remuneration data according to §301 SGB V. 30- and 90-day mortality. Elixhauser comorbidities, Charlson conditions, and Charlson scores were generated from the ICD-10 diagnoses. Multivariable prediction models were developed using a penalized logistic regression approach (logistic ridge regression) in a derivation set (patients treated in 2013). Calibration and discrimination of the models were assessed in an internal validation sample (patients treated in 2014) using calibration curves, Brier scores, receiver operating characteristic curves (ROC curves) and the areas under the ROC curves (AUC). 30- and 90-day mortality rates in the learning-sample were 5.7 and 8.4%, respectively. The corresponding values in the validation sample were 5.9% and once more 8.4%. Models based on Elixhauser comorbidities exhibited the highest discriminatory power with AUC values of 0.804 (95% CI: 0.776 -0.832) and 0.805 (95% CI: 0.782-0.828) for 30- and 90-day mortality. The Brier scores for these models were 0.050 (95% CI: 0.044-0.056) and 0.067 (95% CI: 0.060-0.074) and similar to the models based on Charlson conditions. Regardless of the model, low predicted probabilities were well calibrated, while

  11. Prediction of mortality using on-line, self-reported health data: empirical test of the RealAge score.

    Directory of Open Access Journals (Sweden)

    William R Hobbs

    Full Text Available OBJECTIVE: We validate an online, personalized mortality risk measure called "RealAge" assigned to 30 million individuals over the past 10 years. METHODS: 188,698 RealAge survey respondents were linked to California Department of Public Health death records using a one-way cryptographic hash of first name, last name, and date of birth. 1,046 were identified as deceased. We used Cox proportional hazards models and receiver operating characteristic (ROC curves to estimate the relative scales and predictive accuracies of chronological age, the RealAge score, and the Framingham ATP-III score for hard coronary heart disease (HCHD in this data. To address concerns about selection and to examine possible heterogeneity, we compared the results by time to death at registration, underlying cause of death, and relative health among users. RESULTS: THE REALAGE SCORE IS ACCURATELY SCALED (HAZARD RATIOS: age 1.076; RealAge-age 1.084 and more accurate than chronological age (age c-statistic: 0.748; RealAge c-statistic: 0.847 in predicting mortality from hard coronary heart disease following survey completion. The score is more accurate than the Framingham ATP-III score for hard coronary heart disease (c-statistic: 0.814, perhaps because self-reported cholesterol levels are relatively uninformative in the RealAge user sample. RealAge predicts deaths from malignant neoplasms, heart disease, and external causes. The score does not predict malignant neoplasm deaths when restricted to users with no smoking history, no prior cancer diagnosis, and no indicated health interest in cancer (p-value 0.820. CONCLUSION: The RealAge score is a valid measure of mortality risk in its user population.

  12. Comparison of artificial neural network and logistic regression models for predicting in-hospital mortality after primary liver cancer surgery.

    Directory of Open Access Journals (Sweden)

    Hon-Yi Shi

    Full Text Available BACKGROUND: Since most published articles comparing the performance of artificial neural network (ANN models and logistic regression (LR models for predicting hepatocellular carcinoma (HCC outcomes used only a single dataset, the essential issue of internal validity (reproducibility of the models has not been addressed. The study purposes to validate the use of ANN model for predicting in-hospital mortality in HCC surgery patients in Taiwan and to compare the predictive accuracy of ANN with that of LR model. METHODOLOGY/PRINCIPAL FINDINGS: Patients who underwent a HCC surgery during the period from 1998 to 2009 were included in the study. This study retrospectively compared 1,000 pairs of LR and ANN models based on initial clinical data for 22,926 HCC surgery patients. For each pair of ANN and LR models, the area under the receiver operating characteristic (AUROC curves, Hosmer-Lemeshow (H-L statistics and accuracy rate were calculated and compared using paired T-tests. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and the relative importance of variables. Compared to the LR models, the ANN models had a better accuracy rate in 97.28% of cases, a better H-L statistic in 41.18% of cases, and a better AUROC curve in 84.67% of cases. Surgeon volume was the most influential (sensitive parameter affecting in-hospital mortality followed by age and lengths of stay. CONCLUSIONS/SIGNIFICANCE: In comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data.

  13. Prediction of indoor radon concentration based on residence location and construction

    International Nuclear Information System (INIS)

    Maekelaeinen, I.; Voutilainen, A.; Castren, O.

    1992-01-01

    We have constructed a model for assessing indoor radon concentrations in houses where measurements cannot be performed. It has been used in an epidemiological study and to determine the radon potential of new building sites. The model is based on data from about 10,000 buildings. Integrated radon measurements were made during the cold season in all the houses; their geographic coordinates were also known. The 2-mo measurement results were corrected to annual average concentrations. Construction data were collected from questionnaires completed by residents; geological data were determined from geological maps. Data were classified according to geographical, geological, and construction factors. In order to describe different radon production levels, the country was divided into four zones. We assumed that the factors were multiplicative, and a linear concentration-prediction model was used. The most significant factor in determining radon concentration was the geographical region, followed by soil type, year of construction, and type of foundation. The predicted indoor radon concentrations given by the model varied from 50 to 440 Bq m -3 . The lower figure represents a house with a basement, built in the 1950s on clay soil, in the region with the lowest radon concentration levels. The higher value represents a house with a concrete slab in contact with the ground, built in the 1980s, on gravel, in the region with the highest average radon concentration

  14. Arsenic concentrations, related environmental factors, and the predicted probability of elevated arsenic in groundwater in Pennsylvania

    Science.gov (United States)

    Gross, Eliza L.; Low, Dennis J.

    2013-01-01

    Analytical results for arsenic in water samples from 5,023 wells obtained during 1969–2007 across Pennsylvania were compiled and related to other associated groundwater-quality and environmental factors and used to predict the probability of elevated arsenic concentrations, defined as greater than or equal to 4.0 micrograms per liter (µg/L), in groundwater. Arsenic concentrations of 4.0 µg/L or greater (elevated concentrations) were detected in 18 percent of samples across Pennsylvania; 8 percent of samples had concentrations that equaled or exceeded the U.S. Environmental Protection Agency’s drinking-water maximum contaminant level of 10.0 µg/L. The highest arsenic concentration was 490.0 µg/L.

  15. Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong

    Directory of Open Access Journals (Sweden)

    Jiangshe Zhang

    2017-01-01

    Full Text Available With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The extreme learning machine for single hidden layer feed-forward neural networks tends to provide good generalization performance at an extremely fast learning speed. The major sources of air pollutants in Hong Kong are mobile, stationary, and from trans-boundary sources. We propose predicting the concentration of air pollutants by the use of trained extreme learning machines based on the data obtained from eight air quality parameters in two monitoring stations, including Sham Shui Po and Tap Mun in Hong Kong for six years. The experimental results show that our proposed algorithm performs better on the Hong Kong data both quantitatively and qualitatively. Particularly, our algorithm shows better predictive ability, with R 2 increased and root mean square error values decreased respectively.

  16. Prediction of hydroxyl concentrations in cement pore water using a numerical cement hydration model

    NARCIS (Netherlands)

    Eijk, van R.J.; Brouwers, H.J.H.

    2000-01-01

    In this paper, a 3D numerical cement hydration model is used for predicting alkali and hydroxyl concentrations in cement pore water. First, this numerical model is calibrated for Dutch cement employing both chemical shrinkage and calorimetric experiments. Secondly, the strength development of some

  17. A study on prediction of uranium concentration in pregnant solution from in-situ leaching

    International Nuclear Information System (INIS)

    Yi Weiping; Zhou Quan; Yu Yunzhen; Wang Shude; Yang Yihan; Lei Qifeng

    2005-01-01

    The modeling course on prediction of uranium concentration in pregnant solution from in-situ leaching of uranium is described, a mathematical model based on grey system theory is put forward, and a set of computer application software is correspondingly developed. (authors)

  18. Aquatic Exposure Predictions of Insecticide Field Concentrations Using a Multimedia Mass-Balance Model.

    Science.gov (United States)

    Knäbel, Anja; Scheringer, Martin; Stehle, Sebastian; Schulz, Ralf

    2016-04-05

    Highly complex process-driven mechanistic fate and transport models and multimedia mass balance models can be used for the exposure prediction of pesticides in different environmental compartments. Generally, both types of models differ in spatial and temporal resolution. Process-driven mechanistic fate models are very complex, and calculations are time-intensive. This type of model is currently used within the European regulatory pesticide registration (FOCUS). Multimedia mass-balance models require fewer input parameters to calculate concentration ranges and the partitioning between different environmental media. In this study, we used the fugacity-based small-region model (SRM) to calculate predicted environmental concentrations (PEC) for 466 cases of insecticide field concentrations measured in European surface waters. We were able to show that the PECs of the multimedia model are more protective in comparison to FOCUS. In addition, our results show that the multimedia model results have a higher predictive power to simulate varying field concentrations at a higher level of field relevance. The adaptation of the model scenario to actual field conditions suggests that the performance of the SRM increases when worst-case conditions are replaced by real field data. Therefore, this study shows that a less complex modeling approach than that used in the regulatory risk assessment exhibits a higher level of protectiveness and predictiveness and that there is a need to develop and evaluate new ecologically relevant scenarios in the context of pesticide exposure modeling.

  19. Intra-Operative Amylase Concentration in Peri-Pancreatic Fluid Predicts Pancreatic Fistula After Distal Pancreatectomy

    NARCIS (Netherlands)

    Nahm, C.B.; Reuver, P.R.; Hugh, T.J.; Pearson, A.; Gill, A.J.; Samra, J.S.; Mittal, A.

    2017-01-01

    Post-operative pancreatic fistula (POPF) is a potentially severe complication following distal pancreatectomy. The aim of this study was to assess the predictive value of intra-operative amylase concentration (IOAC) in peri-pancreatic fluid after distal pancreatectomy for the diagnosis of POPF.

  20. Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong.

    Science.gov (United States)

    Zhang, Jiangshe; Ding, Weifu

    2017-01-24

    With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The extreme learning machine for single hidden layer feed-forward neural networks tends to provide good generalization performance at an extremely fast learning speed. The major sources of air pollutants in Hong Kong are mobile, stationary, and from trans-boundary sources. We propose predicting the concentration of air pollutants by the use of trained extreme learning machines based on the data obtained from eight air quality parameters in two monitoring stations, including Sham Shui Po and Tap Mun in Hong Kong for six years. The experimental results show that our proposed algorithm performs better on the Hong Kong data both quantitatively and qualitatively. Particularly, our algorithm shows better predictive ability, with R 2 increased and root mean square error values decreased respectively.

  1. Importance of Foliar Nitrogen Concentration to Predict Forest Productivity in the Mid-Atlantic Region

    Science.gov (United States)

    Yude Pan; John Hom; Jennifer Jenkins; Richard Birdsey

    2004-01-01

    To assess what difference it might make to include spatially defined estimates of foliar nitrogen in the regional application of a forest ecosystem model (PnET-II), we composed model predictions of wood production from extensive ground-based forest inventory analysis data across the Mid-Atlantic region. Spatial variation in foliar N concentration was assigned based on...

  2. The predictive value of current haemoglobin levels for incident tuberculosis and/or mortality during long-term antiretroviral therapy in South Africa: a cohort study.

    Science.gov (United States)

    Kerkhoff, Andrew D; Wood, Robin; Cobelens, Frank G; Gupta-Wright, Ankur; Bekker, Linda-Gail; Lawn, Stephen D

    2015-04-02

    Low haemoglobin concentrations may be predictive of incident tuberculosis (TB) and death in HIV-infected patients receiving antiretroviral therapy (ART), but data are limited and inconsistent. We examined these relationships retrospectively in a long-term South African ART cohort with multiple time-updated haemoglobin measurements. Prospectively collected clinical data on patients receiving ART for up to 8 years in a community-based cohort were analysed. Time-updated haemoglobin concentrations, CD4 counts and HIV viral loads were recorded, and TB diagnoses and deaths from all causes were ascertained. Anaemia severity was classified using World Health Organization criteria. TB incidence and mortality rates were calculated and Poisson regression models were used to identify independent predictors of incident TB and mortality, respectively. During a median follow-up of 5.0 years (IQR, 2.5-5.8) of 1,521 patients, 476 cases of incident TB and 192 deaths occurred during 6,459 person-years (PYs) of follow-up. TB incidence rates were strongly associated with time-updated anaemia severity; those without anaemia had a rate of 4.4 (95%CI, 3.8-5.1) cases/100 PYs compared to 10.0 (95%CI, 8.3-12.1), 26.6 (95%CI, 22.5-31.7) and 87.8 (95%CI, 57.0-138.2) cases/100 PYs in those with mild, moderate and severe anaemia, respectively. Similarly, mortality rates in those with no anaemia or mild, moderate and severe time-updated anaemia were 1.1 (95%CI, 0.8-1.5), 3.5 (95%CI, 2.7-4.8), 11.8 (95%CI, 9.5-14.8) and 28.2 (95%CI, 16.5-51.5) cases/100 PYs, respectively. Moderate and severe anaemia (time-updated) during ART were the strongest independent predictors for incident TB (adjusted IRR = 3.8 [95%CI, 3.0-4.8] and 8.2 [95%CI, 5.3-12.7], respectively) and for mortality (adjusted IRR = 6.0 [95%CI, 3.9-9.2] and adjusted IRR = 8.0 [95%CI, 3.9-16.4], respectively). Increasing severity of anaemia was associated with exceptionally high rates of both incident TB and mortality during

  3. Mathematical Model to Predict Skin Concentration after Topical Application of Drugs

    Directory of Open Access Journals (Sweden)

    Hiroaki Todo

    2013-12-01

    Full Text Available Skin permeation experiments have been broadly done since 1970s to 1980s as an evaluation method for transdermal drug delivery systems. In topically applied drug and cosmetic formulations, skin concentration of chemical compounds is more important than their skin permeations, because primary target site of the chemical compounds is skin surface or skin tissues. Furthermore, the direct pharmacological reaction of a metabolically stable drug that binds with specific receptors of known expression levels in an organ can be determined by Hill’s equation. Nevertheless, little investigation was carried out on the test method of skin concentration after topically application of chemical compounds. Recently we investigated an estimating method of skin concentration of the chemical compounds from their skin permeation profiles. In the study, we took care of “3Rs” issues for animal experiments. We have proposed an equation which was capable to estimate animal skin concentration from permeation profile through the artificial membrane (silicone membrane and animal skin. This new approach may allow the skin concentration of a drug to be predicted using Fick’s second law of diffusion. The silicone membrane was found to be useful as an alternative membrane to animal skin for predicting skin concentration of chemical compounds, because an extremely excellent extrapolation to animal skin concentration was attained by calculation using the silicone membrane permeation data. In this chapter, we aimed to establish an accurate and convenient method for predicting the concentration profiles of drugs in the skin based on the skin permeation parameters of topically active drugs derived from steady-state skin permeation experiments.

  4. Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation

    International Nuclear Information System (INIS)

    Li, Xiang; Peng, Ling; Yao, Xiaojing; Cui, Shaolong; Hu, Yuan; You, Chengzeng; Chi, Tianhe

    2017-01-01

    Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13–24 h prediction tasks (MAPE = 31.47%). - Highlights: • Regional air pollutant concentration shows an obvious spatiotemporal correlation. • Our prediction model presents superior performance. • Climate data and metadata can significantly

  5. A new method to measure effective soil solution concentration predicts copper availability to plants.

    Science.gov (United States)

    Zhang, H; Zhao, F J; Sun, B; Davison, W; McGrath, S P

    2001-06-15

    Risk assessments of metal contaminated soils need to address metal bioavailability. To predict the bioavailability of metals to plants, it is necessary to understand both solution and solid phase supply processes in soils. In striving to find surrogate chemical measurements, scientists have focused either on soil solution chemistry, including free ion activities, or operationally defined fractions of metals. Here we introduce the new concept of effective concentration, CE, which includes both the soil solution concentration and an additional term, expressed as a concentration, that represents metal supplied from the solid phase. CE was measured using the technique of diffusive gradients in thin films (DGT) which, like a plant, locally lowers soil solution concentrations, inducing metal supply from the solid phase, as shown by a dynamic model of the DGT-soil system. Measurements of Cu as CE, soil solution concentration, by EDTA extraction and as free Cu2+ activity in soil solution were made on 29 different soils covering a large range of copper concentrations. Theywere compared to Cu concentrations in the plant material of Lepidium heterophyllum grown on the same soils. Plant concentrations were linearly related and highly correlated with CE but were more scattered and nonlinear with respect to free Cu2+ activity, EDTA extraction, or soil solution concentrations. These results demonstrate that the dominant supply processes in these soils are diffusion and labile metal release, which the DGT-soil system mimics. The quantity CE is shown to have promise as a quantitative measure of the bioavailable metal in soils.

  6. Basic geriatric assessment does not predict in-hospital mortality after PEG placement

    Directory of Open Access Journals (Sweden)

    Smoliner Christine

    2012-09-01

    Full Text Available Abstract Background Percutaneous endoscopic gastrostomy (PEG is an established procedure for long-term nutrition. However, studies have underlined the importance of proper patient selection as mortality has been shown to be relatively high in acute illness and certain patient groups, amongst others geriatric patients. Objective of the study was to gather information about geriatric patients receiving PEG and to identify risk factors associated with in-hospital mortality after PEG placement. Methods All patients from the GEMIDAS database undergoing percutaneous endoscopic gastrostomy in acute geriatric wards from 2006 to 2010 were included in a retrospective database analysis. Data on age, gender, main diagnosis leading to hospital admission, death in hospital, care level, and legal incapacitation were extracted from the main database of the Geriatric Minimum Data Set. Self-care capacity was assessed by the Barthel index, and cognitive status was rated with the Mini Mental State Examination or subjectively judged by the clinician. Descriptive statistics and group comparisons were chosen according to data distribution and scale of measurement, logistic regression analysis was performed to examine influence of various factors on hospital mortality. Results A total of 1232 patients (60.4% women with a median age of 82 years (range 60 to 99 years were included. The mean Barthel index at admission was 9.5 ± 14.0 points. Assessment of cognitive status was available in about half of the patients (n = 664, with 20% being mildly impaired and almost 70% being moderately to severely impaired. Stroke was the most common main diagnosis (55.2%. In-hospital mortality was 12.8%. In a logistic regression analysis, old age (odds ratio (OR 1.030, 95% confidence interval (CI 1.003-1.056, male sex (OR 1.741, 95% CI 1.216-2.493, and pneumonia (OR 2.641, 95% CI 1.457-4.792 or the diagnosis group ‘miscellaneous disease’ (OR 1.864, 95% CI 1

  7. Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

    Science.gov (United States)

    Lin, Shu-Yu; Lee, Wei-Ju; Chou, Ming-Yueh; Peng, Li-Ning; Chiou, Shu-Ti; Chen, Liang-Kung

    2016-01-01

    Frailty Index, defined as an individual's accumulated proportion of listed health-related deficits, is a well-established metric used to assess the health status of old adults; however, it has not yet been developed in Taiwan, and its local related structure factors remain unclear. The objectives were to construct a Taiwan Frailty Index to predict mortality risk, and to explore the structure of its factors. Analytic data on 1,284 participants aged 53 and older were excerpted from the Social Environment and Biomarkers of Aging Study (2006), in Taiwan. A consensus workgroup of geriatricians selected 159 items according to the standard procedure for creating a Frailty Index. Cox proportional hazard modeling was used to explore the association between the Taiwan Frailty Index and mortality. Exploratory factor analysis was used to identify structure factors and produce a shorter version-the Taiwan Frailty Index Short-Form. During an average follow-up of 4.3 ± 0.8 years, 140 (11%) subjects died. Compared to those in the lowest Taiwan Frailty Index tertile ( 0.23) had significantly higher risk of death (Hazard ratio: 3.2; 95% CI 1.9-5.4). Thirty-five items of five structure factors identified by exploratory factor analysis, included: physical activities, life satisfaction and financial status, health status, cognitive function, and stresses. Area under the receiver operating characteristic curves (C-statistics) of the Taiwan Frailty Index and its Short-Form were 0.80 and 0.78, respectively, with no statistically significant difference between them. Although both the Taiwan Frailty Index and Short-Form were associated with mortality, the Short-Form, which had similar accuracy in predicting mortality as the full Taiwan Frailty Index, would be more expedient in clinical practice and community settings to target frailty screening and intervention.

  8. Prediction of cardiovascular and total mortality in Chinese type 2 diabetic patients by the WHO definition for the metabolic syndrome.

    Science.gov (United States)

    Ko, G T-C; So, W-Y; Chan, N N; Chan, W-B; Tong, P C-Y; Li, J; Yeung, V; Chow, C-C; Ozaki, R; Ma, R C-W; Cockram, C S; Chan, J C-N

    2006-01-01

    The aim of this study is to investigate the prevalence of metabolic syndrome (MES) in type 2 diabetic patients and the predictive values of the World Health Organization (WHO) and National Cholesterol Education Programme (NCEP) definitions and the individual components of the MES on total and cardiovascular mortality. A prospective analysis of a consecutive cohort of 5202 Chinese type 2 diabetic patients recruited between July 1994 and April 2001. The prevalence of the MES was 49.2-58.1% depending on the use of various criteria. There were 189 deaths (men: 100 and women: 89) in these 5205 patients during a median (interquartile range) follow-up period of 2.1 (0.3-3.6 years). Of these, 164 (87%) were classified as cardiovascular deaths. Using the NCEP criterion, patients with MES had a death rate similar to those without (3.51 vs. 3.85%). By contrast, based on the WHO criteria, patients with MES had a higher mortality rate than those without (4.3 vs. 2.4%, p = 0.002). Compared to patients with neither NCEP- nor WHO-defined MES, only the group with MES defined by the WHO, but not NCEP, criterion had significantly higher mortality rate (2.6 vs. 6.8%, p hypertension, low BMI and albuminuria were the key predictors for these adverse events. In Chinese type 2 diabetic patients, the WHO criterion has a better discriminative power over the NCEP criterion for predicting death. Among the various components of the MES defined either by WHO or NCEP, hypertension, albuminuria and low BMI were the main predictors of cardiovascular and total mortality.

  9. Appetite predicts mortality in free-living older adults in association with dietary diversity. A NAHSIT cohort study.

    Science.gov (United States)

    Huang, Yi-Chen; Wahlqvist, Mark L; Lee, Meei-Shyuan

    2014-12-01

    This study aimed to assess the predictive ability of appetite for mortality among representative free-living Taiwanese older adults. A total of 1856 participants aged 65 years or over from the Elderly Nutrition and Health Survey during 1999-2000 completed an appetite question in a larger questionnaire. Personal information was obtained by face-to-face interview at baseline, together with a 24-hour dietary recall and simplified food frequency questionnaire which provided a dietary diversity score and food intake frequency. Survivorship was ascertained from the Death Registry until December 31, 2008. Participants with a poor appetite had lower dietary diversity scores (DDS) and intake frequencies of meat, fish and sea food, egg, vegetable and fruit intake, along with lower energy, protein, vitamin B-1, niacin, iron and phosphate intakes. Those who had fair and poor appetites had a higher risk of all-cause mortality compared to those with good appetite, with hazard ratios (HR) (95% confidence interval, CI) of 1.28 (1.03-1.58) and 2.27 (1.71-3.02), respectively. After adjustment for confounders, the HRs (95% CI) were 1.05 (0.83-1.33) and 1.50 (1.03-2.18), respectively. With further adjustment for DDS or general health these HRs became non-significant. The joint HR (95% CI) for "DDS ≤ 4 and poor appetite" was 1.77 (1.04-3.00) compared to "DDS > 4 and good appetite" as referent. Poor appetite is associated with lower food and nutrient intakes and an independent risk for mortality in older Taiwanese. In conclusion, appetite is separate, mediated by general health and modulated by dietary quality in its predictive capacity for mortality. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Maximum solid concentrations of coal water slurries predicted by neural network models

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Jun; Li, Yanchang; Zhou, Junhu; Liu, Jianzhong; Cen, Kefa

    2010-12-15

    The nonlinear back-propagation (BP) neural network models were developed to predict the maximum solid concentration of coal water slurry (CWS) which is a substitute for oil fuel, based on physicochemical properties of 37 typical Chinese coals. The Levenberg-Marquardt algorithm was used to train five BP neural network models with different input factors. The data pretreatment method, learning rate and hidden neuron number were optimized by training models. It is found that the Hardgrove grindability index (HGI), moisture and coalification degree of parent coal are 3 indispensable factors for the prediction of CWS maximum solid concentration. Each BP neural network model gives a more accurate prediction result than the traditional polynomial regression equation. The BP neural network model with 3 input factors of HGI, moisture and oxygen/carbon ratio gives the smallest mean absolute error of 0.40%, which is much lower than that of 1.15% given by the traditional polynomial regression equation. (author)

  11. Watershed regressions for pesticides (WARP) for predicting atrazine concentration in Corn Belt streams

    Science.gov (United States)

    Stone, Wesley W.; Gilliom, Robert J.

    2011-01-01

    Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, can be improved for application to the U.S. Corn Belt region by developing region-specific models that include important watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP-CB) were developed for predicting annual maximum moving-average (14-, 21-, 30-, 60-, and 90-day durations) and annual 95th-percentile atrazine concentrations in streams of the Corn Belt region. All streams used in development of WARP-CB models drain watersheds with atrazine use intensity greater than 17 kilograms per square kilometer (kg/km2). The WARP-CB models accounted for 53 to 62 percent of the variability in the various concentration statistics among the model-development sites.

  12. Ruptured Abdominal Aortic Aneurysm: Prediction of Mortality From Clinical Presentation and Glasgow Aneurysm Score.

    Science.gov (United States)

    Weingarten, Toby N; Thompson, Lauren T; Licatino, Lauren K; Bailey, Christopher H; Schroeder, Darrell R; Sprung, Juraj

    2016-04-01

    To examine association of presenting clinical acuity and Glasgow Aneurysm Score (GAS) with perioperative and 1-year mortality. Retrospective chart review. Major tertiary care facility. Patients with ruptured abdominal aortic aneurysm (rAAA) from 2003 through 2013. Emergency repair of rAAA. The authors reviewed outcomes after stable versus unstable presentation and by GAS. Unstable presentation included hypotension, cardiac arrest, loss of consciousness, and preoperative tracheal intubation. In total, 125 patients (40 stable) underwent repair. Perioperative mortality rates were 41% and 12% in unstable and stable patients, respectively (pClinical presentation and GAS identified patients with rAAA who were likely to have a poor surgical outcome. GAS≥96 was associated with poor long-term survival, but>20% of these patients survived 1 year. Thus, neither clinical presentation nor GAS provided reliable guidance for decisions regarding futility of surgery. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Predicting the natural mortality of marine fish from life history characteristics

    DEFF Research Database (Denmark)

    Gislason, Henrik

    For fish much of the life history is determined by body size. Body size and asymptotic size significantly influences important life history processes such as growth, maturity, egg production, and natural mortality. Futhermore, for a population to persist, offspring must be able to replace...... their parents on a one-for-one basis in the long run. Otherwise the population would either increase exponentially or become extinct. Combining data on growth and specific fecundity in a size-based fish community model of the North Sea and using the requirement of a one-for-one replacement provides...... the information necessary to estimate the scaling of natural mortality with size and asymptotic size. The estimated scaling is compared with output from multispecies fish stock models, with the empirical scaling of the maximum number of recruits per unit of spawning stock biomass with body size...

  14. Butyrylcholinesterase Levels on Admission Predict Severity and 12-Month Mortality in Hospitalized AIDS Patients

    Science.gov (United States)

    Xu, Lijun; Huang, Ying; Yang, Zongxing; Sun, Jia; Xu, Yan; Zheng, Jinlei; Kinloch, Sabine; Yin, Michael T.; Weng, Honglei

    2018-01-01

    Background Butyrylcholinesterase (BChE) is synthesized mainly in the liver and an important marker in many infectious/inflammatory diseases, but its role in acquired immunodeficiency syndrome (AIDS) patients is not clear. We wished to ascertain if BChE level is associated with the progression/prognosis of AIDS patients. Methods BChE levels (in U/L) were measured in 505 patients; assessed. Kaplan–Meier curves and Cox proportional hazards model were used to assess associations between low BChE levels and mortality, after adjustment for age, CD4 count, WHO stage, and laboratory parameters. Results A total of 129 patients (25.5%) had a lower BChE level. BChE was closely associated with CD4 count, WHO stage, CRP level, and BMI (all P AIDS severity and is an independent risk factor for increased mortality in AIDS patients. PMID:29736152

  15. Prediction of Coal Face Gas Concentration by Multi-Scale Selective Ensemble Hybrid Modeling

    Directory of Open Access Journals (Sweden)

    WU Xiang

    2014-06-01

    Full Text Available A selective ensemble hybrid modeling prediction method based on wavelet transformation is proposed to improve the fitting and generalization capability of the existing prediction models of the coal face gas concentration, which has a strong stochastic volatility. Mallat algorithm was employed for the multi-scale decomposition and single-scale reconstruction of the gas concentration time series. Then, it predicted every subsequence by sparsely weighted multi unstable ELM(extreme learning machine predictor within method SERELM(sparse ensemble regressors of ELM. At last, it superimposed the predicted values of these models to obtain the predicted values of the original sequence. The proposed method takes advantage of characteristics of multi scale analysis of wavelet transformation, accuracy and fast characteristics of ELM prediction and the generalization ability of L1 regularized selective ensemble learning method. The results show that the forecast accuracy has large increase by using the proposed method. The average relative error is 0.65%, the maximum relative error is 4.16% and the probability of relative error less than 1% reaches 0.785.

  16. Reduced brain/serum glucose ratios predict cerebral metabolic distress and mortality after severe brain injury.

    Science.gov (United States)

    Kurtz, Pedro; Claassen, Jan; Schmidt, J Michael; Helbok, Raimund; Hanafy, Khalid A; Presciutti, Mary; Lantigua, Hector; Connolly, E Sander; Lee, Kiwon; Badjatia, Neeraj; Mayer, Stephan A

    2013-12-01

    The brain is dependent on glucose to meet its energy demands. We sought to evaluate the potential importance of impaired glucose transport by assessing the relationship between brain/serum glucose ratios, cerebral metabolic distress, and mortality after severe brain injury. We studied 46 consecutive comatose patients with subarachnoid or intracerebral hemorrhage, traumatic brain injury, or cardiac arrest who underwent cerebral microdialysis and intracranial pressure monitoring. Continuous insulin infusion was used to maintain target serum glucose levels of 80-120 mg/dL (4.4-6.7 mmol/L). General linear models of logistic function utilizing generalized estimating equations were used to relate predictors of cerebral metabolic distress (defined as a lactate/pyruvate ratio [LPR] ≥ 40) and mortality. A total of 5,187 neuromonitoring hours over 300 days were analyzed. Mean serum glucose was 133 mg/dL (7.4 mmol/L). The median brain/serum glucose ratio, calculated hourly, was substantially lower (0.12) than the expected normal ratio of 0.40 (brain 2.0 and serum 5.0 mmol/L). In addition to low cerebral perfusion pressure (P = 0.05) and baseline Glasgow Coma Scale score (P brain/serum glucose ratios below the median of 0.12 were independently associated with an increased risk of metabolic distress (adjusted OR = 1.4 [1.2-1.7], P brain/serum glucose ratios were also independently associated with in-hospital mortality (adjusted OR = 6.7 [1.2-38.9], P brain/serum glucose ratios, consistent with impaired glucose transport across the blood brain barrier, are associated with cerebral metabolic distress and increased mortality after severe brain injury.

  17. SuPAR predicts postoperative complications and mortality in patients with asymptomatic aortic stenosis

    DEFF Research Database (Denmark)

    Hodges, Gethin W; Bang, Casper N; Eugen-Olsen, Jesper

    2018-01-01

    complications with a HR of 2.7 (95% CI 1.5 to 5.1, P=0.002), per doubling in suPAR. After adjusting for the European System for Cardiac Operative Risk Evaluation or Society of Thoracic Surgeons risk score, suPAR remained associated with postoperative mortality with a HR 3.2 (95% CI 1.2 to 8.6, P=0.025) and 2...

  18. Single living predicts a higher mortality in both women and men with chronic heart failure.

    Science.gov (United States)

    Mard, Shan; Nielsen, Finn Erland

    2016-09-01

    We examined the impact of single living on all-cause mortality in patients with chronic heart failure and determined if this association was modified by gender. This historical cohort study included 637 patients who were admitted to the Department of Cardiology, Herlev Hospital, Denmark, between 1 July 2005 and 30 June 2007. Baseline clinical data were obtained from patient records. Data on survival rates were obtained from the Danish Civil Registration System. Cox proportional hazard analysis was used to compute the hazard ratio (HR) of all-cause mortality, controlling for confounding factors. The median follow-up time was 2.8 years. A total of 323 (50.7%) patients died during the follow-up period. After adjustment for confounding factors, risk of death was associated with being single (HR = 1.53 (95% confidence interval: 1.19-1.96)). In a gender-stratified analysis, the risk of death did not differ among single-living women and men. Single living is a prognostic determinant of all-cause mortality in men and women with chronic heart failure. none. not relevant.

  19. Single living predicts a higher mortality in both women and men with chronic heart failure

    DEFF Research Database (Denmark)

    Mard, Shan; Nielsen, Finn Erland

    2016-01-01

    INTRODUCTION: We examined the impact of single living on all-cause mortality in patients with chronic heart failure and determined if this association was modified by gender. METHODS: This historical cohort study included 637 patients who were admitted to the Department of Cardiology, Herlev Hosp......, the risk of death did not differ among single-living women and men. CONCLUSION: Single living is a prognostic determinant of all-cause mortality in men and women with chronic heart failure. FUNDING: none. TRIAL REGISTRATION: not relevant.......INTRODUCTION: We examined the impact of single living on all-cause mortality in patients with chronic heart failure and determined if this association was modified by gender. METHODS: This historical cohort study included 637 patients who were admitted to the Department of Cardiology, Herlev...... for confounding factors. RESULTS: The median follow-up time was 2.8 years. A total of 323 (50.7%) patients died during the follow-up period. After adjustment for confounding factors, risk of death was associated with being single (HR = 1.53 (95% confidence interval: 1.19-1.96)). In a gender-stratified analysis...

  20. The use of customised versus population-based birthweight standards in predicting perinatal mortality.

    Science.gov (United States)

    Zhang, X; Platt, R W; Cnattingius, S; Joseph, K S; Kramer, M S

    2007-04-01

    The objective of this study was to critically examine potential artifacts and biases underlying the use of 'customised' standards of birthweight for gestational age (GA). Population-based cohort study. Sweden. A total of 782,303 singletons > or =28 weeks of gestation born in 1992-2001 to Nordic mothers with complete data on birthweight; GA; and maternal age, parity, height, and pre-pregnancy weight. We compared perinatal mortality in four groups of infants based on the following classification of small for gestational age (SGA): non-SGA based on either population-based or customised standards (the reference group), SGA based on the population-based standard only, SGA based on the customised standard only, and SGA according to both standards. We used graphical methods to compare GA-specific birthweight cutoffs for SGA using the two standards and also used logistic regression to control for differences in GA and maternal pre-pregnancy body mass index (BMI) in the four groups. Perinatal mortality, including stillbirth and neonatal death. Customisation led to a large artifactual increase in the proportion of SGA infants born preterm. Adjustment for differences in GA and maternal BMI markedly reduced the excess risk among infants classified as SGA by customised standards only. The large increase in perinatal mortality risk among infants classified as SGA based on customised standards is largely an artifact due to inclusion of more preterm births.

  1. Predicting and measurement of pH of seawater reverse osmosis concentrates

    KAUST Repository

    Waly, Tarek

    2011-10-01

    The pH of seawater reverse osmosis plants (SWRO) is the most influential parameter in determining the degree of supersaturation of CaCO3 in the concentrate stream. For this, the results of pH measurements of the concentrate of a seawater reverse osmosis pilot plant were compared with pH calculations based on the CO2-HCO3 --CO3 2- system equilibrium equations. Results were compared with two commercial software programs from membrane suppliers and also the software package Phreeqc. Results suggest that the real concentrate pH is lower than that of the feed and that none of the used programs was able to predict correctly real pH values. In addition, the effect of incorporating the acidity constant calculated for NaCl medium or seawater medium showed a great influence on the concentrate pH determination. The HCO3 - and CO3 2- equilibrium equation using acidity constants developed for seawater medium was the only method able to predict correctly the concentrate pH. The outcome of this study indicated that the saturation level of the concentrate was lower than previously anticipated. This was confirmed by shutting down the acid and the antiscalants dosing without any signs of scaling over a period of 12 months. © 2011 Elsevier B.V.

  2. Soluble Suppression of Tumorigenicity-2 Predicts Hospital Mortality in Burn Patients: An Observational Prospective Cohort Pilot Study.

    Science.gov (United States)

    Ruiz-Castilla, Mireia; Bosacoma, Pau; Dos Santos, Bruce; Baena, Jacinto; Guilabert, Patricia; Marin-Corral, Judith; Masclans, Joan R; Roca, Oriol; Barret, Juan P

    2018-04-10

    The IL33/ST2 pathway has been implicated in the pathogenesis of different inflammatory diseases. Our aim was to analyze whether plasma levels of biomarkers involved in the IL33/ST2 axis might help to predict mortality in burn patients. Single-center prospective observational cohort pilot study performed at the Burns Unit of the Plastic and Reconstructive Surgery Department of the Vall d'Hebron University Hospital (Barcelona). All patients aged ≥18 years old with second or third-degree burns requiring admission to the Burns Unit were considered for inclusion. Blood samples were taken to measure levels of interleukins (IL)6, IL8, IL33, and soluble suppression of tumorigenicity-2 (sST2) within 24 h of admission to the Burns Unit and at day 3. Results are expressed as medians and interquartile ranges or as frequencies and percentages. Sixty-nine patients (58 [84.1%] male, mean age 52 [35-63] years, total body surface area burned 21% [13%-30%], Abbreviated Burn Severity Index 6 [4-8]) were included. Thirteen (18.8%) finally died in the Burns Unit. Plasma levels of sST2 measured at day 3 after admission demonstrated the best prediction accuracy for survival (area under the ROC curve 0.85 [0.71-0.99]; P < 0.001). The best cutoff point for the AUROC index was estimated to be 2,561. In the Cox proportional hazards model, after adjusting for potential confounding, a plasma sST2 level ≥2,561 measured at day 3 was significantly associated with mortality (HR 6.94 [1.73-27.74]; P = 0.006). Plasma sST2 at day 3 predicts hospital mortality in burn patients.

  3. Identification of enhanced cytokine generation following sepsis. Dream of magic bullet for mortality prediction and therapeutic evaluation

    Directory of Open Access Journals (Sweden)

    H Hamishehkar

    2010-09-01

    Full Text Available "n  "nBackground and the purpose of the study: sepsis is one of the most widespread and lethal disease in Intensive Care Units (ICU. Based on pathophisyology of sepsis, it seems that routine laboratory tests combined with analysis of pro-inflammatory cytokines plasma levels, help clinicians to have more information about disease progress and its correct management. "nMethods:This was a prospective observational study to determine the predictive role of Tumor Necrosis Factor alpha (TNF-α, Interleukin (IL-1β and IL-6 as three main pro-inflammatory cytokines and Acute Physiology and Chronic Health Evaluation (APACHE II and Sequential Organ Failure Assessment (SOFA as two scoring systems in mortality of critically ill patients with severe sepsis. Fifty and five patients with criteria of severe sepsis were included in this study. An exclusion criterion was post Cardiopulmonary Resuscitation (CPR status. Cytokines (TNF-α, IL-1β and IL-6 were assayed in the first, third and seventh days in blood of patients. Results and major conclusion:Among three measured cytokines, sequential levels of TNF-α and IL-6 showed significant differences between survivors and nonsurvivors. IL-6 had a good correlation with outcome and scoring systems during the period of this study. The areas under the receiver operating characteristic (AUROC curve indicated that APACHE II (0.858, 0.848, 0.861 and IL-6 (0.797, 0.799, 0.899 had discriminative power in prediction of mortality during sequental measured days. Multiple logestic regression analysis identified that evaluation of APACHE II and TNF-α in the first day and APACHE II and IL-6 in the third and seventh days of severe septic patients are independent outcome predictors. Results of this study suggest that IL-6 and APACHE II are useful cytokine and scoring systems respectively in prediction of mortality and clinical evaluation of severe septic patients.

  4. Does mortality risk of cigarette smoking depend on serum concentrations of persistent organic pollutants? Prospective investigation of the vasculature in Uppsala seniors (PIVUS study.

    Directory of Open Access Journals (Sweden)

    Duk-Hee Lee

    Full Text Available Cigarette smoking is an important cause of preventable death globally, but associations between smoking and mortality vary substantially across country and calendar time. Although methodological biases have been discussed, it is biologically plausible that persistent organic pollutants (POPs like polychlorinated biphenyls (PCBs and organochlorine (OC pesticides can affect this association. This study was performed to evaluate if associations of cigarette smoking with mortality were modified by serum concentrations of PCBs and OC pesticides. We evaluated cigarette smoking in 111 total deaths among 986 men and women aged 70 years in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS with mean follow-up for 7.7 years. The association between cigarette smoking and total mortality depended on serum concentration of PCBs and OC pesticides (P value for interaction = 0.02. Among participants in the highest tertile of the serum POPs summary score, former and current smokers had 3.7 (95% CI, 1.5-9.3 and 6.4 (95% CI, 2.3-17.7 times higher mortality hazard, respectively, than never smokers. In contrast, the association between cigarette smoking and total mortality among participants in the lowest tertile of the serum POPs summary score was much weaker and statistically non-significant. The strong smoking-mortality association observed among elderly people with high POPs was mainly driven by low risk of mortality among never smokers with high POPs. As smoking is increasing in many low-income and middle-income countries and POPs contamination is a continuing problem in these areas, the interactions between these two important health-related issues should be considered in future research.

  5. Sex/gender and socioeconomic differences in the predictive ability of self-rated health for mortality.

    Directory of Open Access Journals (Sweden)

    Akihiro Nishi

    Full Text Available BACKGROUND: Studies have reported that the predictive ability of self-rated health (SRH for mortality varies by sex/gender and socioeconomic group. The purpose of this study is to evaluate this relationship in Japan and explore the potential reasons for differences between the groups. METHODOLOGY/PRINCIPAL FINDINGS: The analyses in the study were based on the Aichi Gerontological Evaluation Study's (AGES 2003 Cohort Study in Chita Peninsula, Japan, which followed the four-year survival status of 14,668 community-dwelling people who were at least 65 years old at the start of the study. We first examined sex/gender and education-level differences in association with fair/poor SRH. We then estimated the sex/gender- and education-specific hazard ratios (HRs of mortality associated with lower SRH using Cox models. Control variables, including health behaviors (smoking and drinking, symptoms of depression, and chronic co-morbid conditions, were added to sequential regression models. The results showed men and women reported a similar prevalence of lower SRH. However, lower SRH was a stronger predictor of mortality in men (HR = 2.44 [95% confidence interval (CI: 2.14-2.80] than in women (HR = 1.88 [95% CI: 1.44-2.47]; p for sex/gender interaction = 0.018. The sex/gender difference in the predictive ability of SRH was progressively attenuated with the additional introduction of other co-morbid conditions. The predictive ability among individuals with high school education (HR = 2.39 [95% CI: 1.74-3.30] was similar to that among individuals with less than a high school education (HR = 2.14 [95% CI: 1.83-2.50]; p for education interaction = 0.549. CONCLUSIONS: The sex/gender difference in the predictive ability of SRH for mortality among this elderly Japanese population may be explained by male/female differences in what goes into an individual's assessment of their SRH, with males apparently weighting depressive symptoms more than

  6. An Improved Method of Predicting Extinction Coefficients for the Determination of Protein Concentration.

    Science.gov (United States)

    Hilario, Eric C; Stern, Alan; Wang, Charlie H; Vargas, Yenny W; Morgan, Charles J; Swartz, Trevor E; Patapoff, Thomas W

    2017-01-01

    Concentration determination is an important method of protein characterization required in the development of protein therapeutics. There are many known methods for determining the concentration of a protein solution, but the easiest to implement in a manufacturing setting is absorption spectroscopy in the ultraviolet region. For typical proteins composed of the standard amino acids, absorption at wavelengths near 280 nm is due to the three amino acid chromophores tryptophan, tyrosine, and phenylalanine in addition to a contribution from disulfide bonds. According to the Beer-Lambert law, absorbance is proportional to concentration and path length, with the proportionality constant being the extinction coefficient. Typically the extinction coefficient of proteins is experimentally determined by measuring a solution absorbance then experimentally determining the concentration, a measurement with some inherent variability depending on the method used. In this study, extinction coefficients were calculated based on the measured absorbance of model compounds of the four amino acid chromophores. These calculated values for an unfolded protein were then compared with an experimental concentration determination based on enzymatic digestion of proteins. The experimentally determined extinction coefficient for the native proteins was consistently found to be 1.05 times the calculated value for the unfolded proteins for a wide range of proteins with good accuracy and precision under well-controlled experimental conditions. The value of 1.05 times the calculated value was termed the predicted extinction coefficient. Statistical analysis shows that the differences between predicted and experimentally determined coefficients are scattered randomly, indicating no systematic bias between the values among the proteins measured. The predicted extinction coefficient was found to be accurate and not subject to the inherent variability of experimental methods. We propose the use of a

  7. Prediction of Dissolved Gas Concentrations in Transformer Oil Based on the KPCA-FFOA-GRNN Model

    Directory of Open Access Journals (Sweden)

    Jun Lin

    2018-01-01

    Full Text Available The purpose of analyzing the dissolved gas in transformer oil is to determine the transformer’s operating status and is an important basis for fault diagnosis. Accurate prediction of the concentration of dissolved gas in oil can provide an important reference for the evaluation of the state of the transformer. A combined predicting model is proposed based on kernel principal component analysis (KPCA and a generalized regression neural network (GRNN using an improved fruit fly optimization algorithm (FFOA to select the smooth factor. Firstly, based on the idea of using the dissolved gas ratio of oil to diagnose the transformer fault, gas concentration ratios are also used as characteristic parameters. Secondly, the main parameters are selected from the feature parameters using the KPCA method, and the GRNN is then used to predict the gas concentration in the transformer oil. In the training process of the network, the FFOA is used to select the smooth factor of the neural network. Through a concrete example, it is shown that the method proposed in this paper has better data fitting ability and more accurate prediction ability compared with the support vector machine (SVM and gray model (GM methods.

  8. Predicting glycogen concentration in the foot muscle of abalone using near infrared reflectance spectroscopy (NIRS).

    Science.gov (United States)

    Fluckiger, Miriam; Brown, Malcolm R; Ward, Louise R; Moltschaniwskyj, Natalie A

    2011-06-15

    Near infrared reflectance spectroscopy (NIRS) was used to predict glycogen concentrations in the foot muscle of cultured abalone. NIR spectra of live, shucked and freeze-dried abalones were modelled against chemically measured glycogen data (range: 0.77-40.9% of dry weight (DW)) using partial least squares (PLS) regression. The calibration models were then used to predict glycogen concentrations of test abalone samples and model robustness was assessed from coefficient of determination of the validation (R2(val)) and standard error of prediction (SEP) values. The model for freeze-dried abalone gave the best prediction (R2(val) 0.97, SEP=1.71), making it suitable for quantifying glycogen. Models for live and shucked abalones had R2(val) of 0.86 and 0.90, and SEP of 3.46 and 3.07 respectively, making them suitable for producing estimations of glycogen concentration. As glycogen is a taste-active component associated with palatability in abalone, this study demonstrated the potential of NIRS as a rapid method to monitor the factors associated with abalone quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. Evaluating Forest Vegetation Simulator predictions for southern Appalachian upland hardwoods with a modified mortality model

    Science.gov (United States)

    Philip J. Radtke; Nathan D. Herring; David L. Loftis; Chad E. Keyser

    2012-01-01

    Prediction accuracy for projected basal area and trees per acre was assessed for the growth and yield model of the Forest Vegetation Simulator Southern Variant (FVS-Sn). Data for comparison with FVS-Sn predictions were compiled from a collection of n

  10. Watershed regressions for pesticides (warp) models for predicting atrazine concentrations in Corn Belt streams

    Science.gov (United States)

    Stone, Wesley W.; Gilliom, Robert J.

    2012-01-01

    Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region-specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP-CB) were developed for annual maximum moving-average (14-, 21-, 30-, 60-, and 90-day durations) and annual 95th-percentile atrazine concentrations in streams of the Corn Belt region. The WARP-CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model-development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model-development sites. The WARP-CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine-use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP-CB models. The WARP-CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine-use intensities of 17 kg/km2 of watershed area or greater.

  11. Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.

    Science.gov (United States)

    Li, Xiang; Peng, Ling; Yao, Xiaojing; Cui, Shaolong; Hu, Yuan; You, Chengzeng; Chi, Tianhe

    2017-12-01

    Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13-24 h prediction tasks (MAPE = 31.47%). Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Ordinary kriging approach to predicting long-term particulate matter concentrations in seven major Korean cities

    Directory of Open Access Journals (Sweden)

    Sun-Young Kim

    2014-09-01

    Full Text Available Objectives Cohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to 10 μm in diameter (PM10 concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability. Methods We obtained hourly PM10 data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average PM10 concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared (R2 statistics were computed. Results Mean annual average PM10 concentrations in the seven major cities ranged between 45.5 and 66.0 μg/m3 (standard deviation=2.40 and 9.51 μg/m3, respectively. Cross-validated R2 values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had R2 values of zero. The national model produced a higher crossvalidated R2 (0.36 than those for the city-specific models. Conclusions In general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate PM10 source characteristics.

  13. Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation.

    Science.gov (United States)

    Bengtsson-Palme, Johan; Larsson, D G Joakim

    2016-01-01

    There are concerns that selection pressure from antibiotics in the environment may accelerate the evolution and dissemination of antibiotic-resistant pathogens. Nevertheless, there is currently no regulatory system that takes such risks into account. In part, this is due to limited knowledge of environmental concentrations that might exert selection for resistant bacteria. To experimentally determine minimal selective concentrations in complex microbial ecosystems for all antibiotics would involve considerable effort. In this work, our aim was to estimate upper boundaries for selective concentrations for all common antibiotics, based on the assumption that selective concentrations a priori need to be lower than those completely inhibiting growth. Data on Minimal Inhibitory Concentrations (MICs) were obtained for 111 antibiotics from the public EUCAST database. The 1% lowest observed MICs were identified, and to compensate for limited species coverage, predicted lowest MICs adjusted for the number of tested species were extrapolated through modeling. Predicted No Effect Concentrations (PNECs) for resistance selection were then assessed using an assessment factor of 10 to account for differences between MICs and minimal selective concentrations. The resulting PNECs ranged from 8 ng/L to 64 μg/L. Furthermore, the link between taxonomic similarity between species and lowest MIC was weak. This work provides estimated upper boundaries for selective concentrations (lowest MICs) and PNECs for resistance selection for all common antibiotics. In most cases, PNECs for selection of resistance were below available PNECs for ecotoxicological effects. The generated PNECs can guide implementation of compound-specific emission limits that take into account risks for resistance promotion. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  14. Validity of the CR-POSSUM model in surgery for colorectal cancer in Spain (CCR-CARESS study) and comparison with other models to predict operative mortality.

    Science.gov (United States)

    Baré, Marisa; Alcantara, Manuel Jesús; Gil, Maria José; Collera, Pablo; Pont, Marina; Escobar, Antonio; Sarasqueta, Cristina; Redondo, Maximino; Briones, Eduardo; Dujovne, Paula; Quintana, Jose Maria

    2018-01-29

    To validate and recalibrate the CR- POSSUM model and compared its discriminatory capacity with other European models such as POSSUM, P-POSSUM, AFC or IRCS to predict operative mortality in surgery for colorectal cancer. Prospective multicenter cohort study from 22 hospitals in Spain. We included patients undergoing planned or urgent surgery for primary invasive colorectal cancers between June 2010 and December 2012 (N = 2749). Clinical data were gathered through medical chart review. We validated and recalibrated the predictive models using logistic regression techniques. To calculate the discriminatory power of each model, we estimated the areas under the curve - AUC (95% CI). We also assessed the calibration of the models by applying the Hosmer-Lemeshow test. In-hospital mortality was 1.5% and 30-day mortality, 1.7%. In the validation process, the discriminatory power of the CR-POSSUM for predicting in-hospital mortality was 73.6%. However, in the recalibration process, the AUCs improved slightly: the CR-POSSUM reached 75.5% (95% CI: 67.3-83.7). The discriminatory power of the CR-POSSUM for predicting 30-day mortality was 74.2% (95% CI: 67.1-81.2) after recalibration; among the other models the POSSUM had the greatest discriminatory power, with an AUC of 77.0% (95% CI: 68.9-85.2). The Hosmer-Lemeshow test showed good fit for all the recalibrated models. The CR-POSSUM and the other models showed moderate capacity to discriminate the risk of operative mortality in our context, where the actual operative mortality is low. Nevertheless the IRCS might better predict in-hospital mortality, with fewer variables, while the CR-POSSUM could be slightly better for predicting 30-day mortality. Registered at: ClinicalTrials.gov Identifier: NCT02488161.

  15. The importance of different frequency bands in predicting subcutaneous glucose concentration in type 1 diabetic patients.

    Science.gov (United States)

    Lu, Yinghui; Gribok, Andrei V; Ward, W Kenneth; Reifman, Jaques

    2010-08-01

    We investigated the relative importance and predictive power of different frequency bands of subcutaneous glucose signals for the short-term (0-50 min) forecasting of glucose concentrations in type 1 diabetic patients with data-driven autoregressive (AR) models. The study data consisted of minute-by-minute glucose signals collected from nine deidentified patients over a five-day period using continuous glucose monitoring devices. AR models were developed using single and pairwise combinations of frequency bands of the glucose signal and compared with a reference model including all bands. The results suggest that: for open-loop applications, there is no need to explicitly represent exogenous inputs, such as meals and insulin intake, in AR models; models based on a single-frequency band, with periods between 60-120 min and 150-500 min, yield good predictive power (error bands produce predictions that are indistinguishable from those of the reference model as long as the 60-120 min period band is included; and AR models can be developed on signals of short length (approximately 300 min), i.e., ignoring long circadian rhythms, without any detriment in prediction accuracy. Together, these findings provide insights into efficient development of more effective and parsimonious data-driven models for short-term prediction of glucose concentrations in diabetic patients.

  16. Prediction of the HBS width and Xe concentration in grain matrix by the INFRA code

    International Nuclear Information System (INIS)

    Yang, Yong Sik; Lee, Chan Bok; Kim, Dae Ho; Kim, Young Min

    2004-01-01

    Formation of a HBS(High Burnup Structure) is an important phenomenon for the high burnup fuel performance and safety. For the prediction of the HBS(so called 'rim microstructure') proposed rim microstructure formation model, which is a function of the fuel temperature, grain size and fission rate, was inserted into the high burnup fuel performance code INFRA. During the past decades, various examinations have been performed to find the HBS formation mechanism and define HBS characteristics. In the HBEP(High Burnup Effects Program), several rods were examined by EPMA analysis to measure HBS width and these results were re-measured by improved technology including XRF and detail microstructure examination. Recently, very high burnup(∼100MWd/kgU) fuel examination results were reported by Manzel et al., and EPMA analysis results have been released. Using the measured EPMA analysis data, HBS formation prediction model of INFRA code are verified. HBS width prediction results are compared with measured ones and Xe concentration profile is compared with measured EPMA data. Calculated HBS width shows good agreement with measured data in a reasonable error range. Though, there are some difference in transition region and central region due to model limitation and fission gas release prediction error respectively, however, predicted Xe concentration in the fully developed HBS region shows a good agreement with the measured data. (Author)

  17. Osteoporosis markers on low-dose lung cancer screening chest computed tomography scans predict all-cause mortality

    Energy Technology Data Exchange (ETDEWEB)

    Buckens, C.F. [University Medical Center Utrecht, Radiology Department, Utrecht (Netherlands); University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Utrecht (Netherlands); Graaf, Y. van der [University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Utrecht (Netherlands); Verkooijen, H.M.; Mali, W.P.; Jong, P.A. de [University Medical Center Utrecht, Radiology Department, Utrecht (Netherlands); Isgum, I.; Mol, C.P. [University Medical Center Utrecht, Image Sciences Institute, Utrecht (Netherlands); Verhaar, H.J. [University Medical Center Utrecht, Department of Geriatric Medicine, Utrecht (Netherlands); Vliegenthart, R.; Oudkerk, M. [Medical Center Groningen, Department of Radiology, Utrecht (Netherlands); Aalst, C.M. van; Koning, H.J. de [Erasmus MC Rotterdam, Department of Public Health, Rotterdam (Netherlands)

    2015-01-15

    Further survival benefits may be gained from low-dose chest computed tomography (CT) by assessing vertebral fractures and bone density. We sought to assess the association between CT-measured vertebral fractures and bone density with all-cause mortality in lung cancer screening participants. Following a case-cohort design, lung cancer screening trial participants (N = 3,673) who died (N = 196) during a median follow-up of 6 years (inter-quartile range: 5.7-6.3) were identified and added to a random sample of N = 383 from the trial. We assessed vertebral fractures using Genant and acute;s semiquantative method on sagittal reconstructions and measured bone density (Hounsfield Units (HU)) in vertebrae. Cox proportional hazards modelling was used to determine if vertebral fractures or bone density were independently predictive of mortality. The prevalence of vertebral fractures was 35 % (95 % confidence interval 30-40 %) among survivors and 51 % (44-58 %) amongst cases. After adjusting for age, gender, smoking status, pack years smoked, coronary and aortic calcium volume and pulmonary emphysema, the adjusted hazard ratio (HR) for vertebral fracture was 2.04 (1.43-2.92). For each 10 HU decline in trabecular bone density, the adjusted HR was 1.08 (1.02-1.15). Vertebral fractures and bone density are independently associated with all-cause mortality. (orig.)

  18. Osteoporosis markers on low-dose lung cancer screening chest computed tomography scans predict all-cause mortality

    International Nuclear Information System (INIS)

    Buckens, C.F.; Graaf, Y. van der; Verkooijen, H.M.; Mali, W.P.; Jong, P.A. de; Isgum, I.; Mol, C.P.; Verhaar, H.J.; Vliegenthart, R.; Oudkerk, M.; Aalst, C.M. van; Koning, H.J. de

    2015-01-01

    Further survival benefits may be gained from low-dose chest computed tomography (CT) by assessing vertebral fractures and bone density. We sought to assess the association between CT-measured vertebral fractures and bone density with all-cause mortality in lung cancer screening participants. Following a case-cohort design, lung cancer screening trial participants (N = 3,673) who died (N = 196) during a median follow-up of 6 years (inter-quartile range: 5.7-6.3) were identified and added to a random sample of N = 383 from the trial. We assessed vertebral fractures using Genant and acute;s semiquantative method on sagittal reconstructions and measured bone density (Hounsfield Units (HU)) in vertebrae. Cox proportional hazards modelling was used to determine if vertebral fractures or bone density were independently predictive of mortality. The prevalence of vertebral fractures was 35 % (95 % confidence interval 30-40 %) among survivors and 51 % (44-58 %) amongst cases. After adjusting for age, gender, smoking status, pack years smoked, coronary and aortic calcium volume and pulmonary emphysema, the adjusted hazard ratio (HR) for vertebral fracture was 2.04 (1.43-2.92). For each 10 HU decline in trabecular bone density, the adjusted HR was 1.08 (1.02-1.15). Vertebral fractures and bone density are independently associated with all-cause mortality. (orig.)

  19. The interaction between individualism and wellbeing in predicting mortality: Survey of Health Ageing and Retirement in Europe.

    Science.gov (United States)

    Okely, Judith A; Weiss, Alexander; Gale, Catharine R

    2018-02-01

    The link between greater wellbeing and longevity is well documented. The aim of the current study was to test whether this association is consistent across individualistic and collectivistic cultures. The sample consisted of 13,596 participants from 11 European countries, each of which was assigned an individualism score according to Hofstede et al.'s (Cultures and organizations: software of the mind, McGraw Hill, New York, 2010) cultural dimension of individualism. We tested whether individualism moderated the cross-sectional association between wellbeing and self-rated health or the longitudinal association between wellbeing and mortality risk. Our analysis revealed a significant interaction between individualism and wellbeing such that the association between wellbeing and self-rated health or risk of mortality from cardiovascular disease was stronger in more individualistic countries. However, the interaction between wellbeing and individualism was not significant in analysis predicting all-cause mortality. Further prospective studies are needed to confirm our finding and to explore the factors responsible for this culturally dependent effect.

  20. Among nonagenarians, congruence between self-rated and proxy-rated health was low but both predicted mortality.

    Science.gov (United States)

    Vuorisalmi, Merja; Sarkeala, Tytti; Hervonen, Antti; Jylhä, Marja

    2012-05-01

    The congruence between self-rated global health (SRH) and proxy-rated global health (PRH), the factors associated with congruence between SRH and PRH, and their associations with mortality are examined using data from the Vitality 90+ study. The data consist of 213 pairs of subjects--aged 90 years and older--and proxies. The relationship between SRH and PRH was analyzed by chi-square test and Cohen's kappa. Logistic regression analysis was used to find out the factors that are associated with the congruence between health ratings. The association between SRH and PRH with mortality was studied using Cox proportional hazard models. The subjects rated their health more negatively than the proxies. Kappa value indicated only slight congruence between SRH and PRH, and they also predicted mortality differently. Good self-reported functional ability was associated with congruence between SRH and PRH. The results imply that the evaluation processes of SRH and PRH differ, and the measures are not directly interchangeable. Both measures are useful health indicators in very old age but SRH cannot be replaced by PRH in analyses. Copyright © 2012 Elsevier Inc. All rights reserved.

  1. Predicting short-term mortality and long-term survival for hospitalized US patients with alcoholic hepatitis.

    Science.gov (United States)

    Cuthbert, Jennifer A; Arslanlar, Sami; Yepuri, Jay; Montrose, Marc; Ahn, Chul W; Shah, Jessica P

    2014-07-01

    No study has evaluated current scoring systems for their accuracy in predicting short and long-term outcome of alcoholic hepatitis in a US population. We reviewed electronic records for patients with alcoholic liver disease (ALD) admitted to Parkland Memorial Hospital between January 2002 and August 2005. Data and outcomes for 148 of 1,761 admissions meeting pre-defined criteria were collected. The discriminant function (DF) was revised (INRdf) to account for changes in prothrombin time reagents that could potentially affect identification of risk using the previous DF threshold of >32. Admission and theoretical peak scores were calculated by use of the Model for End-stage Liver Disease (MELD). Analysis models compared five different scoring systems. INRdf was closely correlated with the old DF (r (2) = 0.95). Multivariate analysis of the data showed that survival for 28 days was significantly associated with a scoring system using a combination of age, bilirubin, coagulation status, and creatinine (p short-term mortality (p 50 % mortality at four weeks and >80 % mortality at six months without specific treatment.

  2. Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds.

    Science.gov (United States)

    Winchell, Michael F; Peranginangin, Natalia; Srinivasan, Raghavan; Chen, Wenlin

    2018-05-01

    Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km 2 , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization

  3. Evaluation of circulating proteins and hemodynamics towards predicting mortality in children with pulmonary arterial hypertension.

    Directory of Open Access Journals (Sweden)

    Brandie D Wagner

    Full Text Available Although many predictors have been evaluated, a set of strong independent prognostic mortality indicators has not been established in children with pediatric pulmonary arterial hypertension (PAH. The aim of this study was to identify a combination of clinical and molecular predictors of survival in PAH.This single-center, retrospective cohort study was performed from children with PAH between 2001 and 2008 at Children's Hospital Colorado. Blood samples from 83 patients (median age of 8.3 years-old were obtained. We retrospectively analyzed 46 variables, which included 27 circulating proteins, 7 demographic variables and 12 hemodynamic and echocardiographic variables for establishing the best predictors of mortality. A data mining approach was utilized to evaluate predictor variables and to uncover complex data structures while performing variable selection in high dimensional problems.Thirteen children (16% died during follow-up (median; 3.1 years and survival rates from time of sample collection at 1 year, 3 years and 5 years were 95%, 85% and 79%, respectively. A subset of potentially informative predictors were identified, the top four are listed here in order of importance: Tissue inhibitors of metalloproteinases-1 (TIMP-1, apolipoprotein-AI, RV/LV diastolic dimension ratio and age at diagnosis. In univariate analysis, TIMP-1 and apolipoprotein-AI had significant association with survival time (hazard ratio [95% confidence interval]: 1.25 [1.03, 1.51] and 0.70 [0.54-0.90], respectively. Patients grouped by TIMP-1 and apolipoprotein-AI values had significantly different survival risks (p<0.01.Important predictors of mortality were identified from a large number of circulating proteins and clinical markers in this cohort. If confirmed in other populations, measurement of a subset of these predictors could aid in management of pediatric PAH by identifying patients at risk for death. These findings also further support a role for the clinical

  4. C-reactive protein and homocysteine predict long-term mortality in young ischemic stroke patients.

    Science.gov (United States)

    Naess, Halvor; Nyland, Harald; Idicula, Titto; Waje-Andreassen, Ulrike

    2013-11-01

    We investigated the relationship between C-reactive protein (CRP) and homocysteine on follow-up and subsequent mortality in young ischemic stroke patients in a population-based study. Young ischemic stroke patients were followed-up on average 6 years after the index stroke. CRP and homocysteine levels were measured and risk factors were recorded, including myocardial infarction, diabetes mellitus, hypertension, smoking, alcoholism, and cancer. Stroke outcome was measured using the modified Rankin Scale score. Subsequent survival was obtained by examining the official population registry. Cox regression analyses were performed. In total, 198 patients were included in this study (82 [41%] women and 116 [59%] men). The mean age on follow-up was 47.8 years. In total, 36 (18.2%) patients died during the subsequent mean follow-up of 12.4 years. Cox regression analysis revealed that mortality was associated with CRP (hazard ratio [HR] 1.05; P=.001) and homocysteine levels (HR 1.04; P=.02) in patients without dissection. Kaplan-Meier curves grouped by dichotomized CRP (CRP≤1 v >1 mg/L) showed increasing separation between the survival curves, and likewise for dichotomized homocysteine (≤9 v >9 μg/L). There is an independent association between CRP and homocysteine levels obtained several years after ischemic stroke in young adults and subsequent mortality, even when adjusting for traditional risk factors. This association seems to continue for at least 12 years after the measurements. Copyright © 2013 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  5. Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales.

    Science.gov (United States)

    Collins, Sarah M; Oliver, Samantha K; Lapierre, Jean-Francois; Stanley, Emily H; Jones, John R; Wagner, Tyler; Soranno, Patricia A

    2017-07-01

    Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry

  6. A new body shape index predicts mortality hazard independently of body mass index.

    Directory of Open Access Journals (Sweden)

    Nir Y Krakauer

    Full Text Available Obesity, typically quantified in terms of Body Mass Index (BMI exceeding threshold values, is considered a leading cause of premature death worldwide. For given body size (BMI, it is recognized that risk is also affected by body shape, particularly as a marker of abdominal fat deposits. Waist circumference (WC is used as a risk indicator supplementary to BMI, but the high correlation of WC with BMI makes it hard to isolate the added value of WC.We considered a USA population sample of 14,105 non-pregnant adults (age ≥ 18 from the National Health and Nutrition Examination Survey (NHANES 1999-2004 with follow-up for mortality averaging 5 yr (828 deaths. We developed A Body Shape Index (ABSI based on WC adjusted for height and weight: ABSI ≡ WC/(BMI(2/3height(1/2. ABSI had little correlation with height, weight, or BMI. Death rates increased approximately exponentially with above average baseline ABSI (overall regression coefficient of +33% per standard deviation of ABSI [95% confidence interval: +20%-+48%, whereas elevated death rates were found for both high and low values of BMI and WC. 22% (8%-41% of the population mortality hazard was attributable to high ABSI, compared to 15% (3%-30% for BMI and 15% (4%-29% for WC. The association of death rate with ABSI held even when adjusted for other known risk factors including smoking, diabetes, blood pressure, and serum cholesterol. ABSI correlation with mortality hazard held across the range of age, sex, and BMI, and for both white and black ethnicities (but not for Mexican ethnicity, and was not weakened by excluding deaths from the first 3 yr of follow-up.Body shape, as measured by ABSI, appears to be a substantial risk factor for premature mortality in the general population derivable from basic clinical measurements. ABSI expresses the excess risk from high WC in a convenient form that is complementary to BMI and to other known risk factors.

  7. The prediction of concentration profiles for a NIMCIX column absorbing uranium from aqueous solution

    International Nuclear Information System (INIS)

    Wright, R.S.

    1979-01-01

    A procedure is proposed for the prediction of concentration profiles for a countercurrent ion-exchange absorption column, use being made of equilibrium and kinetic data derived from small-scale batch tests. A comparison is presented between the predictions and the measured performance of a column (2,5 m in diameter) absorbing uranium from solution. The method is shown to be adequate for design purposes provided that the data used are from tests in which the solution and resin conditions approximate those for which the plant is being designed [af

  8. Prognostic factors in patients with malignant pleural effusion: Is it possible to predict mortality in patients with good performance status?

    Science.gov (United States)

    Abrao, Fernando Conrado; Peixoto, Renata D'Alpino; de Abreu, Igor Renato Louro Bruno; Janini, Maria Cláudia; Viana, Geisa Garcia; de Oliveira, Mariana Campello; Younes, Riad Naim

    2016-04-01

    The aim of this study was to identify predictors of mortality only in patients with malignant pleural effusion (MPE) showing good performance status which required pleural palliative procedures. All patients with MPE submitted to pleural palliative procedure were enrolled in a prospective study between 2013 and 2014. Patients with Eastern cooperative oncology group (ECOG) score zero, one, and two were considered with good performance status. The possible prognostic factors were tested for significance using the log-rank test (Kaplan-Meier method) and those with significance on univariate analysis were entered into a multivariable Cox model. A total of 64 patients were included in the analysis. Median follow-up time for surviving patients was 263 days. Median survival for the entire cohort was not reached yet. In the multivariate analysis, gastrointestinal primary site (P = 0.006), low albumin concentration in the pleural fluid (P = 0.017), and high serum NLR (P = 0.007) were associated with mortality. In our cohort of ECOG 0-2 patients with MPE submitted to pleural palliative procedures, gastrointestinal malignancy compared to other sites, low pleural fluid albumin and high NLR were significantly associated with mortality. The identification of these prognostic factors may assist the choice of the optimal palliative technique. J. Surg. Oncol. 2016;113:570-574. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  9. The value of arterial blood gas parameters for prediction of mortality in survivors of out-of-hospital cardiac arrest

    Directory of Open Access Journals (Sweden)

    Katharina Isabel von Auenmueller

    2017-01-01

    Full Text Available Context: Sudden cardiac death is one of the leading causes of death in Europe, and early prognostication remains challenging. There is a lack of valid parameters for the prediction of survival after cardiac arrest. Aims: This study aims to investigate if arterial blood gas parameters correlate with mortality of patients after out-of-hospital cardiac arrest. Materials and Methods: All patients who were admitted to our hospital after resuscitation following out-of-hospital cardiac arrest between January 1, 2008, and December 31, 2013, were included in this retrospective study. The patient's survival 5 days after resuscitation defined the study end-point. For the statistical analysis, the mean, standard deviation, Student's t-test, Chi-square test, and logistic regression analyses were used (level of significance P< 0.05. Results: Arterial blood gas samples were taken from 170 patients. In particular, pH < 7.0 (odds ratio [OR]: 7.20; 95% confidence interval [CI]: 3.11–16.69; P< 0.001 and lactate ≥ 5.0 mmol/L (OR: 6.79; 95% CI: 2.77–16.66; P< 0.001 showed strong and independent correlations with mortality within the first 5 days after hospital admission. Conclusion: Our study results indicate that several arterial blood gas parameters correlate with mortality of patients after out-of-hospital resuscitation. The most relevant parameters are pH and lactate because they are strongly and independently associated with mortality within the first 5 days after resuscitation. Despite this correlation, none of these parameters by oneself is strong enough to allow an early prognostication. Still, these parameters can contribute as part of a multimodal approach to assessing the patients' prognosis.

  10. Youth, unemployment, and male gender predict mortality in AIDS patients started on HAART in Nigeria.

    Science.gov (United States)

    DeSilva, Malini B; Merry, Stephen P; Fischer, Philip R; Rohrer, James E; Isichei, Christian O; Cha, Stephen S

    2009-01-01

    This retrospective study identifies risk factors for mortality in a cohort of HIV-positive adult patients treated with highly active antiretroviral therapy (HAART) in Jos, Nigeria. We analyzed clinical data from a cohort of 1552 patients enrolled in a HIV/acquired immune deficiency syndrome treatment program and started on HAART between December 2004 and 30 April 2006. Death was our study endpoint. Patients were followed in the study until death, being lost to follow-up, or the end of data collection, 1 December 2006. Baseline patient characteristics were compared using Wilcoxon Rank Sum Test for continuous variables and Pearson Chi-Square test for categorical variables to determine if certain demographic factors were associated with more rapid progression to death. The Cox proportional hazard multivariate model analysis was used to find risk factors. As of 1 December 2006, a total of 104 cases progressed to death. In addition to the expected association of CD4 count less than 50 at initiation of therapy and active tuberculosis with mortality, the patient characteristics independently associated with a more rapid progression to death after initiation of HAART were male gender, age less than 30 years old, and unemployment or unknown occupation status. Future research is needed to identify the confounding variables that may be amenable to targeted interventions aimed at ameliorating these health disparities.

  11. Elevated soluble urokinase plasminogen activator receptor (suPAR) predicts mortality in Staphylococcus aureus bacteremia

    DEFF Research Database (Denmark)

    Mölkänen, T; Ruotsalainen, E; Thorball, C W

    2011-01-01

    The soluble form of urokinase-type plasminogen activator receptor (suPAR) is a new inflammatory marker. High suPAR levels have been shown to associate with mortality in cancer and in chronic infections like HIV and tuberculosis, but reports on the role of suPAR in acute bacteremic infections...... are scarce. To elucidate the role of suPAR in a common bacteremic infection, the serum suPAR levels in 59 patients with Staphylococcus aureus bacteremia (SAB) were measured using the suPARnostic ELISA assay and associations to 1-month mortality and with deep infection focus were analyzed. On day three, after...... the first positive blood culture for S. aureus, suPAR levels were higher in 19 fatalities (median 12.3; range 5.7-64.6 ng/mL) than in 40 survivors (median 8.4; range 3.7-17.6 ng/mL, p = 0.002). This difference persisted for 10 days. The presence of deep infection focus was not associated with elevated su...

  12. Prognostic value of tissue Doppler imaging for predicting ventricular arrhythmias and cardiovascular mortality in ischaemic cardiomyopathy

    DEFF Research Database (Denmark)

    Biering-Sørensen, Tor; Olsen, Flemming Javier; Storm, Katrine

    2016-01-01

    AIMS: Only 30% of patients receiving an implantable cardioverter defibrillator (ICD) for primary prevention receive appropriately therapy. We sought to investigate the value of tissue Doppler imaging (TDI) to predict ventricular tachycardia (VT), ventricular fibrillation (VF), and cardiovascular...

  13. Air pollution and associated human mortality: the role of air pollutant emissions, climate change and methane concentration increases from the preindustrial period to present

    Directory of Open Access Journals (Sweden)

    Y. Fang

    2013-02-01

    Full Text Available Increases in surface ozone (O3 and fine particulate matter (≤2.5 μm aerodynamic diameter, PM2.5 are associated with excess premature human mortalities. We estimate changes in surface O3 and PM2.5 from pre-industrial (1860 to present (2000 and the global present-day (2000 premature human mortalities associated with these changes. We extend previous work to differentiate the contribution of changes in three factors: emissions of short-lived air pollutants, climate change, and increased methane (CH4 concentrations, to air pollution levels and associated premature mortalities. We use a coupled chemistry-climate model in conjunction with global population distributions in 2000 to estimate exposure attributable to concentration changes since 1860 from each factor. Attributable mortalities are estimated using health impact functions of long-term relative risk estimates for O3 and PM2.5 from the epidemiology literature. We find global mean surface PM2.5 and health-relevant O3 (defined as the maximum 6-month mean of 1-h daily maximum O3 in a year have increased by 8 ± 0.16 μg m−3 and 30 ± 0.16 ppbv (results reported as annual average ±standard deviation of 10-yr model simulations, respectively, over this industrial period as a result of combined changes in emissions of air pollutants (EMIS, climate (CLIM and CH4 concentrations (TCH4. EMIS, CLIM and TCH4 cause global population-weighted average PM2.5 (O3 to change by +7.5 ± 0.19 μg m−3 (+25 ± 0.30 ppbv, +0.4 ± 0.17 μg m−3 (+0.5 ± 0.28 ppbv, and 0.04 ± 0.24 μg m−3 (+4.3 ± 0.33 ppbv, respectively. Total global changes in PM2.5 are associated with 1.5 (95% confidence interval, CI, 1.2–1.8 million cardiopulmonary mortalities and 95 (95% CI, 44–144 thousand lung cancer

  14. Air pollution and associated human mortality: The role of air pollutant emissions, climate change and methane concentration increases during the industrial period

    Science.gov (United States)

    Fang, Y.; Naik, V.; Horowitz, L. W.; Mauzerall, D. L.

    2012-12-01

    Increases in surface ozone (O3) and fine particulate matter (≤ 2.5μm aerodynamic diameter, PM2.5) are associated with excess premature human mortalities. Here we estimate changes in surface O3 and PM2.5 since preindustrial (1860) times and the global present-day (2000) premature human mortalities associated with these changes. We go beyond previous work to analyze and differentiate the contribution of three factors: changes in emissions of short-lived air pollutants, climate change, and increased methane (CH4) concentrations, to air pollution levels and the associated premature mortalities. We use a coupled chemistry-climate model in conjunction with global population distributions in 2000 to estimate exposure attributable to concentration changes since 1860 from each factor. Attributable mortalities are estimated using health impact functions of long-term relative risk estimates for O3 and PM2.5 from the epidemiology literature. We find global mean surface PM2.5 and health-relevant O3 (defined as the maximum 6-month mean of 1-hour daily maximum O3 in a year) have increased by 8±0.16 μg/m3 and 30±0.16 ppbv, respectively, over this industrial period as a result of combined changes in emissions of air pollutants (EMIS), climate (CLIM) and CH4 concentrations (TCH4). EMIS, CLIM and TCH4 cause global average PM2.5 (O3) to change by +7.5±0.19 μg/m3 (+25±0.30 ppbv), +0.4±0.17 μg/m3 (+0.5±0.28 ppbv), and -0.02±0.01 μg/m3 (+4.3±0.33 ppbv), respectively. Total changes in PM2.5 are associated with 1.5 (95% confidence interval, CI, 1.0-2.5) million all-cause mortalities annually and in O3 are associated with 375 (95% CI, 129-592) thousand respiratory mortalities annually. Most air pollution mortality is driven by changes in emissions of short-lived air pollutants and their precursors (95% and 85% of mortalities from PM2.5 and O3 respectively). However, changing climate and increasing CH4 concentrations also increased premature mortality associated with air

  15. MLP based models to predict PM10, O3 concentrations, in Sines industrial area

    Science.gov (United States)

    Durao, R.; Pereira, M. J.

    2012-04-01

    Sines is an important Portuguese industrial area located southwest cost of Portugal with important nearby protected natural areas. The main economical activities are related with this industrial area, the deep-water port, petrochemical and thermo-electric industry. Nevertheless, tourism is also an important economic activity especially in summer time with potential to grow. The aim of this study is to develop prediction models of pollutant concentration categories (e.g. low concentration and high concentration) in order to provide early warnings to the competent authorities who are responsible for the air quality management. The knowledge in advanced of pollutant high concentrations occurrence will allow the implementation of mitigation actions and the release of precautionary alerts to population. The regional air quality monitoring network consists in three monitoring stations where a set of pollutants' concentrations are registered on a continuous basis. From this set stands out the tropospheric ozone (O3) and particulate matter (PM10) due to the high concentrations occurring in the region and their adverse effects on human health. Moreover, the major industrial plants of the region monitor SO2, NO2 and particles emitted flows at the principal chimneys (point sources), also on a continuous basis,. Therefore Artificial neuronal networks (ANN) were the applied methodology to predict next day pollutant concentrations; due to the ANNs structure they have the ability to capture the non-linear relationships between predictor variables. Hence the first step of this study was to apply multivariate exploratory techniques to select the best predictor variables. The classification trees methodology (CART) was revealed to be the most appropriate in this case.. Results shown that pollutants atmospheric concentrations are mainly dependent on industrial emissions and a complex combination of meteorological factors and the time of the year. In the second step, the Multi

  16. High and increasing Oxa-51 DNA load predict mortality in Acinetobacter baumannii bacteremia: implication for pathogenesis and evaluation of therapy.

    Directory of Open Access Journals (Sweden)

    Yu-Chung Chuang

    Full Text Available BACKGROUND: While quantification of viral loads has been successfully employed in clinical medicine and has provided valuable insights and useful markers for several viral diseases, the potential of measuring bacterial DNA load to predict outcome or monitor therapeutic responses remains largely unexplored. We tested this possibility by investigating bacterial loads in Acinetobacter baumannii bacteremia, a rapidly increasing nosocomial infection characterized by high mortality, drug resistance, multiple and complicated risk factors, all of which urged the need of good markers to evaluate therapeutics. METHODS AND FINDINGS: We established a quantitative real-time PCR assay based on an A. baumannii-specific gene, Oxa-51, and conducted a prospective study to examine A. baumannii loads in 318 sequential blood samples from 51 adults patients (17 survivors, 34 nonsurvivors with culture-proven A. baumannii bacteremia in the intensive care units. Oxa-51 DNA loads were significantly higher in the nonsurvivors than survivors on day 1, 2 and 3 (P=0.03, 0.001 and 0.006, respectively. Compared with survivors, nonsurvivors had higher maximum Oxa-51 DNA load and a trend of increase from day 0 to day 3 (P<0.001, which together with Pitt bacteremia score were independent predictors for mortality by multivariate analysis (P=0.014 and 0.016, for maximum Oxa-51 DNA and change of Oxa-51 DNA, respectively. Kaplan-Meier analysis revealed significantly different survival curves in patients with different maximum Oxa-51 DNA and change of Oxa-51 DNA from day 0 to day 3. CONCLUSIONS: High Oxa-51 DNA load and its initial increase could predict mortality. Moreover, monitoring Oxa-51 DNA load in blood may provide direct parameters for evaluating new regimens against A. baumannii in future clinical studies.

  17. Increased circulating D-lactate levels predict risk of mortality after hemorrhage and surgical trauma in baboons.

    Science.gov (United States)

    Sobhian, Babak; Kröpfl, Albert; Hölzenbein, Thomas; Khadem, Anna; Redl, Heinz; Bahrami, Soheyl

    2012-05-01

    Patients with hemorrhagic shock and/or trauma are at risk of developing colonic ischemia associated with bacterial translocation that may lead to multiple organ failure and death. Intestinal ischemia is difficult to diagnose noninvasively. The present retrospective study was designed to determine whether circulating plasma D-lactate is associated with mortality in a clinically relevant two-hit model in baboons. Hemorrhagic shock was induced in anesthetized baboons (n = 24) by controlled bleeding (mean arterial pressure, 40 mmHg), base excess (maximum -5 mmol/L), and time (maximum 3 h). To mimic clinical setting more closely, all animals underwent a surgical trauma after resuscitation including midshaft osteotomy stabilized with reamed femoral interlocking nailing and were followed for 7 days. Hemorrhagic shock/surgical trauma resulted in 66% mortality by day 7. In nonsurvivor (n = 16) hemorrhagic shock/surgical trauma baboons, circulating D-lactate levels were significantly increased (2-fold) at 24 h compared with survivors (n = 8), whereas the early increase during hemorrhage and resuscitation declined during the early postresuscitation phase with no difference between survivors and nonsurvivors. Moreover, D-lactate levels remained elevated in the nonsurvival group until death, whereas it decreased to baseline in survivors. Prediction of death (receiver operating characteristic test) by D-lactate was accurate with an area under the curve (days 1-3 after trauma) of 0.85 (95% confidence interval, 0.72-0.93). The optimal D-lactate cutoff value of 25.34 μg/mL produced sensitivity of 73% to 99% and specificity of 50% to 83%. Our data suggest that elevation of plasma D-lactate after 24 h predicts an increased risk of mortality after hemorrhage and trauma.

  18. The Abdominal Aortic Aneurysm Statistically Corrected Operative Risk Evaluation (AAA SCORE) for predicting mortality after open and endovascular interventions.

    Science.gov (United States)

    Ambler, Graeme K; Gohel, Manjit S; Mitchell, David C; Loftus, Ian M; Boyle, Jonathan R

    2015-01-01

    Accurate adjustment of surgical outcome data for risk is vital in an era of surgeon-level reporting. Current risk prediction models for abdominal aortic aneurysm (AAA) repair are suboptimal. We aimed to develop a reliable risk model for in-hospital mortality after intervention for AAA, using rigorous contemporary statistical techniques to handle missing data. Using data collected during a 15-month period in the United Kingdom National Vascular Database, we applied multiple imputation methodology together with stepwise model selection to generate preoperative and perioperative models of in-hospital mortality after AAA repair, using two thirds of the available data. Model performance was then assessed on the remaining third of the data by receiver operating characteristic curve analysis and compared with existing risk prediction models. Model calibration was assessed by Hosmer-Lemeshow analysis. A total of 8088 AAA repair operations were recorded in the National Vascular Database during the study period, of which 5870 (72.6%) were elective procedures. Both preoperative and perioperative models showed excellent discrimination, with areas under the receiver operating characteristic curve of .89 and .92, respectively. This was significantly better than any of the existing models (area under the receiver operating characteristic curve for best comparator model, .84 and .88; P AAA repair. These models were carefully developed with rigorous statistical methodology and significantly outperform existing methods for both elective cases and overall AAA mortality. These models will be invaluable for both preoperative patient counseling and accurate risk adjustment of published outcome data. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

  19. Predicting the concentration of residual methanol in industrial formalin using machine learning

    OpenAIRE

    Heidkamp, William

    2016-01-01

    In this thesis, a machine learning approach was used to develop a predictive model for residual methanol concentration in industrial formalin produced at the Akzo Nobel factory in Kristinehamn, Sweden. The MATLABTM computational environment supplemented with the Statistics and Machine LearningTM toolbox from the MathWorks were used to test various machine learning algorithms on the formalin production data from Akzo Nobel. As a result, the Gaussian Process Regression algorithm was found to pr...

  20. [Carboxyhemoglobin concentration in carbon monoxide poisoning. Critical appraisal of the predictive value].

    Science.gov (United States)

    Köthe, L; Radke, J

    2010-06-01

    In cases of unclear depression of conciousness, arrhythmia and symptoms of cardiac insufficiency inadvertent carbon monoxide intoxication should always be taken into consideration. Rapid diagnosis of acute carbon monoxide intoxication with mostly unspecific symptoms requires an immediate supply of high dose oxygen which enables a distinct reduction of mortality and long-term morbidity. Levels of carboxyhemoglobin, however, should not be used as a parameter to decide whether to supply normobaric or the more efficient hyperbaric oxygen. There is no sufficient coherence between carboxyhemoglobin blood levels and clinical symptoms. Increased carboxyhemoglobin concentrations help to diagnose acute carbon monoxide intoxication but do not allow conclusions to be drawn about possible long-term neuropsychiatric or cardiac consequences.

  1. Basic model for the prediction of 137Cs concentration in the organisms of detritus food chain

    International Nuclear Information System (INIS)

    Tateda, Yuzuru

    1997-01-01

    In order to predict 137 Cs concentrations in marine organisms for monitoring, a basic model for the prediction of nuclide levels in marine organisms of detritus food chain was studied. The equilibrated values of ( 137 Cs level in organism)/( 137 Cs level in seawater) derived from calculation agreed with the observed data, indicating validity of modeling conditions. The result of simulation by this basic model showed the following conclusions. 1) ''Ecological half-life'' of 137 Cs in organisms of food chain were 35 and 130 days for detritus feeder and benthic teleosts, respectively, indicating that there was no difference of the ecological half lives in organisms between in detritus food chain and in other food chains. 2) The 137 Cs concentration in organisms showed a peak at 18 and 100 days in detritus and detritus feeder, respectively, after the introduction of 137 Cs into environmental seawater. Their concentration ratios to 137 Cs peak level in seawater were within a range of 2.7-3.8, indicating insignificant difference in the response to 137 Cs change in seawater between in the organisms of detritus food chain and of other food chain. 3) The basic model studies makes it available that the prediction of 137 Cs level in organisms of food chain can be simulated in coastal ecosystem. (author)

  2. Predicting mortality in sick African children: the FEAST Paediatric Emergency Triage (PET) Score.

    Science.gov (United States)

    George, Elizabeth C; Walker, A Sarah; Kiguli, Sarah; Olupot-Olupot, Peter; Opoka, Robert O; Engoru, Charles; Akech, Samuel O; Nyeko, Richard; Mtove, George; Reyburn, Hugh; Berkley, James A; Mpoya, Ayub; Levin, Michael; Crawley, Jane; Gibb, Diana M; Maitland, Kathryn; Babiker, Abdel G

    2015-07-31

    Mortality in paediatric emergency care units in Africa often occurs within the first 24 h of admission and remains high. Alongside effective triage systems, a practical clinical bedside risk score to identify those at greatest risk could contribute to reducing mortality. Data collected during the Fluid As Expansive Supportive Therapy (FEAST) trial, a multi-centre trial involving 3,170 severely ill African children, were analysed to identify clinical and laboratory prognostic factors for mortality. Multivariable Cox regression was used to build a model in this derivation dataset based on clinical parameters that could be quickly and easily assessed at the bedside. A score developed from the model coefficients was externally validated in two admissions datasets from Kilifi District Hospital, Kenya, and compared to published risk scores using Area Under the Receiver Operating Curve (AUROC) and Hosmer-Lemeshow tests. The Net Reclassification Index (NRI) was used to identify additional laboratory prognostic factors. A risk score using 8 clinical variables (temperature, heart rate, capillary refill time, conscious level, severe pallor, respiratory distress, lung crepitations, and weak pulse volume) was developed. The score ranged from 0-10 and had an AUROC of 0.82 (95 % CI, 0.77-0.87) in the FEAST trial derivation set. In the independent validation datasets, the score had an AUROC of 0.77 (95 % CI, 0.72-0.82) amongst admissions to a paediatric high dependency ward and 0.86 (95 % CI, 0.82-0.89) amongst general paediatric admissions. This discriminative ability was similar to, or better than other risk scores in the validation datasets. NRI identified lactate, blood urea nitrogen, and pH to be important prognostic laboratory variables that could add information to the clinical score. Eight clinical prognostic factors that could be rapidly assessed by healthcare staff for triage were combined to create the FEAST Paediatric Emergency Triage (PET) score and externally

  3. Amikacin Concentrations Predictive of Ototoxicity in Multidrug-Resistant Tuberculosis Patients.

    Science.gov (United States)

    Modongo, Chawangwa; Pasipanodya, Jotam G; Zetola, Nicola M; Williams, Scott M; Sirugo, Giorgio; Gumbo, Tawanda

    2015-10-01

    Aminoglycosides, such as amikacin, are used to treat multidrug-resistant tuberculosis. However, ototoxicity is a common problem and is monitored using peak and trough amikacin concentrations based on World Health Organization recommendations. Our objective was to identify clinical factors predictive of ototoxicity using an agnostic machine learning method. We used classification and regression tree (CART) analyses to identify clinical factors, including amikacin concentration thresholds that predicted audiometry-confirmed ototoxicity among 28 multidrug-resistant pulmonary tuberculosis patients in Botswana. Amikacin concentrations were measured for all patients. The quantitative relationship between predictive factors and the probability of ototoxicity were then identified using probit analyses. The primary predictors of ototoxicity on CART analyses were cumulative days of therapy, followed by cumulative area under the concentration-time curve (AUC), which improved on the primary predictor by 87%. The area under the receiver operating curve was 0.97 on the test set. Peak and trough were not predictors in any tree. When algorithms were forced to pick peak and trough as primary predictors, the area under the receiver operating curve fell to 0.46. Probit analysis revealed that the probability of ototoxicity increased sharply starting after 6 months of therapy to near maximum at 9 months. A 10% probability of ototoxicity occurred with a threshold cumulative AUC of 87,232 days · mg · h/liter, while that of 20% occurred at 120,000 days · mg · h/liter. Thus, cumulative amikacin AUC and duration of therapy, and not peak and trough concentrations, should be used as the primary decision-making parameters to minimize the likelihood of ototoxicity in multidrug-resistant tuberculosis. Copyright © 2015, Modongo et al.

  4. Prothrombin time is predictive of low plasma prothrombin concentration and clinical outcome in patients with trauma hemorrhage: analyses of prospective observational cohort studies.

    Science.gov (United States)

    Balendran, Clare A; Lövgren, Ann; Hansson, Kenny M; Nelander, Karin; Olsson, Marita; Johansson, Karin J; Brohi, Karim; Fries, Dietmar; Berggren, Anders

    2017-03-14

    Fibrinogen and prothrombin have been suggested to become rate limiting in trauma associated coagulopathy. Administration of fibrinogen is now recommended, however, the importance of prothrombin to patient outcome is unknown. We have utilized two trauma patient databases (database 1 n = 358 and database 2 n = 331) to investigate the relationship of plasma prothrombin concentration on clinical outcome and coagulation status. Database 1 has been used to assess the relationship of plasma prothrombin to administered packed red blood cells (PRBC), clinical outcome and coagulation biomarkers (Prothrombin Time (PT), ROTEM EXTEM Coagulation Time (CT) and Maximum Clot Firmness (MCF)). ROC analyses have been performed to investigate the ability of admission coagulation biomarkers to predict low prothrombin concentration (database 1), massive transfusion and 24 h mortality (database 1 and 2). The importance of prothrombin was further investigated in vitro by PT and ROTEM assays in the presence of a prothrombin neutralizing monoclonal antibody and following step-wise dilution. Patients who survived the first 24 h had higher admission prothrombin levels compared to those who died (94 vs.67 IU/dL). Patients with lower transfusion requirements within the first 24 h (≤10 units of PRBCs) also had higher admission prothrombin levels compared to patients with massive transfusion demands (>10 units of PRBCs) (95 vs.62 IU/dL). Admission PT, in comparison to admission ROTEM EXTEM CT and MCF, was found to be a better predictor of prothrombin concentration <60 IU/dL (AUC 0.94 in database 1), of massive transfusion (AUC 0.92 and 0.81 in database 1 and 2 respectively) and 24 h mortality (AUC 0.90 and 0.78 in database 1 and 2, respectively). In vitro experiments supported a critical role for prothrombin in coagulation and demonstrated that PT and ROTEM EXTEM CT are sensitive methods to measure low prothrombin concentration. Our analyses suggest that prothrombin concentration

  5. Long-Term Survival Prediction for Coronary Artery Bypass Grafting: Validation of the ASCERT Model Compared With The Society of Thoracic Surgeons Predicted Risk of Mortality.

    Science.gov (United States)

    Lancaster, Timothy S; Schill, Matthew R; Greenberg, Jason W; Ruaengsri, Chawannuch; Schuessler, Richard B; Lawton, Jennifer S; Maniar, Hersh S; Pasque, Michael K; Moon, Marc R; Damiano, Ralph J; Melby, Spencer J

    2018-05-01

    The recently developed American College of Cardiology Foundation-Society of Thoracic Surgeons (STS) Collaboration on the Comparative Effectiveness of Revascularization Strategy (ASCERT) Long-Term Survival Probability Calculator is a valuable addition to existing short-term risk-prediction tools for cardiac surgical procedures but has yet to be externally validated. Institutional data of 654 patients aged 65 years or older undergoing isolated coronary artery bypass grafting between 2005 and 2010 were reviewed. Predicted survival probabilities were calculated using the ASCERT model. Survival data were collected using the Social Security Death Index and institutional medical records. Model calibration and discrimination were assessed for the overall sample and for risk-stratified subgroups based on (1) ASCERT 7-year survival probability and (2) the predicted risk of mortality (PROM) from the STS Short-Term Risk Calculator. Logistic regression analysis was performed to evaluate additional perioperative variables contributing to death. Overall survival was 92.1% (569 of 597) at 1 year and 50.5% (164 of 325) at 7 years. Calibration assessment found no significant differences between predicted and actual survival curves for the overall sample or for the risk-stratified subgroups, whether stratified by predicted 7-year survival or by PROM. Discriminative performance was comparable between the ASCERT and PROM models for 7-year survival prediction (p validated for prediction of long-term survival after coronary artery bypass grafting in all risk groups. The widely used STS PROM performed comparably as a predictor of long-term survival. Both tools provide important information for preoperative decision making and patient counseling about potential outcomes after coronary artery bypass grafting. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  6. Neighbourhood Characteristics and Long-Term Air Pollution Levels Modify the Association between the Short-Term Nitrogen Dioxide Concentrations and All-Cause Mortality in Paris.

    Science.gov (United States)

    Deguen, Séverine; Petit, Claire; Delbarre, Angélique; Kihal, Wahida; Padilla, Cindy; Benmarhnia, Tarik; Lapostolle, Annabelle; Chauvin, Pierre; Zmirou-Navier, Denis

    2015-01-01

    While a great number of papers have been published on the short-term effects of air pollution on mortality, few have tried to assess whether this association varies according to the neighbourhood socioeconomic level and long-term ambient air concentrations measured at the place of residence. We explored the effect modification of 1) socioeconomic status, 2) long-term NO2 ambient air concentrations, and 3) both combined, on the association between short-term exposure to NO2 and all-cause mortality in Paris (France). A time-stratified case-crossover analysis was performed to evaluate the effect of short-term NO2 variations on mortality, based on 79,107 deaths having occurred among subjects aged over 35 years, from 2004 to 2009, in the city of Paris. Simple and double interactions were statistically tested in order to analyse effect modification by neighbourhood characteristics on the association between mortality and short-term NO2 exposure. The data was estimated at the census block scale (n=866). The mean of the NO2 concentrations during the five days prior to deaths were associated with an increased risk of all-cause mortality: overall Excess Risk (ER) was 0.94% (95%CI=[0.08;1.80]. A higher risk was revealed for subjects living in the most deprived census blocks in comparison with higher socioeconomic level areas (ER=3.14% (95%CI=[1.41-4.90], ppollution episodes. There is also an indication that people living in these disadvantaged census blocks might experience even higher risk following short-term air pollution episodes, when they are also chronically exposed to higher NO2 levels.

  7. Iron Deficiency and Anemia Predict Mortality in Patients with Tuberculosis123

    Science.gov (United States)

    Isanaka, Sheila; Mugusi, Ferdinand; Urassa, Willy; Willett, Walter C.; Bosch, Ronald J.; Villamor, Eduardo; Spiegelman, Donna; Duggan, Christopher; Fawzi, Wafaie W.

    2012-01-01

    Many studies have documented a high prevalence of anemia among tuberculosis (TB) patients and anemia at TB diagnosis has been associated with an increased risk of death. However, little is known about the factors contributing to the development of TB-associated anemia and their importance in TB disease progression. Data from a randomized clinical trial of micronutrient supplementation in patients with pulmonary TB in Tanzania were analyzed. Repeated measures of anemia with iron deficiency, anemia without iron deficiency, and iron deficiency without anemia were assessed as risk factors for treatment failure, TB recurrence, and mortality. The prevalence of anemia (hemoglobin iron deficiency (mean corpuscular volume , 80 fL). We found no evidence of an association between anemia (with or without iron deficiency) or iron deficiency without anemia at baseline and the risk of treatment failure at 1 mo after initiation. Anemia without iron deficiency was associated with an independent, 4-fold increased risk of TB recurrence [adjusted RR = 4.10 (95% CI = 1.88, 8.91); P Iron deficiency and anemia (with and without iron deficiency) were associated with a 2- to nearly 3-fold independent increase in the risk of death [adjusted RR for iron deficiency without anemia = 2.89 (95% CI = 1.53, 5.47); P = 0.001; anemia without iron deficiency = 2.72 (95% CI = 1.50, 4.93); P = 0.001; iron deficiency anemia = 2.13 (95% CI = 1.10, 4.11); P = 0.02]. Efforts to identify and address the conditions contributing to TB-associated anemia, including iron deficiency, could play an important role in reducing morbidity and mortality in areas heavily affected by TB. PMID:22190024

  8. Physical activity assessed in routine care predicts mortality after a COPD hospitalisation

    Directory of Open Access Journals (Sweden)

    Marilyn L. Moy

    2016-03-01

    Full Text Available The independent relationship between physical inactivity and risk of death after an index chronic obstructive pulmonary disease (COPD hospitalisation is unknown. We conducted a retrospective cohort study in a large integrated healthcare system. Patients were included if they were hospitalised for COPD between January 1, 2011 and December 31, 2011. All-cause mortality in the 12 months after discharge was the primary outcome. Physical activity, expressed as self-reported minutes of moderate to vigorous physical activity (MVPA, was routinely assessed at outpatient visits prior to hospitalisation. 1727 (73% patients were inactive (0 min of MVPA per week, 412 (17% were insufficiently active (1–149 min of MVPA per week and 231 (10% were active (≥150 min of MVPA per week. Adjusted Cox regression models assessed risk of death across the MVPA categories. Among 2370 patients (55% females and mean age 73±11 years, there were 464 (20% deaths. Patients who were insufficiently active or active had a 28% (adjusted HR 0.72 (95% CI 0.54–0.97, p=0.03 and 47% (adjusted HR 0.53 (95% CI 0.34–0.84, p<0.01 lower risk of death, respectively, in the 12 months following an index COPD hospitalisation compared to inactive patients. Any level of MVPA is associated with lower risk of all-cause mortality after a COPD hospitalisation. Routine assessment of physical activity in clinical care would identify persons at high risk for dying after COPD hospitalisation.

  9. Hematoma shape, hematoma size, Glasgow coma scale score and ICH score: which predicts the 30-day mortality better for intracerebral hematoma?

    Directory of Open Access Journals (Sweden)

    Chih-Wei Wang

    Full Text Available To investigate the performance of hematoma shape, hematoma size, Glasgow coma scale (GCS score, and intracerebral hematoma (ICH score in predicting the 30-day mortality for ICH patients. To examine the influence of the estimation error of hematoma size on the prediction of 30-day mortality.This retrospective study, approved by a local institutional review board with written informed consent waived, recruited 106 patients diagnosed as ICH by non-enhanced computed tomography study. The hemorrhagic shape, hematoma size measured by computer-assisted volumetric analysis (CAVA and estimated by ABC/2 formula, ICH score and GCS score was examined. The predicting performance of 30-day mortality of the aforementioned variables was evaluated. Statistical analysis was performed using Kolmogorov-Smirnov tests, paired t test, nonparametric test, linear regression analysis, and binary logistic regression. The receiver operating characteristics curves were plotted and areas under curve (AUC were calculated for 30-day mortality. A P value less than 0.05 was considered as statistically significant.The overall 30-day mortality rate was 15.1% of ICH patients. The hematoma shape, hematoma size, ICH score, and GCS score all significantly predict the 30-day mortality for ICH patients, with an AUC of 0.692 (P = 0.0018, 0.715 (P = 0.0008 (by ABC/2 to 0.738 (P = 0.0002 (by CAVA, 0.877 (P<0.0001 (by ABC/2 to 0.882 (P<0.0001 (by CAVA, and 0.912 (P<0.0001, respectively.Our study shows that hematoma shape, hematoma size, ICH scores and GCS score all significantly predict the 30-day mortality in an increasing order of AUC. The effect of overestimation of hematoma size by ABC/2 formula in predicting the 30-day mortality could be remedied by using ICH score.

  10. Hematoma Shape, Hematoma Size, Glasgow Coma Scale Score and ICH Score: Which Predicts the 30-Day Mortality Better for Intracerebral Hematoma?

    Science.gov (United States)

    Wang, Chih-Wei; Liu, Yi-Jui; Lee, Yi-Hsiung; Hueng, Dueng-Yuan; Fan, Hueng-Chuen; Yang, Fu-Chi; Hsueh, Chun-Jen; Kao, Hung-Wen; Juan, Chun-Jung; Hsu, Hsian-He

    2014-01-01

    Purpose To investigate the performance of hematoma shape, hematoma size, Glasgow coma scale (GCS) score, and intracerebral hematoma (ICH) score in predicting the 30-day mortality for ICH patients. To examine the influence of the estimation error of hematoma size on the prediction of 30-day mortality. Materials and Methods This retrospective study, approved by a local institutional review board with written informed consent waived, recruited 106 patients diagnosed as ICH by non-enhanced computed tomography study. The hemorrhagic shape, hematoma size measured by computer-assisted volumetric analysis (CAVA) and estimated by ABC/2 formula, ICH score and GCS score was examined. The predicting performance of 30-day mortality of the aforementioned variables was evaluated. Statistical analysis was performed using Kolmogorov-Smirnov tests, paired t test, nonparametric test, linear regression analysis, and binary logistic regression. The receiver operating characteristics curves were plotted and areas under curve (AUC) were calculated for 30-day mortality. A P value less than 0.05 was considered as statistically significant. Results The overall 30-day mortality rate was 15.1% of ICH patients. The hematoma shape, hematoma size, ICH score, and GCS score all significantly predict the 30-day mortality for ICH patients, with an AUC of 0.692 (P = 0.0018), 0.715 (P = 0.0008) (by ABC/2) to 0.738 (P = 0.0002) (by CAVA), 0.877 (Phematoma shape, hematoma size, ICH scores and GCS score all significantly predict the 30-day mortality in an increasing order of AUC. The effect of overestimation of hematoma size by ABC/2 formula in predicting the 30-day mortality could be remedied by using ICH score. PMID:25029592

  11. Predicting redox-sensitive contaminant concentrations in groundwater using random forest classification

    Science.gov (United States)

    Tesoriero, Anthony J.; Gronberg, Jo Ann; Juckem, Paul F.; Miller, Matthew P.; Austin, Brian P.

    2017-08-01

    Machine learning techniques were applied to a large (n > 10,000) compliance monitoring database to predict the occurrence of several redox-active constituents in groundwater across a large watershed. Specifically, random forest classification was used to determine the probabilities of detecting elevated concentrations of nitrate, iron, and arsenic in the Fox, Wolf, Peshtigo, and surrounding watersheds in northeastern Wisconsin. Random forest classification is well suited to describe the nonlinear relationships observed among several explanatory variables and the predicted probabilities of elevated concentrations of nitrate, iron, and arsenic. Maps of the probability of elevated nitrate, iron, and arsenic can be used to assess groundwater vulnerability and the vulnerability of streams to contaminants derived from groundwater. Processes responsible for elevated concentrations are elucidated using partial dependence plots. For example, an increase in the probability of elevated iron and arsenic occurred when well depths coincided with the glacial/bedrock interface, suggesting a bedrock source for these constituents. Furthermore, groundwater in contact with Ordovician bedrock has a higher likelihood of elevated iron concentrations, which supports the hypothesis that groundwater liberates iron from a sulfide-bearing secondary cement horizon of Ordovician age. Application of machine learning techniques to existing compliance monitoring data offers an opportunity to broadly assess aquifer and stream vulnerability at regional and national scales and to better understand geochemical processes responsible for observed conditions.

  12. Outcome prediction value of determination of cord blood ADM concentrations in neonates with perinatal asphyxia events

    International Nuclear Information System (INIS)

    Zhang Shifa; Zhou Mingxiong; Zhang Xinlu

    2006-01-01

    Objective: To investigate the clinical value of determination of cord blood adrenomedullin (ADM) concentration for predicting development of hypoxic ischemic encephalopathy (HIE) in neonates suffered from perinatal asphyxia. Methods: Cord blood plasma ADM concentrations were measured with RIA in 77 full-ferm neonates with perinatal asphyxia and 30 controls. Results: In the 77 neonates with perinatal asphyxia, 32 developed clinical evidence of HIE within 7 days after birth (HIE group) and 45 didn't (non-HIE group). Cord blood plasma ADM concentrations in the HIE group (160.30 ± 41.3pg/ml) were significantly higher than those in the non-HIE group (112.26 ± 22.90 pg/ml) and controls (102.90 ± 19.43pg/ml). The cord blood plasma ADH concentrations in HIE group were also significantly positively correlated with the severity of the disease (r s = 0. 752, P < 0. 01 ). From our data, taking 117.93pg/ml as cut-off value for diagnosis of HIE would result in a sensitivity of 90.63%, specificity of 80%, and accuracy of 84.42%. Conclusion: High level of ADM in cord blood of neonates with perinatal asphyxia (≥117.93pg/ml) would predict development of HIE with a reasonable accuracy. (authors)

  13. Numerical predictions of the separation of heavy components inside the trace gas concentrator

    International Nuclear Information System (INIS)

    Mo, J.D.

    1995-01-01

    The component with a heavier molecular weight can be separated from the one with a lighter molecular weight in a binary mixture by applying an appropriate pressure gradient. A centrifugal force field effectively generates the required pressure gradient and a favorable flow field along the radial direction in a trace gas concentrator for such an application. This paper presents the numerical predictions of the mass separation inside a trace gas concentrator, which enriches Xenon in air. A Navier-Stokes solver in primitive variables using a pressure based algorithm has been applied to solve for the flow fields. Subsequently, the transport equations with a strong centrifugal field are solved for the mass concentration. This study is the continued effort for the proof-of-concept of centrifugal separation of components with a considerable difference in their molecular weight in a binary mixture. The significant effects of rotational speed, flow field, and the geometrical configuration on the mass separation are presented in this paper

  14. Analysis and Prediction of Energy Production in Concentrating Photovoltaic (CPV Installations

    Directory of Open Access Journals (Sweden)

    Allen Barnett

    2012-03-01

    Full Text Available A method for the prediction of Energy Production (EP in Concentrating Photovoltaic (CPV installations is examined in this study. It presents a new method that predicts EP by using Global Horizontal Irradiation (GHI and the Photovoltaic Geographical Information System (PVGIS database, instead of Direct Normal Irradiation (DNI data, which are rarely recorded at most locations. EP at four Spanish CPV installations is analyzed: two are based on silicon solar cells and the other two on multi-junction III-V solar cells. The real EP is compared with the predicted EP. Two methods for EP prediction are presented. In the first preliminary method, a monthly Performance Ratio (PR is used as an arbitrary constant value (75% and an estimation of the DNI. The DNI estimation is obtained from GHI measurements and the PVGIS database. In the second method, a lineal model is proposed for the first time in this paper to obtain the predicted EP from the estimated DNI. This lineal model is the regression line that correlates the real monthly EP and the estimated DNI in 2009. This new method implies that the monthly PR is variable. Using the new method, the difference between the predicted and the real EP values is less than 2% for the annual EP and is in the range of 5.6%–16.1% for the monthly EP. The method that uses the variable monthly PR allows the prediction of the EP with reasonable accuracy. It is therefore possible to predict the CPV EP for any location, using only widely available GHI data and the PVGIS database.

  15. Decadal Recruitment and Mortality of Ponderosa pine Predicted for the 21st Century Under five Downscaled Climate Change Scenarios

    Science.gov (United States)

    Ironside, K. E.; Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Shaw, J. D.; Cobb, N. S.

    2008-12-01

    Ponderosa pine (Pinus ponderosa var. scopulorum) is the dominant conifer in higher elevation regions of the southwestern United States. Because this species is so prominent, southwestern montane ecosystems will be significantly altered if this species is strongly affected by future climate changes. These changes could be highly challenging for land management agencies. In order to model the consequences of future climates, 20th Century recruitment events and mortality for ponderosa pine were characterized using measures of seasonal water balance (precipitation - potential evapotranspiration). These relationships, assuming they will remain unchanged, were then used to predict 21st Century changes in ponderosa pine occurrence in the southwest. Twenty-one AR4 IPCC General Circulation Model (GCM) A1B simulation results were ranked on their ability to simulate the later 20th Century (1950-2000 AD) precipitation seasonality, spatial patterns, and quantity in the western United States. Among the top ranked GCMs, five were selected for downscaling to a 4 km grid that represented a range in predictions in terms of changes in water balance. Predicted decadal changes in southwestern ponderosa pine for the 21st Century for these five climate change scenarios were calculated using a multiple quadratic logistic regression model. Similar models of other western tree species (Pinus edulis, Yucca brevifolia) predicted severe contractions, especially in the southern half of their ranges. However, the results for Ponderosa pine suggested future expansions throughout its range to both higher and lower elevations, as well as very significant expansions northward.

  16. Spontaneous intracerebral hemorrhage: Clinical and computed tomography findings in predicting in-hospital mortality in Central Africans

    Directory of Open Access Journals (Sweden)

    Michel Lelo Tshikwela

    2012-01-01

    Full Text Available Background and Purpose: Intracerebral hemorrhage (ICH constitutes now 52% of all strokes. Despite of its deadly pattern, locally there is no clinical grading scale for ICH-related mortality prediction. The first objective of this study was to develop a risk stratification scale (Kinshasa ICH score by assessing the strength of independent predictors and their association with in-hospital 30-day mortality. The second objective of the study was to create a specific local and African model for ICH prognosis. Materials and Methods: Age, sex, hypertension, type 2 diabetes mellitus (T2DM, smoking, alcohol intake, and neuroimaging data from CT scan (ICH volume, Midline shift of patients admitted with primary ICH and follow-upped in 33 hospitals of Kinshasa, DR Congo, from 2005 to 2008, were analyzed using logistic regression models. Results: A total of 185 adults and known hypertensive patients (140 men and 45 women were examined. 30-day mortality rate was 35% (n=65. ICH volume>25 mL (OR=8 95% CI: 3.1-20.2; P 7 mm, a consequence of ICH volume, was also a significant predictor of mortality. The Kinshasa ICH score was the sum of individual points assigned as follows: Presence of coma coded 2 (2 × 2 = 4, absence of coma coded 1 (1 × 2 = 2, ICH volume>25 mL coded 2 (2 × 2=4, ICH volume of ≤25 mL coded 1(1 × 2=2, left hemispheric site of ICH coded 2 (2 × 1=2, and right hemispheric site of hemorrhage coded 1(1 × 1 = 1. All patients with Kinshasa ICH score ≤7 survived and the patients with a score >7 died. In considering sex influence (Model 3, points were allowed as follows: Presence of coma (2 × 3 = 6, absence of coma (1 × 3 = 3, men (2 × 2 = 4, women (1 × 2 = 2, midline shift ≤7 mm (1 × 3 = 3, and midline shift >7 mm (2 × 3 = 6. Patients who died had the Kinshasa ICH score ≥16. Conclusion: In this study, the Kinshasa ICH score seems to be an accurate method for distinguishing those ICH patients who need continuous and special management

  17. Preoperative Metabolic Syndrome Is Predictive of Significant Gastric Cancer Mortality after Gastrectomy: The Fujian Prospective Investigation of Cancer (FIESTA Study

    Directory of Open Access Journals (Sweden)

    Dan Hu

    2017-02-01

    Full Text Available Metabolic syndrome (MetS has been shown to be associated with an increased risk of gastric cancer. However, the impact of MetS on gastric cancer mortality remains largely unknown. Here, we prospectively examined the prediction of preoperative MetS for gastric cancer mortality by analyzing a subset of data from the ongoing Fujian prospective investigation of cancer (FIESTA study. This study was conducted among 3012 patients with gastric cancer who received radical gastrectomy between 2000 and 2010. The latest follow-up was completed in 2015. Blood/tissue specimens, demographic and clinicopathologic characteristics were collected at baseline. During 15-year follow-up, 1331 of 3012 patients died of gastric cancer. The median survival time (MST of patients with MetS was 31.3 months, which was significantly shorter than that of MetS-free patients (157.1 months. The coexistence of MetS before surgery was associated with a 2.3-fold increased risk for gastric cancer mortality (P < 0.001. The multivariate-adjusted hazard ratios (HRs were increased with invasion depth T1/T2 (HR = 2.78, P < 0.001, regional lymph node metastasis N0 (HR = 2.65, P < 0.001, positive distant metastasis (HR = 2.53, P < 0.001, TNM stage I/II (HR = 3.00, P < 0.001, intestinal type (HR = 2.96, P < 0.001, negative tumor embolus (HR = 2.34, P < 0.001, and tumor size ≤4.5 cm (HR = 2.49, P < 0.001. Further survival tree analysis confirmed the top splitting role of TNM stage, followed by MetS or hyperglycemia with remarkable discrimination ability. In this large cohort study, preoperative MetS, especially hyperglycemia, was predictive of significant gastric cancer mortality in patients with radical gastrectomy, especially for early stage of gastric cancer.

  18. Serum YKL-40 predicts long-term mortality in patients with stable coronary disease

    DEFF Research Database (Denmark)

    Harutyunyan, Marina; Gøtze, Jens P; Winkel, Per

    2013-01-01

    We investigated whether the inflammatory biomarker YKL-40 could improve the long-term prediction of death made by common risk factors plus high-sensitivity C-reactive protein (hs-CRP) and N-terminal-pro-B natriuretic peptide (NT-proBNP) in patients with stable coronary artery disease (CAD)....

  19. Admission body temperature predicts long-term mortality after acute stroke

    DEFF Research Database (Denmark)

    Kammersgaard, L P; Jørgensen, H S; Rungby, Jørgen

    2002-01-01

    Body temperature is considered crucial in the management of acute stroke patients. Recently hypothermia applied as a therapy for stroke has been demonstrated to be feasible and safe in acute stroke patients. In the present study, we investigated the predictive role of admission body temperature...

  20. Study on the Relationship between Manganese Concentrations in Rural Drinking Water and Incidence and Mortality Caused by Cancer in Huai’an City

    Directory of Open Access Journals (Sweden)

    Qin Zhang

    2014-01-01

    Full Text Available Background. Cancer is a significant disease burden in the world. Many studies showed that heavy metals or their compounds had connection with cancer. But the data conflicting about the relationship of manganese (Mn to cancer are not enough. In this paper, the relationship was discussed between Mn concentrations in drinking water for rural residents and incidence and mortality caused by malignant tumors in Huai’an city. Methods. A total of 158 water samples from 28 villages of 14 towns were, respectively, collected during periods of high flow and low flow in 3 counties of Huai’an city, along Chinese Huai’he River. The samples of deep groundwater, shallow groundwater, and surface water were simultaneously collected in all selected villages. Mn concentrations in all water samples were determined by inductively coupled plasma-mass spectrometry (ICP-MS 7500a. The correlation analysis was used to study the relationship between the Mn concentration and cancer incidence and mortality. Results. Mn concentrations detectable rate was 100% in all water samples. The mean concentration was 452.32 μg/L ± 507.76 μg/L. There was significant difference between the high flow period and low flow period (t=-5.23, P<0.05 and also among deep groundwater, shallow groundwater, and surface water (F=5.02, P<0.05. The ratio of superscale of Mn was 75.32%. There was significant difference of Mn level between samples in the high flow period and low flow period (χ2=45.62,  P<0.05 and also among deep groundwater, shallow groundwater, and surface water (χ2=10.66, P<0.05. And also we found that, during the low flow period, Mn concentration has positive correlation with cancer incidence and mortality; for a 1 μg/L increase in Mn concentration, there was a corresponding increase of 0.45/100000 new cancer cases and 0.35/100000 cancer deaths (P<0.05. Conclusions. In Huai’an city, the mean concentration of Mn in drinking water was very high. Mn concentration

  1. Mortality Risk After Transcatheter Aortic Valve Implantation: Analysis of the Predictive Accuracy of the Transcatheter Valve Therapy Registry Risk Assessment Model.

    Science.gov (United States)

    Codner, Pablo; Malick, Waqas; Kouz, Remi; Patel, Amisha; Chen, Cheng-Han; Terre, Juan; Landes, Uri; Vahl, Torsten Peter; George, Isaac; Nazif, Tamim; Kirtane, Ajay J; Khalique, Omar K; Hahn, Rebecca T; Leon, Martin B; Kodali, Susheel

    2018-05-08

    Risk assessment tools currently used to predict mortality in transcatheter aortic valve implantation (TAVI) were designed for patients undergoing cardiac surgery. We aim to assess the accuracy of the TAVI dedicated American College of Cardiology / Transcatheter Valve Therapies (ACC/TVT) risk score in predicting mortality outcomes. Consecutive patients (n=1038) undergoing TAVI at a single institution from 2014 to 2016 were included. The ACC/TVT registry mortality risk score, the Society of Thoracic Surgeons - Patient Reported Outcomes (STS-PROM) score and the EuroSCORE II were calculated for all patients. In hospital and 30-day all-cause mortality rates were 1.3% and 2.9%, respectively. The ACC/TVT risk stratification tool scored higher for patients who died in-hospital than in those who survived the index hospitalization (6.4 ± 4.6 vs. 3.5 ± 1.6, p = 0.03; respectively). The ACC/TVT score showed a high level of discrimination, C-index for in-hospital mortality 0.74, 95% CI [0.59 - 0.88]. There were no significant differences between the performance of the ACC/TVT registry risk score, the EuroSCORE II and the STS-PROM for in hospital and 30-day mortality rates. The ACC/TVT registry risk model is a dedicated tool to aid in the prediction of in-hospital mortality risk after TAVI.

  2. Mortality and One-Year Functional Outcome in Elderly and Very Old Patients with Severe Traumatic Brain Injuries: Observed and Predicted

    Directory of Open Access Journals (Sweden)

    Cecilie Røe

    2015-01-01

    Full Text Available The aim of the present study was to evaluate mortality and functional outcome in old and very old patients with severe traumatic brain injury (TBI and compare to the predicted outcome according to the internet based CRASH (Corticosteroid Randomization After Significant Head injury model based prediction, from the Medical Research Council (MRC. Methods. Prospective, national multicenter study including patients with severe TBI ≥65 years. Predicted mortality and outcome were calculated based on clinical information (CRASH basic (age, GCS score, and pupil reactivity to light, as well as with additional CT findings (CRASH CT. Observed 14-day mortality and favorable/unfavorable outcome according to the Glasgow Outcome Scale at one year was compared to the predicted outcome according to the CRASH models. Results. 97 patients, mean age 75 (SD 7 years, 64% men, were included. Two patients were lost to follow-up; 48 died within 14 days. The predicted versus the observed odds ratio (OR for mortality was 2.65. Unfavorable outcome (GOSE < 5 was observed at one year follow-up in 72% of patients. The CRASH models predicted unfavorable outcome in all patients. Conclusion. The CRASH model overestimated mortality and unfavorable outcome in old and very old Norwegian patients with severe TBI.

  3. Mortality and One-Year Functional Outcome in Elderly and Very Old Patients with Severe Traumatic Brain Injuries: Observed and Predicted

    Science.gov (United States)

    Røe, Cecilie; Skandsen, Toril; Manskow, Unn; Ader, Tiina; Anke, Audny

    2015-01-01

    The aim of the present study was to evaluate mortality and functional outcome in old and very old patients with severe traumatic brain injury (TBI) and compare to the predicted outcome according to the internet based CRASH (Corticosteroid Randomization After Significant Head injury) model based prediction, from the Medical Research Council (MRC). Methods. Prospective, national multicenter study including patients with severe TBI ≥65 years. Predicted mortality and outcome were calculated based on clinical information (CRASH basic) (age, GCS score, and pupil reactivity to light), as well as with additional CT findings (CRASH CT). Observed 14-day mortality and favorable/unfavorable outcome according to the Glasgow Outcome Scale at one year was compared to the predicted outcome according to the CRASH models. Results. 97 patients, mean age 75 (SD 7) years, 64% men, were included. Two patients were lost to follow-up; 48 died within 14 days. The predicted versus the observed odds ratio (OR) for mortality was 2.65. Unfavorable outcome (GOSE < 5) was observed at one year follow-up in 72% of patients. The CRASH models predicted unfavorable outcome in all patients. Conclusion. The CRASH model overestimated mortality and unfavorable outcome in old and very old Norwegian patients with severe TBI. PMID:26688614

  4. Prediction of Mortality after Emergent Transjugular Intrahepatic Portosystemic Shunt Placement: Use of APACHE II, Child-Pugh and MELD Scores in Asian Patients with Refractory Variceal Hemorrhage

    International Nuclear Information System (INIS)

    Tzeng, Wen Sheng; Wu, Reng Hong; Lin, Ching Yih; Chen, Jyh Jou; Sheu, Ming Juen; Koay, Lok Beng; Lee, Chuan

    2009-01-01

    This study was designed to determine if existing methods of grading liver function that have been developed in non-Asian patients with cirrhosis can be used to predict mortality in Asian patients treated for refractory variceal hemorrhage by the use of the transjugular intrahepatic portosystemic shunt (TIPS) procedure. Data for 107 consecutive patients who underwent an emergency TIPS procedure were retrospectively analyzed. Acute physiology and chronic health evaluation (APACHE II), Child-Pugh and model for end-stage liver disease (MELD) scores were calculated. Survival analyses were performed to evaluate the ability of the various models to predict 30-day, 60-day and 360-day mortality. The ability of stratified APACHE II, Child-Pugh, and MELD scores to predict survival was assessed by the use of Kaplan-Meier analysis with the log-rank test. No patient died during the TIPS procedure, but 82 patients died during the follow-up period. Thirty patients died within 30 days after the TIPS procedure; 37 patients died within 60 days and 53 patients died within 360 days. Univariate analysis indicated that hepatorenal syndrome, use of inotropic agents and mechanical ventilation were associated with elevated 30-day mortality (p 11 or an MELD score > 20 predicted increased risk of death at 30, 60 and 360 days (p 11 or an MELD score > 20 are predictive of mortality in Asian patients with refractory variceal hemorrhage treated with the TIPS procedure. An APACHE II score is not predictive of early mortality in this patient population

  5. [Application of predictive model to estimate concentrations of chemical substances in the work environment].

    Science.gov (United States)

    Kupczewska-Dobecka, Małgorzata; Czerczak, Sławomir; Jakubowski, Marek; Maciaszek, Piotr; Janasik, Beata

    2010-01-01

    Based on the Estimation and Assessment of Substance Exposure (EASE) predictive model implemented into the European Union System for the Evaluation of Substances (EUSES 2.1.), the exposure to three chosen organic solvents: toluene, ethyl acetate and acetone was estimated and compared with the results of measurements in workplaces. Prior to validation, the EASE model was pretested using three exposure scenarios. The scenarios differed in the decision tree of pattern of use. Five substances were chosen for the test: 1,4-dioxane tert-methyl-butyl ether, diethylamine, 1,1,1-trichloroethane and bisphenol A. After testing the EASE model, the next step was the validation by estimating the exposure level and comparing it with the results of measurements in the workplace. We used the results of measurements of toluene, ethyl acetate and acetone concentrations in the work environment of a paint and lacquer factory, a shoe factory and a refinery. Three types of exposure scenarios, adaptable to the description of working conditions were chosen to estimate inhalation exposure. Comparison of calculated exposure to toluene, ethyl acetate and acetone with measurements in workplaces showed that model predictions are comparable with the measurement results. Only for low concentration ranges, the measured concentrations were higher than those predicted. EASE is a clear, consistent system, which can be successfully used as an additional component of inhalation exposure estimation. If the measurement data are available, they should be preferred to values estimated from models. In addition to inhalation exposure estimation, the EASE model makes it possible not only to assess exposure-related risk but also to predict workers' dermal exposure.

  6. Dose response characterization of the association of serum digoxin concentration with mortality outcomes in the Digitalis Investigation Group trial

    NARCIS (Netherlands)

    Adams, Kirkwood F.; Butler, Javed; Patterson, J. Herbert; Stough, Wendy Gattis; Bauman, Jerry L.; van Veldhuisen, Dirk J.; Schwartz, Todd A.; Sabbah, Hani; Mackowiak, John I.; Ventura, Hector O.; Ghali, Jalal K.

    AimsMany patients with heart failure and reduced EF remain at high risk for hospitalization despite evidence-based therapy. Digoxin may decrease hospitalization; however, uncertainty persists concerning its proper administration and effect on mortality. This study investigated whether using dose

  7. Desert Dust Outbreaks in Southern Europe: Contribution to Daily PM10 Concentrations and Short-Term Associations with Mortality and Hospital Admissions

    Science.gov (United States)

    Stafoggia, Massimo; Zauli-Sajani, Stefano; Pey, Jorge; Samoli, Evangelia; Alessandrini, Ester; Basagaña, Xavier; Cernigliaro, Achille; Chiusolo, Monica; Demaria, Moreno; Díaz, Julio; Faustini, Annunziata; Katsouyanni, Klea; Kelessis, Apostolos G.; Linares, Cristina; Marchesi, Stefano; Medina, Sylvia; Pandolfi, Paolo; Pérez, Noemí; Querol, Xavier; Randi, Giorgia; Ranzi, Andrea; Tobias, Aurelio; Forastiere, Francesco

    2015-01-01

    Background: Evidence on the association between short-term exposure to desert dust and health outcomes is controversial. Objectives: We aimed to estimate the short-term effects of particulate matter ≤ 10 μm (PM10) on mortality and hospital admissions in 13 Southern European cities, distinguishing between PM10 originating from the desert and from other sources. Methods: We identified desert dust advection days in multiple Mediterranean areas for 2001–2010 by combining modeling tools, back-trajectories, and satellite data. For each advection day, we estimated PM10 concentrations originating from desert, and computed PM10 from other sources by difference. We fitted city-specific Poisson regression models to estimate the association between PM from different sources (desert and non-desert) and daily mortality and emergency hospitalizations. Finally, we pooled city-specific results in a random-effects meta-analysis. Results: On average, 15% of days were affected by desert dust at ground level (desert PM10 > 0 μg/m3). Most episodes occurred in spring–summer, with increasing gradient of both frequency and intensity north–south and west–east of the Mediterranean basin. We found significant associations of both PM10 concentrations with mortality. Increases of 10 μg/m3 in non-desert and desert PM10 (lag 0–1 days) were associated with increases in natural mortality of 0.55% (95% CI: 0.24, 0.87%) and 0.65% (95% CI: 0.24, 1.06%), respectively. Similar associations were estimated for cardio-respiratory mortality and hospital admissions. Conclusions: PM10 originating from the desert was positively associated with mortality and hospitalizations in Southern Europe. Policy measures should aim at reducing population exposure to anthropogenic airborne particles even in areas with large contribution from desert dust advections. Citation: Stafoggia M, Zauli-Sajani S, Pey J, Samoli E, Alessandrini E, Basagaña X, Cernigliaro A, Chiusolo M, Demaria M, Díaz J, Faustini A

  8. Desert Dust Outbreaks in Southern Europe: Contribution to Daily PM₁₀ Concentrations and Short-Term Associations with Mortality and Hospital Admissions.

    Science.gov (United States)

    Stafoggia, Massimo; Zauli-Sajani, Stefano; Pey, Jorge; Samoli, Evangelia; Alessandrini, Ester; Basagaña, Xavier; Cernigliaro, Achille; Chiusolo, Monica; Demaria, Moreno; Díaz, Julio; Faustini, Annunziata; Katsouyanni, Klea; Kelessis, Apostolos G; Linares, Cristina; Marchesi, Stefano; Medina, Sylvia; Pandolfi, Paolo; Pérez, Noemí; Querol, Xavier; Randi, Giorgia; Ranzi, Andrea; Tobias, Aurelio; Forastiere, Francesco

    2016-04-01

    Evidence on the association between short-term exposure to desert dust and health outcomes is controversial. We aimed to estimate the short-term effects of particulate matter ≤ 10 μm (PM10) on mortality and hospital admissions in 13 Southern European cities, distinguishing between PM10 originating from the desert and from other sources. We identified desert dust advection days in multiple Mediterranean areas for 2001-2010 by combining modeling tools, back-trajectories, and satellite data. For each advection day, we estimated PM10 concentrations originating from desert, and computed PM10 from other sources by difference. We fitted city-specific Poisson regression models to estimate the association between PM from different sources (desert and non-desert) and daily mortality and emergency hospitalizations. Finally, we pooled city-specific results in a random-effects meta-analysis. On average, 15% of days were affected by desert dust at ground level (desert PM10 > 0 μg/m3). Most episodes occurred in spring-summer, with increasing gradient of both frequency and intensity north-south and west-east of the Mediterranean basin. We found significant associations of both PM10 concentrations with mortality. Increases of 10 μg/m3 in non-desert and desert PM10 (lag 0-1 days) were associated with increases in natural mortality of 0.55% (95% CI: 0.24, 0.87%) and 0.65% (95% CI: 0.24, 1.06%), respectively. Similar associations were estimated for cardio-respiratory mortality and hospital admissions. PM10 originating from the desert was positively associated with mortality and hospitalizations in Southern Europe. Policy measures should aim at reducing population exposure to anthropogenic airborne particles even in areas with large contribution from desert dust advections. Stafoggia M, Zauli-Sajani S, Pey J, Samoli E, Alessandrini E, Basagaña X, Cernigliaro A, Chiusolo M, Demaria M, Díaz J, Faustini A, Katsouyanni K, Kelessis AG, Linares C, Marchesi S, Medina S, Pandolfi P, P

  9. The ADOPT-LC score: a novel predictive index of in-hospital mortality of cirrhotic patients following surgical procedures, based on a national survey.

    Science.gov (United States)

    Sato, Masaya; Tateishi, Ryosuke; Yasunaga, Hideo; Horiguchi, Hiromasa; Matsui, Hiroki; Yoshida, Haruhiko; Fushimi, Kiyohide; Koike, Kazuhiko

    2017-03-01

    We aimed to develop a model for predicting in-hospital mortality of cirrhotic patients following major surgical procedures using a large sample of patients derived from a Japanese nationwide administrative database. We enrolled 2197 cirrhotic patients who underwent elective (n = 1973) or emergency (n = 224) surgery. We analyzed the risk factors for postoperative mortality and established a scoring system for predicting postoperative mortality in cirrhotic patients using a split-sample method. In-hospital mortality rates following elective or emergency surgery were 4.7% and 20.5%, respectively. In multivariate analysis, patient age, Child-Pugh (CP) class, Charlson Comorbidity Index (CCI), and duration of anesthesia in elective surgery were significantly associated with in-hospital mortality. In emergency surgery, CP class and duration of anesthesia were significant factors. Based on multivariate analysis in the training set (n = 987), the Adequate Operative Treatment for Liver Cirrhosis (ADOPT-LC) score that used patient age, CP class, CCI, and duration of anesthesia to predict in-hospital mortality following elective surgery was developed. This scoring system was validated in the testing set (n = 986) and produced an area under the curve of 0.881. We also developed iOS/Android apps to calculate ADOPT-LC scores to allow easy access to the current evidence in daily clinical practice. Patient age, CP class, CCI, and duration of anesthesia were identified as important risk factors for predicting postoperative mortality in cirrhotic patients. The ADOPT-LC score effectively predicts in-hospital mortality following elective surgery and may assist decisions regarding surgical procedures in cirrhotic patients based on a quantitative risk assessment. © 2016 The Authors Hepatology Research published by John Wiley & Sons Australia, Ltd on behalf of Japan Society of Hepatology.

  10. Forced vital capacity predicts morbidity and mortality in adults with repaired tetralogy of Fallot.

    Science.gov (United States)

    Cohen, Katie E; Buelow, Matthew W; Dixon, Jennifer; Brazauskas, Ruta; Cohen, Scott B; Earing, Michael G; Ginde, Salil

    2017-07-01

    Abnormal lung function characterized by a reduced forced vital capacity (FVC) is common in adults with repaired tetralogy of Fallot (TOF) and is associated with previous thoracotomies and sternotomies. The impact of abnormal lung function on clinical outcomes in adult patients with repaired TOF is unclear. The aim of this study was to determine the impact of abnormal lung function on the outcome of hospitalization and death in adults with repaired TOF when analyzed with other traditional cardiac risk factors. Retrospective study of adults with repaired TOF, who underwent spirometry between 2000 and 2014. FVC < 60% of predicted was categorized as moderate-to-severely reduced lung function. Primary outcome measure was the combined clinical endpoint of death, cardiac transplantation, or nonelective hospitalization for primary cardiac or respiratory indication. A total of 122 patients were included. Average age at spirometry testing was 31 ± 10.1 years. FVC was < 60% predicted in 23 (19%) patients. During a mean follow-up period of 3.97 ± 2.65 years, 23 (19%) patients reached the combined clinical outcome of nonelective hospitalization and/or death. FVC < 60% predicted was independently associated with the risk for the combined clinical outcome (RR 6.68 (95% CI 2.49-17.94), P < .001). Abnormal pulmonary function characterized by reduced FVC is common in adults with repaired TOF. Patients with FVC < 60% predicted had a 6 times higher rate of hospitalization and/or death compared to those with FVC ≥ 60%. © 2017 Wiley Periodicals, Inc.

  11. Use of Artificial Neural Network Models to Predict Indicator Organism Concentrations in an Urban Watershed

    Science.gov (United States)

    Mas, D. M.; Ahlfeld, D. P.

    2004-05-01

    Forecasting stream water quality is important for numerous aspects of resource protection and management. Fecal coliform and enteroccocus are primary indicator organisms used to assess potential pathogen contamination. Consequently, modeling the occurrence and concentration of fecal coliform and enterococcus is an important tool in watershed management. In addition, analyzing the relationship between model input and predicted indicator organisms is useful for elucidating possible sources of contamination and mechanisms of transport. While many process-based, statistical, and empirical models exist for water quality prediction, artificial neural network (ANN) models are increasingly being used for forecasting of water resources variables because ANNs are often capable of modeling complex systems for which behavioral rules are either unknown or difficult to simulate. The performance of ANNs compared to more established modeling approaches such as multiple linear regression (MLR) remains an importance research question. Data collected the U.S. Geological Survey in the lower Charles River in Massachusetts, USA in 1999-2000 was examined to determine correlation between various water quality constituents and indicator organisms and to explore the relationship between rainfall characteristics and indicator organism concentrations. Using the results of the statistical analysis to guide the selection of explanatory variables, MLR was performed to develop predictive equations for wet weather and dry weather conditions. The results show that the best-performing predictor variables are generally consistent for both indicator organisms considered. In addition, the regression equations show increasing indicator organism concentrations as a function of suspended sediment concentrations and length of time since last precipitation event, suggesting accumulation and wash off as a key mechanism of pathogen transport under wet weather conditions. This research also presents the

  12. Examination of the uncertainty in air concentration predictions using Hanford field data

    International Nuclear Information System (INIS)

    Miller, C.W.; Fields, D.E.; Cotter, S.J.

    1986-10-01

    The accuracy of an environmental transport model is best determined by comparing model predictions with environmental measurements made under conditions similar to those assumed by the model, a process commonly referred to as model validation. Over the past several years, we have done a variety of validation studies with the popular Gaussian plume atmospheric dispersion model using data from tests conducted on the Hanford reservation. Data for short-term releases of small particles for release heights of 2 m, 56 m, and 111 m have been used. Up to six different sets of atmospheric dispersion parameters and three different atmospheric stability class specification schemes have been examined. Overall, dispersion parameters based on measurements made near Juelich, West Germany, give the best comparisons between observed and predicted air concentrations. The commonly-used vertical temperature gradient method for determining atmospheric stability class consistently gives poor results. The accuracy of air concentration predictions improves when dry deposition processes are included in the model. Further validation studies using various Hanford data sets are planned

  13. A contemporary risk model for predicting 30-day mortality following percutaneous coronary intervention in England and Wales.

    Science.gov (United States)

    McAllister, Katherine S L; Ludman, Peter F; Hulme, William; de Belder, Mark A; Stables, Rodney; Chowdhary, Saqib; Mamas, Mamas A; Sperrin, Matthew; Buchan, Iain E

    2016-05-01

    The current risk model for percutaneous coronary intervention (PCI) in the UK is based on outcomes of patients treated in a different era of interventional cardiology. This study aimed to create a new model, based on a contemporary cohort of PCI treated patients, which would: predict 30 day mortality; provide good discrimination; and be well calibrated across a broad risk-spectrum. The model was derived from a training dataset of 336,433 PCI cases carried out between 2007 and 2011 in England and Wales, with 30 day mortality provided by record linkage. Candidate variables were selected on the basis of clinical consensus and data quality. Procedures in 2012 were used to perform temporal validation of the model. The strongest predictors of 30-day mortality were: cardiogenic shock; dialysis; and the indication for PCI and the degree of urgency with which it was performed. The model had an area under the receiver operator characteristic curve of 0.85 on the training data and 0.86 on validation. Calibration plots indicated a good model fit on development which was maintained on validation. We have created a cont