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.

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.

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.

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

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.

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.

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.

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

[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.

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.

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.

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

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.

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 ...

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.

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.

Particulate air pollution and daily mortality in Detroit.

Science.gov (United States)

Schwartz, J

1991-12-01

Particulate air pollution has been associated with increased mortality during episodes of high pollution concentrations. The relationship at lower concentrations has been more controversial, as has the relative role of particles and sulfur dioxide. Replication has been difficult because suspended particle concentrations are usually measured only every sixth day in the U.S. This study used concurrent measurements of total suspended particulates (TSP) and airport visibility from every sixth day sampling for 10 years to fit a predictive model for TSP. Predicted daily TSP concentrations were then correlated with daily mortality counts in Poisson regression models controlling for season, weather, time trends, overdispersion, and serial correlation. A significant correlation (P less than 0.0001) was found between predicted TSP and daily mortality. This correlation was independent of sulfur dioxide, but not vice versa. The magnitude of the effect was very similar to results recently reported from Steubenville, Ohio (using actual TSP measurements), with each 100 micrograms/m3 increase in TSP resulting in a 6% increase in mortality. Graphical analysis indicated a dose-response relationship with no evidence of a threshold down to concentrations below half of the National Ambient Air Quality Standards for particulate matter.

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

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....

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 ...

[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

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

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.

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

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

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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.

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

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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.

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

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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.

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...

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

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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.

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

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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.

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

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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....

Cholecystokinin in plasma predicts cardiovascular mortality in elderly females

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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...

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

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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.

Monitoring of the newborn dog and prediction of neonatal mortality.

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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.

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

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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.

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....

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

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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.

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

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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.

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

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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.

Periodontitis in older Swedish individuals fails to predict mortality.

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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.

Acute aluminium phosphide poisoning: Can we predict mortality?

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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

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

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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

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...

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

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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.

Predicting mortality for five California conifers following wildfire

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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...

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

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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...

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.

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.

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.

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

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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.

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

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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.

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....

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

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

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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.

Cardiac Troponin Elevation Predicts Mortality in Patients Undergoing Orthotopic Liver Transplantation

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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.

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.

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

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...

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

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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

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.

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.

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

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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.

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.

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.

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

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

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

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

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.

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.

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.

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

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.

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...

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 ...

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

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

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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.

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

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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.

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

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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

Lung cancer mortality in European women: trends and predictions.

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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.

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

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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.

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

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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.

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- ...

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...

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

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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.

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

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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.

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

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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%.

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

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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.

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

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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.

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

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

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

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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.

Prothrombin time is predictive of low plasma prothrombin concentration and clinical outcome in patients with trauma hemorrhage: analyses of prospective observational cohort studies.

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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

Flow-covariate prediction of stream pesticide concentrations.

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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.

Reducing mortality risk by targeting specific air pollution sources: Suva, Fiji.

Science.gov (United States)

Isley, C F; Nelson, P F; Taylor, M P; Stelcer, E; Atanacio, A J; Cohen, D D; Mani, F S; Maata, M

2018-01-15

Health implications of air pollution vary dependent upon pollutant sources. This work determines the value, in terms of reduced mortality, of reducing ambient particulate matter (PM 2.5 : effective aerodynamic diameter 2.5μm or less) concentration due to different emission sources. Suva, a Pacific Island city with substantial input from combustion sources, is used as a case-study. Elemental concentration was determined, by ion beam analysis, for PM 2.5 samples from Suva, spanning one year. Sources of PM 2.5 have been quantified by positive matrix factorisation. A review of recent literature has been carried out to delineate the mortality risk associated with these sources. Risk factors have then been applied for Suva, to calculate the possible mortality reduction that may be achieved through reduction in pollutant levels. Higher risk ratios for black carbon and sulphur resulted in mortality predictions for PM 2.5 from fossil fuel combustion, road vehicle emissions and waste burning that surpass predictions for these sources based on health risk of PM 2.5 mass alone. Predicted mortality for Suva from fossil fuel smoke exceeds the national toll from road accidents in Fiji. The greatest benefit for Suva, in terms of reduced mortality, is likely to be accomplished by reducing emissions from fossil fuel combustion (diesel), vehicles and waste burning. Copyright © 2017. Published by Elsevier B.V.

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.

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...

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.

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

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.

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.)

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.)

Nonstructural leaf carbohydrate dynamics of Pinus edulis during drought-induced tree mortality reveal role for carbon metabolism in mortality mechanism.

Science.gov (United States)

Adams, Henry D; Germino, Matthew J; Breshears, David D; Barron-Gafford, Greg A; Guardiola-Claramonte, Maite; Zou, Chris B; Huxman, Travis E

2013-03-01

Vegetation change is expected with global climate change, potentially altering ecosystem function and climate feedbacks. However, causes of plant mortality, which are central to vegetation change, are understudied, and physiological mechanisms remain unclear, particularly the roles of carbon metabolism and xylem function. We report analysis of foliar nonstructural carbohydrates (NSCs) and associated physiology from a previous experiment where earlier drought-induced mortality of Pinus edulis at elevated temperatures was associated with greater cumulative respiration. Here, we predicted faster NSC decline for warmed trees than for ambient-temperature trees. Foliar NSC in droughted trees declined by 30% through mortality and was lower than in watered controls. NSC decline resulted primarily from decreased sugar concentrations. Starch initially declined, and then increased above pre-drought concentrations before mortality. Although temperature did not affect NSC and sugar, starch concentrations ceased declining and increased earlier with higher temperatures. Reduced foliar NSC during lethal drought indicates a carbon metabolism role in mortality mechanism. Although carbohydrates were not completely exhausted at mortality, temperature differences in starch accumulation timing suggest that carbon metabolism changes are associated with time to death. Drought mortality appears to be related to temperature-dependent carbon dynamics concurrent with increasing hydraulic stress in P. edulis and potentially other similar species. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

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.

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....

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...

Plant Water Content is the Best Predictor of Drought-induced Mortality

Science.gov (United States)

Sapes, G.; Roskilly, B.; Dobrowski, S.; Sala, A.

2017-12-01

Predicting drought-induced forest mortality remains extremely challenging. Recent research has shown that both plant hydraulics and stored non-structural carbohydrates (NSC) interact during drought-induced mortality. The strong interaction between these two variables and the fact that they are both difficult to measure render drought-induced plant mortality extremely difficult to monitor and predict. A variable that is easier to measure and that integrates hydraulic transport and carbohydrate dynamics may, therefore, improve our ability to monitor and predict mortality. Here, we tested whether plant water content is such an integrator variable and, therefore, a better predictor of mortality under drought. We subjected 250 two-year-old ponderosa pine seedlings to drought until they died in a greenhouse experiment. Periodically during the dry down, we measured percent loss of hydraulic conductivity (PLC), NSC concentration (starch and soluble sugars), and tissue volumetric water content (VWC) in roots, stems and leaves. At each measurement time, a separate set of seedlings were re-watered to estimate the probability of mortality at the population level. Linear models were used to explore whether PLC and NSC were linked to VWC and to determine which of the three variables predicted mortality the best. As expected, plants lost hydraulic conductivity in stems and roots during the dry down. Starch concentrations also decreased in all organs as the drought proceeded. In contrast, soluble sugars increased in stems and roots, consistent with the conversion of stored NSCs into osmotically active compounds. Models containing both PLC and NSC concentrations as predictors of VWC were highly significant in all organs and at the whole plant level, indicating that water content is influenced by both PLC and NSCs. PLC, NSC, and VWC explained mortality across organs and at the whole plant level, but VWC was the best predictor (R2 = 0.99). Our results indicate that plant water

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.

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.

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....

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.

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.

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

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.

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.

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.

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.

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

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.

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

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.

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

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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

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.

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...

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.

Hematoma Shape, Hematoma Size, Glasgow Coma Scale Score and ICH Score: Which Predicts the 30-Day Mortality Better for Intracerebral Hematoma?

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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

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...

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

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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.

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

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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.

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....

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

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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.

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.

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.

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

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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

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.

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

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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.

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

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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.

Darcy’s law predicts widespread forest mortality under climate warming

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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.

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

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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.

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.

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

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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.

Predictability Analysis of PM10 Concentrations in Budapest

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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.

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)

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

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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

A prediction model for 5-year cardiac mortality in patients with chronic heart failure using {sup 123}I-metaiodobenzylguanidine imaging

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Nakajima, Kenichi; Matsuo, Shinro [Kanazawa University Hospital, Department of Nuclear Medicine, Kanazawa (Japan); Nakata, Tomoaki [Sapporo Medical University School of Medicine, Second Department of Internal Medicine (Cardiology), Sapporo (Japan); Hakodate-Goryoukaku Hospital, Department of Cardiology, Hakodate (Japan); Yamada, Takahisa [Osaka Prefectural General Medical Center, Department of Cardiology, Osaka (Japan); Yamashina, Shohei [Toho University Omori Medical Center, Department of Cardiovascular Medicine, Tokyo (Japan); Momose, Mitsuru [Tokyo Women' s Medical University, Department of Nuclear Medicine, Tokyo (Japan); Kasama, Shu [Cardiovascular Hospital of Central Japan, Department of Cardiology, Shibukawa (Japan); Matsui, Toshiki [Social Insurance Shiga General Hospital, Department of Cardiology, Otsu (Japan); Travin, Mark I. [Albert Einstein Medical College, Department of Cardiology and Nuclear Medicine, Montefiore Medical Center, Bronx, NY (United States); Jacobson, Arnold F. [GE Healthcare, Medical Diagnostics, Princeton, NJ (United States)

2014-09-15

Prediction of mortality risk is important in the management of chronic heart failure (CHF). The aim of this study was to create a prediction model for 5-year cardiac death including assessment of cardiac sympathetic innervation using data from a multicenter cohort study in Japan. The original pooled database consisted of cohort studies from six sites in Japan. A total of 933 CHF patients who underwent {sup 123}I-metaiodobenzylguanidine (MIBG) imaging and whose 5-year outcomes were known were selected from this database. The late MIBG heart-to-mediastinum ratio (HMR) was used for quantification of cardiac uptake. Cox proportional hazard and logistic regression analyses were used to select appropriate variables for predicting 5-year cardiac mortality. The formula for predicting 5-year mortality was created using a logistic regression model. During the 5-year follow-up, 205 patients (22 %) died of a cardiac event including heart failure death, sudden cardiac death and fatal acute myocardial infarction (64 %, 30 % and 6 %, respectively). Multivariate logistic analysis selected four parameters, including New York Heart Association (NYHA) functional class, age, gender and left ventricular ejection fraction, without HMR (model 1) and five parameters with the addition of HMR (model 2). The net reclassification improvement analysis for all subjects was 13.8 % (p < 0.0001) by including HMR and its inclusion was most effective in the downward reclassification of low-risk patients. Nomograms for predicting 5-year cardiac mortality were created from the five-parameter regression model. Cardiac MIBG imaging had a significant additive value for predicting cardiac mortality. The prediction formula and nomograms can be used for risk stratifying in patients with CHF. (orig.)

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

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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.

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

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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.

Application of XGBoost algorithm in hourly PM2.5 concentration prediction

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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.

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

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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

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

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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

Osteoprotegerin and mortality in type 2 diabetic patients

DEFF Research Database (Denmark)

Reinhard, Henrik; Lajer, Maria Stenkil; Gall, Mari-Anne

2010-01-01

aimed to investigate the prognostic value of OPG in relation to all-cause and cardiovascular mortality in a cohort of type 2 diabetic patients. RESEARCH DESIGN AND METHODS In a prospective observational follow-up study, 283 type 2 diabetic patients (172 men; aged 53.9 ± 8.8 years) were followed...... predictor of all-cause mortality in type 2 diabetic patients. The effect of OPG on all-cause mortality was independent of conventional cardiovascular risk factors, UAER, and NT-proBNP levels....... for a median of 16.8 years (range 0.2-23.0). Baseline plasma OPG concentrations were determined by immunoassay. RESULTS During follow-up, 193 (68%) patients died. High versus low levels of OPG predicted all-cause mortality (covariate-adjusted for urinary albumin excretion rate [UAER], estimated glomerular...

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

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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. 

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

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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.

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

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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

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

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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.

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

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)

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

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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.

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

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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.

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

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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.

Index to Predict In-hospital Mortality in Older Adults after Non-traumatic Emergency Department Intubations

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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.

A Risk Prediction Score for Kidney Failure or Mortality in Rhabdomyolysis

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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

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...

Sex/gender and socioeconomic differences in the predictive ability of self-rated health for mortality.

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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

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

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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.

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.)

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...

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.

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.

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.

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

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

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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.

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

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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

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.

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.)

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.

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.

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.

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.

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.

Levels of and changes in life satisfaction predict mortality hazards: Disentangling the role of physical health, perceived control, and social orientation.

Science.gov (United States)

Hülür, Gizem; Heckhausen, Jutta; Hoppmann, Christiane A; Infurna, Frank J; Wagner, Gert G; Ram, Nilam; Gerstorf, Denis

2017-09-01

It is well documented that well-being typically evinces precipitous decrements at the end of life. However, research has primarily taken a postdictive approach by knowing the outcome (date of death) and aligning, in retrospect, how well-being has changed for people with documented death events. In the present study, we made use of a predictive approach by examining whether and how levels of and changes in life satisfaction prospectively predict mortality hazards and delineate the role of contributing factors, including health, perceived control, and social orientation. To do so, we applied shared parameter growth-survival models to 20-year longitudinal data from 10,597 participants (n = 1,560 [15%] deceased; age at baseline: M = 44 years, SD = 17, range = 18-98 years) from the national German Socio-Economic Panel Study. Our findings showed that lower levels and steeper declines of life satisfaction each uniquely predicted higher mortality risks. Results also revealed moderating effects of age and perceived control: Life satisfaction levels and changes had stronger predictive effects for mortality hazards among older adults. Perceived control was associated with lower mortality hazards; however, this effect was diminished for those who experienced accelerated life satisfaction decline. Variance decomposition suggests that predictive effects of life satisfaction trajectories were partially unique (3%-6%) and partially shared with physical health, perceived control, and social orientation (17%-19%). Our discussion focuses on the strengths and challenges of a predictive approach to link developmental changes (in life satisfaction) to mortality hazards, and considers implications of our findings for healthy aging. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

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.

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.

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.

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.

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.

Ratio of Systolic Blood Pressure to Right Atrial Pressure, a Novel Marker to Predict Morbidity and Mortality in Acute Systolic Heart Failure.

Science.gov (United States)

Omar, Hesham R; Charnigo, Richard; Guglin, Maya

2017-04-01

Congestion is the main contributor to heart failure (HF) morbidity and mortality. We assessed the combined role of congestion and decreased forward flow in predicting morbidity and mortality in acute systolic HF. The Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness trial data set was used to determine if the ratio of simultaneously measured systolic blood pressure (SBP)/right atrial pressure (RAP) on admission predicted HF rehospitalization and 6-month mortality. One hundred ninety-five patients (mean age 56.5 years, 75% men) who received pulmonary artery catheterization were studied. The RAP, SBP, and SBP/RAP had an area under the curve (AUC) of 0.593 (p = 0.0205), 0.585 (p = 0.0359), and 0.621 (p = 0.0026), respectively, in predicting HF rehospitalization. The SBP/RAP was a superior marker of HF rehospitalization compared with RAP alone (difference in AUC 0.0289, p = 0.0385). The optimal criterion of SBP/RAP AUC 0.622, p = 0.0108, and a cut-off value of SBP/RAP <8 had a sensitivity of 61.9% and specificity 64.1% in predicting mortality. Multivariate analysis showed that an SBP/RAP <11 independently predicted rehospitalization for HF (estimated odds ratio 3.318, 95% confidence interval 1.692 to 6.506, p = 0.0005) and an SBP/RAP <8 independently predicted mortality (estimated hazard ratio 2.025, 95% confidence interval 1.069 to 3.833, p = 0.030). In conclusion, SBP/RAP ratio is a marker that identifies a spectrum of complications after hospitalization of patients with decompensated systolic HF, starting with increased incidence of HF rehospitalization at SBP/RAP <11 to increased mortality with SBP/RAP <8. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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

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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.

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.

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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.

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

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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.

[Risk Prediction Using Routine Data: Development and Validation of Multivariable Models Predicting 30- and 90-day Mortality after Surgical Treatment of Colorectal Cancer].

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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

Comparison of the Full Outline of UnResponsiveness score and the Glasgow Coma Scale in predicting mortality in critically ill patients*.

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Wijdicks, Eelco F M; Kramer, Andrew A; Rohs, Thomas; Hanna, Susan; Sadaka, Farid; O'Brien, Jacklyn; Bible, Shonna; Dickess, Stacy M; Foss, Michelle

2015-02-01

Impaired consciousness has been incorporated in prediction models that are used in the ICU. The Glasgow Coma Scale has value but is incomplete and cannot be assessed in intubated patients accurately. The Full Outline of UnResponsiveness score may be a better predictor of mortality in critically ill patients. Thirteen ICUs at five U.S. hospitals. One thousand six hundred ninety-five consecutive unselected ICU admissions during a six-month period in 2012. Glasgow Coma Scale and Full Outline of UnResponsiveness score were recorded within 1 hour of admission. Baseline characteristics and physiologic components of the Acute Physiology and Chronic Health Evaluation system, as well as mortality were linked to Glasgow Coma Scale/Full Outline of UnResponsiveness score information. None. We recruited 1,695 critically ill patients, of which 1,645 with complete data could be linked to data in the Acute Physiology and Chronic Health Evaluation system. The area under the receiver operating characteristic curve of predicting ICU mortality using the Glasgow Coma Scale was 0.715 (95% CI, 0.663-0.768) and using the Full Outline of UnResponsiveness score was 0.742 (95% CI, 0.694-0.790), statistically different (p = 0.001). A similar but nonsignificant difference was found for predicting hospital mortality (p = 0.078). The respiratory and brainstem reflex components of the Full Outline of UnResponsiveness score showed a much wider range of mortality than the verbal component of Glasgow Coma Scale. In multivariable models, the Full Outline of UnResponsiveness score was more useful than the Glasgow Coma Scale for predicting mortality. The Full Outline of UnResponsiveness score might be a better prognostic tool of ICU mortality than the Glasgow Coma Scale in critically ill patients, most likely a result of incorporating brainstem reflexes and respiration into the Full Outline of UnResponsiveness score.

The derivation and validation of a simple model for predicting in-hospital mortality of acutely admitted patients to internal medicine wards.

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Sakhnini, Ali; Saliba, Walid; Schwartz, Naama; Bisharat, Naiel

2017-06-01

Limited information is available about clinical predictors of in-hospital mortality in acute unselected medical admissions. Such information could assist medical decision-making.To develop a clinical model for predicting in-hospital mortality in unselected acute medical admissions and to test the impact of secondary conditions on hospital mortality.This is an analysis of the medical records of patients admitted to internal medicine wards at one university-affiliated hospital. Data obtained from the years 2013 to 2014 were used as a derivation dataset for creating a prediction model, while data from 2015 was used as a validation dataset to test the performance of the model. For each admission, a set of clinical and epidemiological variables was obtained. The main diagnosis at hospitalization was recorded, and all additional or secondary conditions that coexisted at hospital admission or that developed during hospital stay were considered secondary conditions.The derivation and validation datasets included 7268 and 7843 patients, respectively. The in-hospital mortality rate averaged 7.2%. The following variables entered the final model; age, body mass index, mean arterial pressure on admission, prior admission within 3 months, background morbidity of heart failure and active malignancy, and chronic use of statins and antiplatelet agents. The c-statistic (ROC-AUC) of the prediction model was 80.5% without adjustment for main or secondary conditions, 84.5%, with adjustment for the main diagnosis, and 89.5% with adjustment for the main diagnosis and secondary conditions. The accuracy of the predictive model reached 81% on the validation dataset.A prediction model based on clinical data with adjustment for secondary conditions exhibited a high degree of prediction accuracy. We provide a proof of concept that there is an added value for incorporating secondary conditions while predicting probabilities of in-hospital mortality. Further improvement of the model performance

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

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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.

Prediction of toxic metals concentration using artificial intelligence techniques

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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.

Blunted cyclic variation of heart rate predicts mortality risk in post-myocardial infarction, end-stage renal disease, and chronic heart failure patients.

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Hayano, Junichiro; Yasuma, Fumihiko; Watanabe, Eiichi; Carney, Robert M; Stein, Phyllis K; Blumenthal, James A; Arsenos, Petros; Gatzoulis, Konstantinos A; Takahashi, Hiroshi; Ishii, Hideki; Kiyono, Ken; Yamamoto, Yoshiharu; Yoshida, Yutaka; Yuda, Emi; Kodama, Itsuo

2017-08-01

Cyclic variation of heart rate (CVHR) associated with sleep-disordered breathing is thought to reflect cardiac autonomic responses to apnoeic/hypoxic stress. We examined whether blunted CVHR observed in ambulatory ECG could predict the mortality risk. CVHR in night-time Holter ECG was detected by an automated algorithm, and the prognostic relationships of the frequency (FCV) and amplitude (ACV) of CVHR were examined in 717 patients after myocardial infarction (post-MI 1, 6% mortality, median follow-up 25 months). The predictive power was prospectively validated in three independent cohorts: a second group of 220 post-MI patients (post-MI 2, 25.5% mortality, follow-up 45 months); 299 patients with end-stage renal disease on chronic haemodialysis (ESRD, 28.1% mortality, follow-up 85 months); and 100 patients with chronic heart failure (CHF, 35% mortality, follow-up 38 months). Although CVHR was observed in ≥96% of the patients in all cohorts, FCV did not predict mortality in any cohort. In contrast, decreased ACV was a powerful predictor of mortality in the post-MI 1 cohort (hazard ratio [95% CI] per 1 ln [ms] decrement, 2.9 [2.2-3.7], P < 0.001). This prognostic relationship was validated in the post-MI 2 (1.8 [1.4-2.2], P < 0.001), ESRD (1.5 [1.3-1.8], P < 0.001), and CHF (1.4 [1.1-1.8], P = 0.02) cohorts. The prognostic value of ACV was independent of age, gender, diabetes, β-blocker therapy, left ventricular ejection fraction, sleep-time mean R-R interval, and FCV. Blunted CVHR detected by decreased ACV in a night-time Holter ECG predicts increased mortality risk in post-MI, ESRD, and CHF patients. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Cardiology.

Blunted cyclic variation of heart rate predicts mortality risk in post-myocardial infarction, end-stage renal disease, and chronic heart failure patients

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Hayano, Junichiro; Yasuma, Fumihiko; Watanabe, Eiichi; Carney, Robert M.; Stein, Phyllis K.; Blumenthal, James A.; Arsenos, Petros; Gatzoulis, Konstantinos A.; Takahashi, Hiroshi; Ishii, Hideki; Kiyono, Ken; Yamamoto, Yoshiharu; Yoshida, Yutaka; Yuda, Emi; Kodama, Itsuo

2017-01-01

Abstract Aims Cyclic variation of heart rate (CVHR) associated with sleep-disordered breathing is thought to reflect cardiac autonomic responses to apnoeic/hypoxic stress. We examined whether blunted CVHR observed in ambulatory ECG could predict the mortality risk. Methods and results CVHR in night-time Holter ECG was detected by an automated algorithm, and the prognostic relationships of the frequency (FCV) and amplitude (ACV) of CVHR were examined in 717 patients after myocardial infarction (post-MI 1, 6% mortality, median follow-up 25 months). The predictive power was prospectively validated in three independent cohorts: a second group of 220 post-MI patients (post-MI 2, 25.5% mortality, follow-up 45 months); 299 patients with end-stage renal disease on chronic haemodialysis (ESRD, 28.1% mortality, follow-up 85 months); and 100 patients with chronic heart failure (CHF, 35% mortality, follow-up 38 months). Although CVHR was observed in ≥96% of the patients in all cohorts, FCV did not predict mortality in any cohort. In contrast, decreased ACV was a powerful predictor of mortality in the post-MI 1 cohort (hazard ratio [95% CI] per 1 ln [ms] decrement, 2.9 [2.2–3.7], P < 0.001). This prognostic relationship was validated in the post-MI 2 (1.8 [1.4–2.2], P < 0.001), ESRD (1.5 [1.3–1.8], P < 0.001), and CHF (1.4 [1.1–1.8], P = 0.02) cohorts. The prognostic value of ACV was independent of age, gender, diabetes, β-blocker therapy, left ventricular ejection fraction, sleep-time mean R-R interval, and FCV. Conclusion Blunted CVHR detected by decreased ACV in a night-time Holter ECG predicts increased mortality risk in post-MI, ESRD, and CHF patients. PMID:27789562

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

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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

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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

The Ability of the Acute Physiology and Chronic Health Evaluation (APACHE IV Score to Predict Mortality in a Single Tertiary Hospital

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Jae Woo Choi

2017-08-01

Full Text Available Background The Acute Physiology and Chronic Health Evaluation (APACHE II model has been widely used in Korea. However, there have been few studies on the APACHE IV model in Korean intensive care units (ICUs. The aim of this study was to compare the ability of APACHE IV and APACHE II in predicting hospital mortality, and to investigate the ability of APACHE IV as a critical care triage criterion. Methods The study was designed as a prospective cohort study. Measurements of discrimination and calibration were performed using the area under the receiver operating characteristic curve (AUROC and the Hosmer-Lemeshow goodness-of-fit test respectively. We also calculated the standardized mortality ratio (SMR. Results The APACHE IV score, the Charlson Comorbidity index (CCI score, acute respiratory distress syndrome, and unplanned ICU admissions were independently associated with hospital mortality. The calibration, discrimination, and SMR of APACHE IV were good (H = 7.67, P = 0.465; C = 3.42, P = 0.905; AUROC = 0.759; SMR = 1.00. However, the explanatory power of an APACHE IV score >93 alone on hospital mortality was low at 44.1%. The explanatory power was increased to 53.8% when the hospital mortality was predicted using a model that considers APACHE IV >93 scores, medical admission, and risk factors for CCI >3 coincidentally. However, the discriminative ability of the prediction model was unsatisfactory (C index <0.70. Conclusions The APACHE IV presented good discrimination, calibration, and SMR for hospital mortality.

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

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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.

The ADHF/NT-proBNP risk score to predict 1-year mortality in hospitalized patients with advanced decompensated heart failure.

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Scrutinio, Domenico; Ammirati, Enrico; Guida, Pietro; Passantino, Andrea; Raimondo, Rosa; Guida, Valentina; Sarzi Braga, Simona; Canova, Paolo; Mastropasqua, Filippo; Frigerio, Maria; Lagioia, Rocco; Oliva, Fabrizio

2014-04-01

The acute decompensated heart failure/N-terminal pro-B-type natriuretic peptide (ADHF/NT-proBNP) score is a validated risk scoring system that predicts mortality in hospitalized heart failure patients with a wide range of left ventricular ejection fractions (LVEFs). We sought to assess discrimination and calibration of the score when applied to patients with advanced decompensated heart failure (AHF). We studied 445 patients hospitalized for AHF, defined by the presence of severe symptoms of worsening HF at admission, severely depressed LVEF, and the need for intravenous diuretic and/or inotropic drugs. The primary outcome was cumulative (in-hospital and post-discharge) mortality and post-discharge 1-year mortality. Separate analyses were performed for patients aged ≤ 70 years. A Seattle Heart Failure Score (SHFS) was calculated for each patient discharged alive. During follow-up, 144 patients (32.4%) died, and 69 (15.5%) underwent heart transplantation (HT) or ventricular assist device (VAD) implantation. After accounting for the competing events (VAD/HT), the ADHF/NT-proBNP score's C-statistic for cumulative mortality was 0.738 in the overall cohort and 0.771 in patients aged ≤ 70 years. The C-statistic for post-discharge mortality was 0.741 and 0.751, respectively. Adding prior (≤6 months) hospitalizations for HF to the score increased the C-statistic for post-discharge mortality to 0.759 in the overall cohort and to 0.774 in patients aged ≤ 70 years. Predicted and observed mortality rates by quartiles of score were highly correlated. The SHFS demonstrated adequate discrimination but underestimated the risk. The ADHF/NT-proBNP risk calculator is available at http://www.fsm.it/fsm/file/NTproBNPscore.zip. Our data suggest that the ADHF/NT-proBNP score may efficiently predict mortality in patients hospitalized with AHF. Copyright © 2014 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

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

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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.

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

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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.

Air pollution and associated human mortality: The role of air pollutant emissions, climate change and methane concentration increases during the industrial period

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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

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

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

Syndecan-4 Is an Independent Predictor of All-Cause as Well as Cardiovascular Mortality in Hemodialysis Patients.

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Andrzej J Jaroszyński

Full Text Available Left ventricular hypertrophy is associated withincreased mortality in hemodialysis (HD patients.Syndecan-4 plays a role in many processes that are involved in the heart fibrosis and hypertrophy.We designed this study to prospectively determine whether syndecan-4 was predictive of mortality in a group of HD patients.In total, 191 HD patients were included. Clinical, biochemical and echocardiographic parameters were recorded. HD patients were followed-up for 23.18 ± 4.02 months.Syndecan-4 levels correlated strongly with geometrical echocardiographic parameters and ejection fraction. Relations with pressure-related parameters were weak and only marginally significant. Using the receiver operating characteristics the optimal cut-off points in predicting all-cause as well as cardiovascular (CV mortality were evaluated and patients were divided into low and high syndecan-4 groups. A Kaplan-Meier analysis showed that the cumulative incidences of all-cause as well as CV mortality were higher in high serum syndecan-4 group compared with those with low serum syndecan-4 (p<0.001 in both cases.A multivariate Cox proportional hazards regression analysis revealed syndecan-4 concentration to be an independent and significant predictor of all-cause (hazard ratio, 2.99; confidence interval, 2.34 to 3.113; p<0.001as well as CV mortality (hazard ratio, 2.81;confidence interval, 2.28to3.02; p<0.001.Serum syndecan-4 concentration reflects predominantly geometrical echocardiographic parameters. In HD patients serum syndecan-4 concentration is independently associated with all-cause as well as CV mortality.

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

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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.

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...

Macrophage activation markers predict mortality in patients with liver cirrhosis without or with acute-on-chronic liver failure (ACLF)

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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...

Synergistic interactions between leaf beetle herbivory and fire enhance tamarisk (Tamarix spp.) mortality

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Drus, Gail M.; Dudley, Tom L.; Antonio, Carla M.; Even, Thomas J.; Brooks, Matt L.; Matchett, J.R.

2014-01-01

The combined effects of herbivory and fire on plant mortality were investigated using prescribed burns of tamarisk (Tamarix ramosissima Lebed) exposed to herbivory by the saltcedar leaf beetle (Chrysomelidae: Diorhabda carinulata Desbrocher). Tamarix stands in the Humboldt Sink (NV, USA) were divided into three treatments: summer burn (August 2006), fall burn (October 2006) and control (unburned), and litter depth was manipulated to vary fire intensity within burn seasons. A gradient of existing herbivory impact was described with three plant condition metrics prior to fire: reduced proportions of green canopy, percent root crown starch sampled at the height of the growing season (August 2006), and percent root crown starch measured during dormancy (December 2006). August root crown starch concentration and proportion green canopy were strongly correlated, although the proportion green canopy predicted mortality better than August root crown starch. December root crown starch concentration was more depleted in unburned trees and in trees burned during the summer than in fall burn trees. Mortality in summer burned trees was higher than fall burned trees due to higher fire intensity, but December root crown starch available for resprouting in the spring was also lower in summer burned trees. The greatest mortality was observed in trees with the lowest December root crown starch concentration which were exposed to high fire intensity. Disproportionate changes in the slope and curvature of prediction traces as fire intensity and December starch reach reciprocal maximum and minimum levels indicate that beetle herbivory and fire intensity are synergistic.

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

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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.

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...

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

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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.

Study on the Relationship between Manganese Concentrations in Rural Drinking Water and Incidence and Mortality Caused by Cancer in Huai’an City

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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

Prediction of mortality using on-line, self-reported health data: empirical test of the RealAge score.

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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.

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

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Tzeng, Wen Sheng; Wu, Reng Hong; Lin, Ching Yih; Chen, Jyh Jou; Sheu, Ming Juen; Koay, Lok Beng; Lee, Chuan [Chi-Mei Foundation Medical Center, Tainan (China)

2009-10-15

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 < 0.05). Multivariate analysis showed that a Child-Pugh score > 11 or an MELD score > 20 predicted increased risk of death at 30, 60 and 360 days (p < 0.05). APACHE II scores could only predict mortality at 360 days (p < 0.05). A Child-Pugh score > 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.

Finely Resolved On-Road PM2.5 and Estimated Premature Mortality in Central North Carolina.

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Chang, Shih Ying; Vizuete, William; Serre, Marc; Vennam, Lakshmi Pradeepa; Omary, Mohammad; Isakov, Vlad; Breen, Michael; Arunachalam, Saravanan

2017-12-01

To quantify the on-road PM 2.5 -related premature mortality at a national scale, previous approaches to estimate concentrations at a 12-km × 12-km or larger grid cell resolution may not fully characterize concentration hotspots that occur near roadways and thus the areas of highest risk. Spatially resolved concentration estimates from on-road emissions to capture these hotspots may improve characterization of the associated risk, but are rarely used for estimating premature mortality. In this study, we compared the on-road PM 2.5 -related premature mortality in central North Carolina with two different concentration estimation approaches-(i) using the Community Multiscale Air Quality (CMAQ) model to model concentration at a coarser resolution of a 36-km × 36-km grid resolution, and (ii) using a hybrid of a Gaussian dispersion model, CMAQ, and a space-time interpolation technique to provide annual average PM 2.5 concentrations at a Census-block level (∼105,000 Census blocks). The hybrid modeling approach estimated 24% more on-road PM 2.5 -related premature mortality than CMAQ. The major difference is from the primary on-road PM 2.5 where the hybrid approach estimated 2.5 times more primary on-road PM 2.5 -related premature mortality than CMAQ due to predicted exposure hotspots near roadways that coincide with high population areas. The results show that 72% of primary on-road PM 2.5 premature mortality occurs within 1,000 m from roadways where 50% of the total population resides, highlighting the importance to characterize near-road primary PM 2.5 and suggesting that previous studies may have underestimated premature mortality due to PM 2.5 from traffic-related emissions. © 2017 Society for Risk Analysis.

Mathematical Model to Predict Skin Concentration after Topical Application of Drugs

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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.

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

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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

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

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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

Prediction of five-year all-cause mortality in Chinese patients with type 2 diabetes mellitus - A population-based retrospective cohort study.

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Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen

2017-06-01

This study aimed to develop and validate an all-cause mortality risk prediction model for Chinese primary care patients with type 2 diabetes mellitus(T2DM) in Hong Kong. A population-based retrospective cohort study was conducted on 132,462 Chinese patients who had received public primary care services during 2010. Each gender sample was randomly split on a 2:1 basis into derivation and validation cohorts and was followed-up for a median period of 5years. Gender-specific mortality risk prediction models showing the interaction effect between predictors and age were derived using Cox proportional hazards regression with forward stepwise approach. Developed models were compared with pre-existing models by Harrell's C-statistic and calibration plot using validation cohort. Common predictors of increased mortality risk in both genders included: age; smoking habit; diabetes duration; use of anti-hypertensive agents, insulin and lipid-lowering drugs; body mass index; hemoglobin A1c; systolic blood pressure(BP); total cholesterol to high-density lipoprotein-cholesterol ratio; urine albumin to creatinine ratio(urine ACR); and estimated glomerular filtration rate(eGFR). Prediction models showed better discrimination with Harrell"'s C-statistics of 0.768(males) and 0.782(females) and calibration power from the plots than previously established models. Our newly developed gender-specific models provide a more accurate predicted 5-year mortality risk for Chinese diabetic patients than other established models. Copyright © 2017 Elsevier Inc. All rights reserved.

Gender differences in the predictive role of self-rated health on short-term risk of mortality among older adults

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Shervin Assari

2016-09-01

Full Text Available Objectives: Despite the well-established association between self-rated health and mortality, research findings have been inconsistent regarding how men and women differ on this link. Using a national sample in the United States, this study compared American male and female older adults for the predictive role of baseline self-rated health on the short-term risk of mortality. Methods: This longitudinal study followed 1500 older adults (573 men (38.2% and 927 women (61.8% aged 66 years or older for 3 years from 2001 to 2004. The main predictor of interest was self-rated health, which was measured using a single item in 2001. The outcome was the risk of all-cause mortality during the 3-year follow-up period. Demographic factors (race and age, socio-economic factors (education and marital status, and health behaviors (smoking and drinking were covariates. Gender was the focal moderator. We ran logistic regression models in the pooled sample and also stratified by gender, with self-rated health treated as either nominal variables, poor compared to other levels (i.e. fair, good, or excellent or excellent compared to other levels (i.e. good, fair, or poor, or an ordinal variable. Results: In the pooled sample, baseline self-rated health predicted mortality risk, regardless of how the variable was treated. We found a significant interaction between gender and poor self-rated health, indicating a stronger effect of poor self-rated health on mortality risk for men compared to women. Gender did not interact with excellent self-rated health on mortality. Conclusion: Perceived poor self-rated health better reflects risk of mortality over a short period of time for older men compared to older women. Clinicians may need to take poor self-rated health of older men very seriously. Future research should test whether the differential predictive validity of self-rated health based on gender is due to a different meaning of poor self-rated health for older men

[Risk factors associated with long-term mortality in patients with pulmonary embolism and the predictive value of Charlson comorbidity index].

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Zhou, Haixia; Tang, Yangjiang; Wang, Lan; Shi, Chaoli; Feng, Yulin; Yi, Qun

2016-01-26

To explore the risk factors associated with long-term mortality and the predictive value of Charlson comorbidity index (CCI) for long-term mortality in patients with pulmonary embolism (PE). A total of 234 patients with confirmed PE from the medical departments of West China Hospital of Sichuan University from January 2010 and December 2012 were enrolled, and these meeting the inclusion criteria were followed-up for 2 years after discharge. The long-term mortality was calculated and univariate and multivariate analysis were performed to identify the risk factors associated with long-term mortality of PE. All the patients were assessed the comorbidity burden with the CCI, and survival analysis was used to study its value in predicting long-term mortality in patients with PE. A total of 176 PE patients were finally included in this study, and 53 patients died during the follow-up period, with 2 years' mortality 30.1%. The univariate analysis showed diabetes (P=0.034), malignant neoplasm (P=0.001), chronic lung disease (P=0.035), liver disease (P=0.048), in bed for a long time (P=0.049), inappropriate anticoagulant therapy (P=0.016) were associated with the long-term mortality of PE patients. Among these risk factors, the multivariate analysis revealed malignant neoplasm (OR=9.28, 95%CI: 2.85-31.00, P=0.003), chronic lung disease (OR=2.96, 95%CI: 1.15-7.62, P=0.024), inappropriate anticoagulant therapy (OR=4.08, 95%CI: 1.64-10.20, P=0.003) were the independent risk factors. The median CCI scores for died PE patients during follow-up was higher than that for the survived PE patients ((2(1, 3) vs 1(0, 2), Prisk of long-term mortality compared with patients with no comorbidity (CCI=0) (95%CI: 1.14-6.00, P=0.024). The per 1-score increase of CCI was associated with 1.76-fold increased risk of long-term mortality in PE patients (95%CI: 1.04-2.97, P=0.035). Survival analysis showed that the 2-year cumulative survival of PE patients with CCI score≥1 was significant lower

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

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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.

Plasma 8-iso-Prostaglandin F2α concentrations and outcomes after acute intracerebral hemorrhage.

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Du, Quan; Yu, Wen-Hua; Dong, Xiao-Qiao; Yang, Ding-Bo; Shen, Yong-Feng; Wang, Hao; Jiang, Li; Du, Yuan-Feng; Zhang, Zu-Yong; Zhu, Qiang; Che, Zhi-Hao; Liu, Qun-Jie

2014-11-01

Higher plasma 8-iso-Prostaglandin F2α concentrations have been associated with poor outcome of severe traumatic brain injury. We further investigated the relationships between plasma 8-iso-Prostaglandin F2α concentrations and clinical outcomes in patients with acute intracerebral hemorrhage. Plasma 8-iso-Prostaglandin F2α concentrations of 128 consecutive patients and 128 sex- and gender-matched healthy subjects were measured by enzyme-linked immunosorbent assay. We assessed their relationships with disease severity and clinical outcomes including 1-week mortality, 6-month mortality and unfavorable outcome (modified Rankin Scale score>2). Plasma 8-iso-Prostaglandin F2α concentrations were substantially higher in patients than in healthy controls. Plasma 8-iso-Prostaglandin F2α concentrations were positively associated with National Institutes of Health Stroke Scale (NIHSS) scores and hematoma volume using a multivariate linear regression. It emerged as an independent predictor for clinical outcomes of patients using a forward stepwise logistic regression. ROC curves identified the predictive values of plasma 8-iso-Prostaglandin F2α concentrations, and found its predictive value was similar to NIHSS scores and hematoma volumes. However, it just numerically added the predictive values of NIHSS score and hematoma volume. Increased plasma 8-iso-Prostaglandin F2α concentrations are associated with disease severity and clinical outcome after acute intracerebral hemorrhage. Copyright © 2014 Elsevier B.V. All rights reserved.

Five year experience in management of perforated peptic ulcer and validation of common mortality risk prediction models - are existing models sufficient? A retrospective cohort study.

Science.gov (United States)

Anbalakan, K; Chua, D; Pandya, G J; Shelat, V G

2015-02-01

Emergency surgery for perforated peptic ulcer (PPU) is associated with significant morbidity and mortality. Accurate and early risk stratification is important. The primary aim of this study is to validate the various existing MRPMs and secondary aim is to audit our experience of managing PPU. 332 patients who underwent emergency surgery for PPU at a single intuition from January 2008 to December 2012 were studied. Clinical and operative details were collected. Four MRPMs: American Society of Anesthesiology (ASA) score, Boey's score, Mannheim peritonitis index (MPI) and Peptic ulcer perforation (PULP) score were validated. Median age was 54.7 years (range 17-109 years) with male predominance (82.5%). 61.7% presented within 24 h of onset of abdominal pain. Median length of stay was 7 days (range 2-137 days). Intra-abdominal collection, leakage, re-operation and 30-day mortality rates were 8.1%, 2.1%, 1.2% and 7.2% respectively. All the four MRPMs predicted intra-abdominal collection and mortality; however, only MPI predicted leak (p = 0.01) and re-operation (p = 0.02) rates. The area under curve for predicting mortality was 75%, 72%, 77.2% and 75% for ASA score, Boey's score, MPI and PULP score respectively. Emergency surgery for PPU has low morbidity and mortality in our experience. MPI is the only scoring system which predicts all - intra-abdominal collection, leak, reoperation and mortality. All four MRPMs had a similar and fair accuracy to predict mortality, however due to geographic and demographic diversity and inherent weaknesses of exiting MRPMs, quest for development of an ideal model should continue. Copyright © 2015 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

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

Predictive value of a profile of routine blood measurements on mortality in older persons in the general population: the Leiden 85-plus Study.

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Anne H van Houwelingen

Full Text Available BACKGROUND: Various questionnaires and performance tests predict mortality in older people. However, most are heterogeneous, laborious and a validated consensus index is not available yet. Since most older people are regularly monitored by laboratory tests, we compared the predictive value of a profile of seven routine laboratory measurements on mortality in older persons in the general population with other predictors of mortality; gait speed and disability in instrumental activities of daily living (IADL. METHODOLOGY/PRINCIPAL FINDINGS: Within the Leiden 85-plus Study, a prospective population-based study, we followed 562 participants aged 85 years for mortality over five years. At baseline (age 85 years high-density lipoprotein cholesterol, albumin, alanine transaminase, hemoglobin, creatinin clearance, C-reactive protein and homocysteine were measured. Participants were stratified based on their number of laboratory abnormalities (0, 1, 2-4 and 5-7. The predictive capacity was compared with gait speed (6-meter walking test and disability in IADL (Groningen Activity Restriction Scale by C-statistics. At baseline, 418 (74% 85-year old participants had at least one laboratory abnormality. All cause mortality risk increased with increasing number of laboratory abnormalities to a hazard ratio of 5.64 [95% CI 3.49-9.12] for those with 5-7 laboratory abnormalities (p<0.001 compared to those without abnormalities. The c-statistic was 0.66 [95% CI 0.59-0.69], similar to that of gait speed and disability in IADL. CONCLUSIONS/SIGNIFICANCE: In the general population of oldest old, the number of abnormalities in seven routine laboratory measurements predicts five-year mortality as accurately as gait speed and IADL disability.

Predicted risks of second malignant neoplasm incidence and mortality due to secondary neutrons in a girl and boy receiving proton craniospinal irradiation

International Nuclear Information System (INIS)

Taddei, Phillip J; Mirkovic, Dragan; Zhang Rui; Giebeler, Annelise; Harvey, Mark; Newhauser, Wayne D; Mahajan, Anita; Kornguth, David; Woo, Shiao

2010-01-01

The purpose of this study was to compare the predicted risks of second malignant neoplasm (SMN) incidence and mortality from secondary neutrons for a 9-year-old girl and a 10-year-old boy who received proton craniospinal irradiation (CSI). SMN incidence and mortality from neutrons were predicted from equivalent doses to radiosensitive organs for cranial, spinal and intracranial boost fields. Therapeutic proton absorbed dose and equivalent dose from neutrons were calculated using Monte Carlo simulations. Risks of SMN incidence and mortality in most organs and tissues were predicted by applying risks models from the National Research Council of the National Academies to the equivalent dose from neutrons; for non-melanoma skin cancer, risk models from the International Commission on Radiological Protection were applied. The lifetime absolute risks of SMN incidence due to neutrons were 14.8% and 8.5%, for the girl and boy, respectively. The risks of a fatal SMN were 5.3% and 3.4% for the girl and boy, respectively. The girl had a greater risk for any SMN except colon and liver cancers, indicating that the girl's higher risks were not attributable solely to greater susceptibility to breast cancer. Lung cancer predominated the risk of SMN mortality for both patients. This study suggests that the risks of SMN incidence and mortality from neutrons may be greater for girls than for boys treated with proton CSI.

HPA-axis hyperactivity and mortality in psychotic depressive disorder: preliminary findings.

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Coryell, William; Fiedorowicz, Jess; Zimmerman, Mark; Young, Elizabeth

2008-06-01

The excess mortality associated with depressive disorders has been most often attributed to risks for suicide but diverse findings indicate that depressive disorders also increase risks for cardiovascular (CV) mortality. Among the possible mediators is the hypothalamic-pituitary-adrenal (HPA)-axis hyperactivity that characterizes many cases of relatively severe depressive disorder and severity is characteristic of psychotic depressive disorder. The following describes a 17-year mortality follow-up of 54 patients with Research Diagnostic Criteria (RDC) psychotic major depression or schizoaffective, mainly affective, depression. All had baseline assessments that included a 1mg dexamethasone suppression test with post-dexamethasone samples at 8 a.m., 4 p.m. and 11 p.m. Regression analyses showed that both greater age and higher maximum post-dexamethasone cortisol concentrations predicted deaths due to CV causes (t=4.01, pdepressive disorder to CV mortality.

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.

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

Trauma and Injury Severity Score in Predicting Mortality of Polytrauma Patients

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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

Amikacin Concentrations Predictive of Ototoxicity in Multidrug-Resistant Tuberculosis Patients.

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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.

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.

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...

Mortality of marine planktonic copepods : global rates and patterns

DEFF Research Database (Denmark)

Hirst, A.G.; Kiørboe, Thomas

2002-01-01

Using life history theory we make predictions of mortality rates in marine epi-pelagic copepods from field estimates of adult fecundity, development times and adult sex ratios. Predicted mortality increases with temperature in both broadcast and sac spawning copepods, and declines with body weight...... in broadcast spawners, while mortality in sac spawners is invariant with body size. Although the magnitude of copepod mortality does lie close to the overall general pattern for pelagic animals, copepod mortality scaling is much weaker, implying that small copepods are avoiding some mortality agent....../s that other pelagic animals of a similar size do not, We compile direct in situ estimates of copepod mortality and compare these with our indirect predictions; we find the predictions generally match the field measurements well with respect to average rates and patterns. Finally, by comparing in situ adult...

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...

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

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.

Prediction and analysis of near-road concentrations using a reduced-form emission/dispersion model

Directory of Open Access Journals (Sweden)

Kononowech Robert

2010-06-01

Full Text Available Abstract Background Near-road exposures of traffic-related air pollutants have been receiving increased attention due to evidence linking emissions from high-traffic roadways to adverse health outcomes. To date, most epidemiological and risk analyses have utilized simple but crude exposure indicators, most typically proximity measures, such as the distance between freeways and residences, to represent air quality impacts from traffic. This paper derives and analyzes a simplified microscale simulation model designed to predict short- (hourly to long-term (annual average pollutant concentrations near roads. Sensitivity analyses and case studies are used to highlight issues in predicting near-road exposures. Methods Process-based simulation models using a computationally efficient reduced-form response surface structure and a minimum number of inputs integrate the major determinants of air pollution exposures: traffic volume and vehicle emissions, meteorology, and receptor location. We identify the most influential variables and then derive a set of multiplicative submodels that match predictions from "parent" models MOBILE6.2 and CALINE4. The assembled model is applied to two case studies in the Detroit, Michigan area. The first predicts carbon monoxide (CO concentrations at a monitoring site near a freeway. The second predicts CO and PM2.5 concentrations in a dense receptor grid over a 1 km2 area around the intersection of two major roads. We analyze the spatial and temporal patterns of pollutant concentration predictions. Results Predicted CO concentrations showed reasonable agreement with annual average and 24-hour measurements, e.g., 59% of the 24-hr predictions were within a factor of two of observations in the warmer months when CO emissions are more consistent. The highest concentrations of both CO and PM2.5 were predicted to occur near intersections and downwind of major roads during periods of unfavorable meteorology (e.g., low wind

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.

Effects of impairment in activities of daily living on predicting mortality following hip fracture surgery in studies using administrative healthcare databases

Science.gov (United States)

2014-01-01

Background Impairment in activities of daily living (ADL) is an important predictor of outcomes although many administrative databases lack information on ADL function. We evaluated the impact of ADL function on predicting postoperative mortality among older adults with hip fractures in Ontario, Canada. Methods Sociodemographic and medical correlates of ADL impairment were first identified in a population of older adults with hip fractures who had ADL information available prior to hip fracture. A logistic regression model was developed to predict 360-day postoperative mortality and the predictive ability of this model were compared when ADL impairment was included or omitted from the model. Results The study sample (N = 1,329) had a mean age of 85.2 years, were 72.8% female and the majority resided in long-term care (78.5%). Overall, 36.4% of individuals died within 360 days of surgery. After controlling for age, sex, medical comorbidity and medical conditions correlated with ADL impairment, addition of ADL measures improved the logistic regression model for predicting 360 day mortality (AIC = 1706.9 vs. 1695.0; c -statistic = 0.65 vs 0.67; difference in - 2 log likelihood ratios: χ2 = 16.9, p = 0.002). Conclusions Direct measures of ADL impairment provides additional prognostic information on mortality for older adults with hip fractures even after controlling for medical comorbidity. Observational studies using administrative databases without measures of ADLs may be potentially prone to confounding and bias and case-mix adjustment for hip fracture outcomes should include ADL measures where these are available. PMID:24472282

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...

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.

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.

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

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�

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.

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...

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.

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.

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

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.

External validation of Vascular Study Group of New England risk predictive model of mortality after elective abdominal aorta aneurysm repair in the Vascular Quality Initiative and comparison against established models.

Science.gov (United States)

Eslami, Mohammad H; Rybin, Denis V; Doros, Gheorghe; Siracuse, Jeffrey J; Farber, Alik

2018-01-01

The purpose of this study is to externally validate a recently reported Vascular Study Group of New England (VSGNE) risk predictive model of postoperative mortality after elective abdominal aortic aneurysm (AAA) repair and to compare its predictive ability across different patients' risk categories and against the established risk predictive models using the Vascular Quality Initiative (VQI) AAA sample. The VQI AAA database (2010-2015) was queried for patients who underwent elective AAA repair. The VSGNE cases were excluded from the VQI sample. The external validation of a recently published VSGNE AAA risk predictive model, which includes only preoperative variables (age, gender, history of coronary artery disease, chronic obstructive pulmonary disease, cerebrovascular disease, creatinine levels, and aneurysm size) and planned type of repair, was performed using the VQI elective AAA repair sample. The predictive value of the model was assessed via the C-statistic. Hosmer-Lemeshow method was used to assess calibration and goodness of fit. This model was then compared with the Medicare, Vascular Governance Northwest model, and Glasgow Aneurysm Score for predicting mortality in VQI sample. The Vuong test was performed to compare the model fit between the models. Model discrimination was assessed in different risk group VQI quintiles. Data from 4431 cases from the VSGNE sample with the overall mortality rate of 1.4% was used to develop the model. The internally validated VSGNE model showed a very high discriminating ability in predicting mortality (C = 0.822) and good model fit (Hosmer-Lemeshow P = .309) among the VSGNE elective AAA repair sample. External validation on 16,989 VQI cases with an overall 0.9% mortality rate showed very robust predictive ability of mortality (C = 0.802). Vuong tests yielded a significant fit difference favoring the VSGNE over then Medicare model (C = 0.780), Vascular Governance Northwest (0.774), and Glasgow Aneurysm Score (0

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

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.

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)

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.

Validation of a new mortality risk prediction model for people 65 years and older in northwest Russia: The Crystal risk score.

Science.gov (United States)

Turusheva, Anna; Frolova, Elena; Bert, Vaes; Hegendoerfer, Eralda; Degryse, Jean-Marie

2017-07-01

Prediction models help to make decisions about further management in clinical practice. This study aims to develop a mortality risk score based on previously identified risk predictors and to perform internal and external validations. In a population-based prospective cohort study of 611 community-dwelling individuals aged 65+ in St. Petersburg (Russia), all-cause mortality risks over 2.5 years follow-up were determined based on the results obtained from anthropometry, medical history, physical performance tests, spirometry and laboratory tests. C-statistic, risk reclassification analysis, integrated discrimination improvement analysis, decision curves analysis, internal validation and external validation were performed. Older adults were at higher risk for mortality [HR (95%CI)=4.54 (3.73-5.52)] when two or more of the following components were present: poor physical performance, low muscle mass, poor lung function, and anemia. If anemia was combined with high C-reactive protein (CRP) and high B-type natriuretic peptide (BNP) was added the HR (95%CI) was slightly higher (5.81 (4.73-7.14)) even after adjusting for age, sex and comorbidities. Our models were validated in an external population of adults 80+. The extended model had a better predictive capacity for cardiovascular mortality [HR (95%CI)=5.05 (2.23-11.44)] compared to the baseline model [HR (95%CI)=2.17 (1.18-4.00)] in the external population. We developed and validated a new risk prediction score that may be used to identify older adults at higher risk for mortality in Russia. Additional studies need to determine which targeted interventions improve the outcomes of these at-risk individuals. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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.

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)

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.

Development and evaluation of a regression-based model to predict cesium-137 concentration ratios for saltwater fish

International Nuclear Information System (INIS)

Pinder, John E.; Rowan, David J.; Smith, Jim T.

2016-01-01

Data from published studies and World Wide Web sources were combined to develop a regression model to predict "1"3"7Cs concentration ratios for saltwater fish. Predictions were developed from 1) numeric trophic levels computed primarily from random resampling of known food items and 2) K concentrations in the saltwater for 65 samplings from 41 different species from both the Atlantic and Pacific Oceans. A number of different models were initially developed and evaluated for accuracy which was assessed as the ratios of independently measured concentration ratios to those predicted by the model. In contrast to freshwater systems, were K concentrations are highly variable and are an important factor in affecting fish concentration ratios, the less variable K concentrations in saltwater were relatively unimportant in affecting concentration ratios. As a result, the simplest model, which used only trophic level as a predictor, had comparable accuracies to more complex models that also included K concentrations. A test of model accuracy involving comparisons of 56 published concentration ratios from 51 species of marine fish to those predicted by the model indicated that 52 of the predicted concentration ratios were within a factor of 2 of the observed concentration ratios. - Highlights: • We developed a model to predict concentration ratios (C_r) for saltwater fish. • The model requires only a single input variable to predict C_r. • That variable is a mean numeric trophic level available at (fishbase.org). • The K concentrations in seawater were not an important predictor variable. • The median-to observed ratio for 56 independently measured C_r was 0.83.

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....

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

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.

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.

Development of Indoor Air Pollution Concentration Prediction by Geospatial Analysis

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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.

The Glasgow Prognostic Score at the Time of Palliative Esophageal Stent Insertion is a Predictive Factor of 30-Day Mortality and Overall Survival.

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Driver, Robert J; Handforth, Catherine; Radhakrishna, Ganesh; Bennett, Michael I; Ford, Alexander C; Everett, Simon M

2018-03-01

Optimizing the timing of esophageal stent insertion is a challenge, partly due to difficulty predicting survival in advanced malignancy. The Glasgow prognostic score (GPS) is a validated tool for predicting survival in a number of cancers. To assess the utility of the GPS in predicting 30-day mortality and overall survival postesophageal stent insertion. Patients at a tertiary referral center who had received an esophageal stent for palliation of dysphagia were included if they had a measurement of albumin and C-reactive protein (CRP) in the week preceding the procedure (n=209). Patients with both an elevated CRP (>10 mg/L) and hypoalbuminemia (L) were given a GPS score of 2 (GPS2). Patients with only one of these abnormalities were assigned as GPS1 and those with normal CRP and albumin were assigned as GPS0. Clinical and pathologic parameters were also collected to assess for potential confounding factors in the survival analysis. Increasing GPS was associated with 30-day mortality; for patients with GPS0, 30-day mortality was 5% (2/43), for GPS1 it was 23% (26/114), and for GPS2 it was 33% (17/52). The adjusted hazard ratio for overall poststent mortality was 1.6 (95% confidence interval, 1.1-2.4; P=0.02) for GPS1 and 2.4 (95% confidence interval, 1.5-3.8; PGPS2 patients compared with GPS0. GPS is an independent prognostic factor of 30-day mortality and overall survival after esophageal stent insertion. It is a potential adjunct to clinical assessment in identifying those patients at high-risk of short-term mortality poststent.

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.

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.

Extreme nonfasting remnant cholesterol vs extreme LDL cholesterol as contributors to cardiovascular disease and all-cause mortality in 90000 individuals from the general population.

Science.gov (United States)

Varbo, Anette; Freiberg, Jacob J; Nordestgaard, Børge G

2015-03-01

Increased nonfasting remnant cholesterol, like increased LDL cholesterol, is causally associated with increased risk for ischemic heart disease (IHD). We tested the hypothesis that extreme concentrations of nonfasting remnant and LDL cholesterol are equal contributors to the risk of IHD, myocardial infarction (MI), and all-cause mortality. We compared stepwise increasing concentrations of nonfasting remnant and LDL cholesterol for association with risk of IHD, MI, and all-cause mortality in approximately 90 000 individuals from the Danish general population. During up to 22 years of complete follow-up, 4435 participants developed IHD, 1722 developed MI, and 8121 died. Compared with participants with nonfasting remnant cholesterol cholesterol of 0.5-0.99 mmol/L (19.3-38.2 mg/dL) to 2.4 (1.9-2.9) for remnant cholesterol of ≥1.5 mmol/L (58 mg/dL) (P for trend LDL cholesterol LDL cholesterol of 3-3.99 mmol/L (115.8-154 mg/dL) to 2.3 (1.9-2.8) for LDL cholesterol of ≥5 mmol/L (193 mg/dL) (P cholesterol (P LDL cholesterol (P cholesterol concentrations were associated stepwise with all-cause mortality ranging from hazard ratio 1.0 (0.9-1.1) to 1.6 (1.4-1.9) (P LDL cholesterol concentrations were associated with decreased all-cause mortality risk in a U-shaped pattern, with hazard ratios from 0.8 (0.7-0.8) to 0.9 (0.8-1.0) (P = 0.002). After mutual adjustment, LDL cholesterol best predicted MI, and remnant cholesterol best predicted all-cause mortality. Both lipoproteins were associated equally with risk of IHD and MI; however, only nonfasting remnant cholesterol concentrations were associated stepwise with increased all-cause mortality risk. © 2015 American Association for Clinical Chemistry.

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.

Clostridium Difficile Infection Due to Pneumonia Treatment: Mortality Risk Models.

Science.gov (United States)

Chmielewska, M; Zycinska, K; Lenartowicz, B; Hadzik-Błaszczyk, M; Cieplak, M; Kur, Z; Wardyn, K A

2017-01-01

One of the most common gastrointestinal infection after the antibiotic treatment of community or nosocomial pneumonia is caused by the anaerobic spore Clostridium difficile (C. difficile). The aim of this study was to retrospectively assess mortality due to C. difficile infection (CDI) in patients treated for pneumonia. We identified 94 cases of post-pneumonia CDI out of the 217 patients with CDI. The mortality issue was addressed by creating a mortality risk models using logistic regression and multivariate fractional polynomial analysis. The patients' demographics, clinical features, and laboratory results were taken into consideration. To estimate the influence of the preceding respiratory infection, a pneumonia severity scale was included in the analysis. The analysis showed two statistically significant and clinically relevant mortality models. The model with the highest prognostic strength entailed age, leukocyte count, serum creatinine and urea concentration, hematocrit, coexisting neoplasia or chronic obstructive pulmonary disease. In conclusion, we report on two prognostic models, based on clinically relevant factors, which can be of help in predicting mortality risk in C. difficile infection, secondary to the antibiotic treatment of pneumonia. These models could be useful in preventive tailoring of individual therapy.

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.

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.

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)

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.

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.

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.

External validation of a multivariable claims-based rule for predicting in-hospital mortality and 30-day post-pulmonary embolism complications

Directory of Open Access Journals (Sweden)

Craig I. Coleman

2016-10-01

Full Text Available Abstract Background Low-risk pulmonary embolism (PE patients may be candidates for outpatient treatment or abbreviated hospital stay. There is a need for a claims-based prediction rule that payers/hospitals can use to risk stratify PE patients. We sought to validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT prediction rule for in-hospital and 30-day outcomes. Methods We used the Optum Research Database from 1/2008-3/2015 and included adults hospitalized for PE (415.1x in the primary position or secondary position when accompanied by a primary code for a PE complication and having continuous medical and prescription coverage for ≥6-months prior and 3-months post-inclusion or until death. In-hospital and 30-day mortality and 30-day complications (recurrent venous thromboembolism, rehospitalization or death were assessed and prognostic accuracies of IMPACT with 95 % confidence intervals (CIs were calculated. Results In total, 47,531 PE patients were included. In-hospital and 30-day mortality occurred in 7.9 and 9.4 % of patients and 20.8 % experienced any complication within 30-days. Of the 19.5 % of patients classified as low-risk by IMPACT, 2.0 % died in-hospital, resulting in a sensitivity and specificity of 95.2 % (95 % CI, 94.4–95.8 and 20.7 % (95 % CI, 20.4–21.1. Only 1 additional low-risk patient died within 30-days of admission and 12.2 % experienced a complication, translating into a sensitivity and specificity of 95.9 % (95 % CI, 95.3–96.5 and 21.1 % (95 % CI, 20.7–21.5 for mortality and 88.5 % (95 % CI, 87.9–89.2 and 21.6 % (95 % CI, 21.2–22.0 for any complication. Conclusion IMPACT had acceptable sensitivity for predicting in-hospital and 30-day mortality or complications and may be valuable for retrospective risk stratification of PE patients.

External validation of a multivariable claims-based rule for predicting in-hospital mortality and 30-day post-pulmonary embolism complications.

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Coleman, Craig I; Peacock, W Frank; Fermann, Gregory J; Crivera, Concetta; Weeda, Erin R; Hull, Michael; DuCharme, Mary; Becker, Laura; Schein, Jeff R

2016-10-22

Low-risk pulmonary embolism (PE) patients may be candidates for outpatient treatment or abbreviated hospital stay. There is a need for a claims-based prediction rule that payers/hospitals can use to risk stratify PE patients. We sought to validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule for in-hospital and 30-day outcomes. We used the Optum Research Database from 1/2008-3/2015 and included adults hospitalized for PE (415.1x in the primary position or secondary position when accompanied by a primary code for a PE complication) and having continuous medical and prescription coverage for ≥6-months prior and 3-months post-inclusion or until death. In-hospital and 30-day mortality and 30-day complications (recurrent venous thromboembolism, rehospitalization or death) were assessed and prognostic accuracies of IMPACT with 95 % confidence intervals (CIs) were calculated. In total, 47,531 PE patients were included. In-hospital and 30-day mortality occurred in 7.9 and 9.4 % of patients and 20.8 % experienced any complication within 30-days. Of the 19.5 % of patients classified as low-risk by IMPACT, 2.0 % died in-hospital, resulting in a sensitivity and specificity of 95.2 % (95 % CI, 94.4-95.8) and 20.7 % (95 % CI, 20.4-21.1). Only 1 additional low-risk patient died within 30-days of admission and 12.2 % experienced a complication, translating into a sensitivity and specificity of 95.9 % (95 % CI, 95.3-96.5) and 21.1 % (95 % CI, 20.7-21.5) for mortality and 88.5 % (95 % CI, 87.9-89.2) and 21.6 % (95 % CI, 21.2-22.0) for any complication. IMPACT had acceptable sensitivity for predicting in-hospital and 30-day mortality or complications and may be valuable for retrospective risk stratification of PE patients.

Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

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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.

Appetite predicts mortality in free-living older adults in association with dietary diversity. A NAHSIT cohort study.

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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.

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

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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

The interaction between individualism and wellbeing in predicting mortality: Survey of Health Ageing and Retirement in Europe.

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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.

Chronic disease associated with long-term concentrations of nitrogen dioxide

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Abbey, D.E.; Colome, S.D.; Mills, P.K.; Burchette, R.; Beeson, W.L.; Tian, Y. (Loma Linda Univ., CA (United States))

1993-04-01

A prospective epidemiologic cohort study of 6,000 residentially stable and non-smoking Seventh-day Adventists (SDA) in California was conducted to evaluate long-term cumulative levels of ambient nitrogen dioxide (NO2) in association with several chronic diseases. These diseases included respiratory symptoms, cancer, myocardial infarction (MI), and all natural causes mortality. Cumulative ambient concentrations of NO2 were estimated for each study subject using monthly interpolations from fixed site monitoring stations and applying these estimates to the monthly residence and work place zip code histories of study participants. In addition, a personal NO2 exposure study on a randomly selected sample of 650 people in southern California was conducted to predict total personal NO2 exposure using household and lifestyle characteristics and ambient NO2 concentrations. It was found that good predictability could be obtained (correlation coefficient between predicted and observed values = 0.79) from a model predicting personal NO2. The resulting regression equations from the personal NO2 exposure study were applied to the epidemiologic study cohort to adjust ambient concentrations of NO2.

To live and die in L.A. County: neighborhood economic and social context and premature age-specific mortality rates among Latinos.

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Bjornstrom, Eileen

2011-01-01

This ecological study compares the utility of neighborhood economic, social, and co-ethnic concentration characteristics in explaining mortality among Latinos aged 25-64 due to all causes and heart disease in Los Angeles County from 2000 to 2004. Results indicate that local economic well-being and social resources are beneficial for both outcomes to varying degrees. Economic well-being is the strongest predictor of all-cause mortality rates among Latinos aged 25-64 and was the only characteristic that significantly predicted heart disease mortality among those aged 45-64. Among social resources, results indicate collective efficacy is comparatively more important for mortality in younger adults. Social interaction was associated with lower mortality but the effect was not significant for any outcome. Co-ethnic concentration was consistently associated with increased mortality, but only achieved significance for all-cause mortality in younger adults. This effect was mediated by neighborhood income. Though social resources appear to be beneficial to a lesser extent, results suggest policy should first aim to address income disparities across local communities. Copyright © 2010 Elsevier Ltd. All rights reserved.

Neighbourhood Characteristics and Long-Term Air Pollution Levels Modify the Association between the Short-Term Nitrogen Dioxide Concentrations and All-Cause Mortality in Paris.

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Séverine Deguen

Full Text Available 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], p<0.001. Among these deprived census blocks, excess risk was even higher where long-term average NO2 concentrations were above 55.8 μg/m3 (the top tercile of distribution: ER=4.84% (95%CI=[1.56;8.24], p for interaction=0.02.Our results show that people living in census blocks characterized by low socioeconomic status are more vulnerable to air pollution 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.

The optimal definition of contrast-induced acute kidney injury for prediction of inpatient mortality in patients undergoing percutaneous coronary interventions.

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Parsh, Jessica; Seth, Milan; Briguori, Carlo; Grossman, Paul; Solomon, Richard; Gurm, Hitinder S

2016-05-01

It is unknown which definition of contrast-induced acute kidney injury (CI-AKI) in the setting of percutaneous coronary interventions is best associated with inpatient mortality and whether this association is stable across patients with various preprocedural serum creatinine (SCr) values. We applied logistic regression models to multiple CI-AKI definitions used by the Kidney Disease Improving Global Outcomes guidelines and previously published studies to examine the impact of preprocedural SCr on a candidate definition's correlation with the adverse outcome of inpatient mortality. We used likelihood ratio tests to examine candidate definitions and identify those where association with inpatient mortality remained constant regardless of preprocedural SCr. These definitions were assessed for specificity, sensitivity, and positive and negative predictive values to identify an optimal definition. Our study cohort included 119,554 patients who underwent percutaneous coronary intervention in Michigan between 2010 and 2014. Most commonly used definitions were not associated with inpatient mortality in a constant fashion across various preprocedural SCr values. Of the 266 candidate definitions examined, 16 definition's association with inpatient mortality was not significantly altered by preprocedural SCr. Contrast-induced acute kidney injury defined as an absolute increase of SCr ≥0.3 mg/dL and a relative SCr increase ≥50% was selected as the optimal candidate using Perkins and Shisterman decision theoretic optimality criteria and was highly predictive of and specific for inpatient mortality. We identified the optimal definition for CI-AKI to be an absolute increase in SCr ≥0.3 mg/dL and a relative SCr increase ≥50%. Further work is needed to validate this definition in independent studies and to establish its utility for clinical trials and quality improvement efforts. Copyright © 2016 Elsevier Inc. All rights reserved.

Air pollution and associated human mortality: the role of air pollutant emissions, climate change and methane concentration increases from the preindustrial period to present

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Y. Fang

2013-02-01

Full Text Available Increases in surface ozone (O₃ and fine particulate matter (≤2.5 μm aerodynamic diameter, PM_2.5 are associated with excess premature human mortalities. We estimate changes in surface O₃ and PM_2.5 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 PM_2.5 from the epidemiology literature. We find global mean surface PM_2.5 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 PM_2.5 (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 PM_2.5 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

Prediction of hydrogen concentration in nuclear power plant containment under severe accidents using cascaded fuzzy neural networks

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Choi, Geon Pil; Kim, Dong Yeong; Yoo, Kwae Hwan; Na, Man Gyun, E-mail: magyna@chosun.ac.kr

2016-04-15

Highlights: • We present a hydrogen-concentration prediction method in an NPP containment. • The cascaded fuzzy neural network (CFNN) is used in this prediction model. • The CFNN model is much better than the existing FNN model. • This prediction can help prevent severe accidents in NPP due to hydrogen explosion. - Abstract: Recently, severe accidents in nuclear power plants (NPPs) have attracted worldwide interest since the Fukushima accident. If the hydrogen concentration in an NPP containment is increased above 4% in atmospheric pressure, hydrogen combustion will likely occur. Therefore, the hydrogen concentration must be kept below 4%. This study presents the prediction of hydrogen concentration using cascaded fuzzy neural network (CFNN). The CFNN model repeatedly applies FNN modules that are serially connected. The CFNN model was developed using data on severe accidents in NPPs. The data were obtained by numerically simulating the accident scenarios using the MAAP4 code for optimized power reactor 1000 (OPR1000) because real severe accident data cannot be obtained from actual NPP accidents. The root-mean-square error level predicted by the CFNN model is below approximately 5%. It was confirmed that the CFNN model could accurately predict the hydrogen concentration in the containment. If NPP operators can predict the hydrogen concentration in the containment using the CFNN model, this prediction can assist them in preventing a hydrogen explosion.

Malnutrition: a highly predictive risk factor of short-term mortality in elderly presenting to the emergency department.

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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.

Deciphering infant mortality

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Berrut, Sylvie; Pouillard, Violette; Richmond, Peter; Roehner, Bertrand M.

2016-12-01

This paper is about infant mortality. In line with reliability theory, "infant" refers to the time interval following birth during which the mortality (or failure) rate decreases. This definition provides a systems science perspective in which birth constitutes a sudden transition falling within the field of application of the Transient Shock (TS) conjecture put forward in Richmond and Roehner (2016c). This conjecture provides predictions about the timing and shape of the death rate peak. It says that there will be a death rate spike whenever external conditions change abruptly and drastically and also predicts that after a steep rise there will be a much longer hyperbolic relaxation process. These predictions can be tested by considering living organisms for which the transient shock occurs several days after birth. Thus, for fish there are three stages: egg, yolk-sac and young adult phases. The TS conjecture predicts a mortality spike at the end of the yolk-sac phase and this timing is indeed confirmed by observation. Secondly, the hyperbolic nature of the relaxation process can be tested using very accurate Swiss statistics for postnatal death rates spanning the period from one hour immediately after birth through to age 10 years. It turns out that since the 19th century despite a significant and large reduction in infant mortality, the shape of the age-specific death rate has remained basically unchanged. Moreover the hyperbolic pattern observed for humans is also found for small primates as recorded in the archives of zoological gardens. Our overall objective is to identify a series of cases which start from simple systems and move step by step to more complex organisms. The cases discussed here we believe represent initial landmarks in this quest.

Does mortality risk of cigarette smoking depend on serum concentrations of persistent organic pollutants? Prospective investigation of the vasculature in Uppsala seniors (PIVUS study.

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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.

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

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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.

Metabonomics analysis of plasma reveals the lactate to cholesterol ratio as an independent prognostic factor of short-term mortality in acute heart failure.

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Franck Desmoulin

Full Text Available OBJECTIVE: Mortality in heart failure (AHF remains high, especially during the first days of hospitalization. New prognostic biomarkers may help to optimize treatment. The aim of the study was to determine metabolites that have a high prognostic value. METHODS: We conducted a prospective study on a training cohort of AHF patients (n = 126 admitted in the cardiac intensive care unit and assessed survival at 30 days. Venous plasmas collected at admission were used for (1H NMR--based metabonomics analysis. Differences between plasma metabolite profiles allow determination of discriminating metabolites. A cohort of AHF patients was subsequently constituted (n = 74 to validate the findings. RESULTS: Lactate and cholesterol were the major discriminating metabolites predicting 30-day mortality. Mortality was increased in patients with high lactate and low total cholesterol concentrations at admission. Accuracies of lactate, cholesterol concentration and lactate to cholesterol (Lact/Chol ratio to predict 30-day mortality were evaluated using ROC analysis. The Lact/Chol ratio provided the best accuracy with an AUC of 0.82 (P < 0.0001. The acute physiology and chronic health evaluation (APACHE II scoring system provided an AUC of 0.76 for predicting 30-day mortality. APACHE II score, Cardiogenic shock (CS state and Lact/Chol ratio ≥ 0.4 (cutoff value with 82% sensitivity and 64% specificity were significant independent predictors of 30-day mortality with hazard ratios (HR of 1.11, 4.77 and 3.59, respectively. In CS patients, the HR of 30-day mortality risk for plasma Lact/Chol ratio ≥ 0.4 was 3.26 compared to a Lact/Chol ratio of < 0.4 (P = 0.018. The predictive power of the Lact/Chol ratio for 30-day mortality outcome was confirmed with the independent validation cohort. CONCLUSION: This study identifies the plasma Lact/Chol ratio as a useful objective and simple parameter to evaluate short term prognostic and could be integrated into quantitative

Comparison of artificial neural network and logistic regression models for predicting in-hospital mortality after primary liver cancer surgery.

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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.

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

Prediction of Coal Face Gas Concentration by Multi-Scale Selective Ensemble Hybrid Modeling

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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.

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....

Seven-day mortality can be predicted in medical patients by blood pressure, age, respiratory rate, loss of independence, and peripheral oxygen saturation (the PARIS score: a prospective cohort study with external validation.

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Mikkel Brabrand

Full Text Available Most existing risk stratification systems predicting mortality in emergency departments or admission units are complex in clinical use or have not been validated to a level where use is considered appropriate. We aimed to develop and validate a simple system that predicts seven-day mortality of acutely admitted medical patients using routinely collected variables obtained within the first minutes after arrival.This observational prospective cohort study used three independent cohorts at the medical admission units at a regional teaching hospital and a tertiary university hospital and included all adult (≥ 15 years patients. Multivariable logistic regression analysis was used to identify the clinical variables that best predicted the endpoint. From this, we developed a simplified model that can be calculated without specialized tools or loss of predictive ability. The outcome was defined as seven-day all-cause mortality. 76 patients (2.5% met the endpoint in the development cohort, 57 (2.0% in the first validation cohort, and 111 (4.3% in the second. Systolic blood Pressure, Age, Respiratory rate, loss of Independence, and peripheral oxygen Saturation were associated with the endpoint (full model. Based on this, we developed a simple score (range 0-5, ie, the PARIS score, by dichotomizing the variables. The ability to identify patients at increased risk (discriminatory power and calibration was excellent for all three cohorts using both models. For patients with a PARIS score ≥ 3, sensitivity was 62.5-74.0%, specificity 85.9-91.1%, positive predictive value 11.2-17.5%, and negative predictive value 98.3-99.3%. Patients with a score ≤ 1 had a low mortality (≤ 1%; with 2, intermediate mortality (2-5%; and ≥ 3, high mortality (≥ 10%.Seven-day mortality can be predicted upon admission with high sensitivity and specificity and excellent negative predictive values.

Comparison of severity of illness scoring systems in the prediction of hospital mortality in severe sepsis and septic shock

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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.

Validation of the MARS (Medical Admission Risk System): A combined physiological and laboratory risk prediction tool for 5- to 7-day in-hospital mortality.

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Ohman, Malin Charlotta; Atkins, Tara E Holm; Cooksley, Tim; Brabrand, Mikkel

2018-03-10

The MARS (Medical Admission Risk System) uses 11 physiological and laboratory data and had promising results in its derivation study for predicting 5 and 7 day mortality. To perform an external independent validation of the MARS score. An unplanned secondary cohort study. Patients admitted to the medical admission unit (MAU) at The Hospital of South West Jutland were included from 2 October 2008 until 19 February 2009 and 23 February 2010 until 26 May 2010 were analysed. Validation of the MARS score using 5 and 7 day mortality was the primary endpoint. 5858 patients were included in the study. 2923 (49.9%) patients were women with a median age of 65 years (15-107). The MARS score had an AUROC of 0.858 (95% CI: 0.831-0.884) for 5-day mortality and 0.844 (0.818-0.870) for 7 day mortality with poor calibration for both outcomes. The MARS score had excellent discriminatory power but poor calibration in predicting both 5 and 7-day mortality. The development of accurate combination physiological/laboratory data risk scores has the potential to improve the recognition of at risk patients.

Global concentration additivity and prediction of mixture toxicities, taking nitrobenzene derivatives as an example.

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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.

The predictive value of current haemoglobin levels for incident tuberculosis and/or mortality during long-term antiretroviral therapy in South Africa: a cohort study.

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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

Increased circulating D-lactate levels predict risk of mortality after hemorrhage and surgical trauma in baboons.

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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.

Predicting arsenic concentrations in groundwater of San Luis Valley, Colorado: implications for individual-level lifetime exposure assessment.

Science.gov (United States)

James, Katherine A; Meliker, Jaymie R; Buttenfield, Barbara E; Byers, Tim; Zerbe, Gary O; Hokanson, John E; Marshall, Julie A

2014-08-01

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83-0.92 for samples collected from the same well 15-25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.

Development and evaluation of a regression-based model to predict cesium concentration ratios for freshwater fish

International Nuclear Information System (INIS)

Pinder, John E.; Rowan, David J.; Rasmussen, Joseph B.; Smith, Jim T.; Hinton, Thomas G.; Whicker, F.W.

2014-01-01

Data from published studies and World Wide Web sources were combined to produce and test a regression model to predict Cs concentration ratios for freshwater fish species. The accuracies of predicted concentration ratios, which were computed using 1) species trophic levels obtained from random resampling of known food items and 2) K concentrations in the water for 207 fish from 44 species and 43 locations, were tested against independent observations of ratios for 57 fish from 17 species from 25 locations. Accuracy was assessed as the percent of observed to predicted ratios within factors of 2 or 3. Conservatism, expressed as the lack of under prediction, was assessed as the percent of observed to predicted ratios that were less than 2 or less than 3. The model's median observed to predicted ratio was 1.26, which was not significantly different from 1, and 50% of the ratios were between 0.73 and 1.85. The percentages of ratios within factors of 2 or 3 were 67 and 82%, respectively. The percentages of ratios that were <2 or <3 were 79 and 88%, respectively. An example for Perca fluviatilis demonstrated that increased prediction accuracy could be obtained when more detailed knowledge of diet was available to estimate trophic level. - Highlights: • We developed a model to predict Cs concentration ratios for freshwater fish species. • The model uses only two variables to predict a species CR for any location. • One variable is the K concentration in the freshwater. • The other is a species mean trophic level measure easily obtained from (fishbase.org). • The median observed to predicted ratio for 57 independent test cases was 1.26

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.

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

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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

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

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

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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.

[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)].

Science.gov (United States)

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

2015-07-01

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 gastrointestinal bleeding in a hospital of Lima, Peru. This was a longitudinal, retrospective, analytical validation study, with data from patients with a clinical and endoscopic diagnosis of upper gastrointestinal bleeding treated at the Gastrointestinal Hemorrhage Unit of the Hospital Nacional Edgardo Rebagliati Martins between June 2012 and December 2013. We calculated the area under the curve for the receiver operating characteristic of the Glasgow-Blatchford Scoring System to predict mortality with a 95% confidence interval. A total of 339 records were analyzed. 57.5% were male and the mean age (standard deviation) was 67.0 (15.7) years. The median of the Glasgow-Blatchford Scoring System obtained in the population was 12. The ROC analysis for death gave an area under the curve of 0.59 (95% CI 0.5-0.7). Stratifying by type of upper gastrointestinal bleeding resulted in an area under the curve of 0.66 (95% CI 0.53-0.78) for non-variceal type. In this population, the Glasgow-Blatchford Scoring System has no diagnostic validity for predicting mortality.

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

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Alessandra Cassana

2015-08-01

Full Text Available 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 gastrointestinal bleeding in a hospital of Lima, Peru. Methods: This was a longitudinal, retrospective, analytical validation study, with data from patients with a clinical and endoscopic diagnosis of upper gastrointestinal bleeding treated at the Gastrointestinal Hemorrhage Unit of the Hospital Nacional Edgardo Rebagliati Martins between June 2012 and December 2013. We calculated the area under the curve for the receiver operating characteristic of the Glasgow-Blatchford Scoring System to predict mortality with a 95% confidence interval. Results: A total of 339 records were analyzed. 57.5% were male and the mean age (standard deviation was 67.0 (15.7 years. The median of the Glasgow-Blatchford Scoring System obtained in the population was 12. The ROC analysis for death gave an area under the curve of 0.59 (95% CI 0.5-0.7. Stratifying by type of upper gastrointestinal bleeding resulted in an area under the curve of 0.66 (95% CI 0.53-0.78 for non-variceal type. Conclusions: In this population, the Glasgow-Blatchford Scoring System has no diagnostic validity for predicting mortality.

Predicting short-term mortality in advanced decompensated heart failure - role of the updated acute decompensated heart failure/N-terminal pro-B-type natriuretic Peptide risk score.

Science.gov (United States)

Scrutinio, Domenico; Ammirati, Enrico; Passantino, Andrea; Guida, Pietro; D'Angelo, Luciana; Oliva, Fabrizio; Ciccone, Marco Matteo; Iacoviello, Massimo; Dentamaro, Ilaria; Santoro, Daniela; Lagioia, Rocco; Sarzi Braga, Simona; Guzzetti, Daniela; Frigerio, Maria

2015-01-01

The first few months after admission are the most vulnerable period in patients with acute decompensated heart failure (ADHF). We assessed the association of the updated ADHF/N-terminal pro-B-type natriuretic peptide (NT-proBNP) risk score with 90-day and in-hospital mortality in 701 patients admitted with advanced ADHF, defined as severe symptoms of worsening HF, severely depressed left ventricular ejection fraction, and the need for i.v. diuretic and/or inotropic drugs. A total of 15.7% of the patients died within 90 days of admission and 5.2% underwent ventricular assist device (VAD) implantation or urgent heart transplantation (UHT). The C-statistic of the ADHF/NT-proBNP risk score for 90-day mortality was 0.810 (95% CI: 0.769-0.852). Predicted and observed mortality rates were in close agreement. When the composite outcome of death/VAD/UHT at 90 days was considered, the C-statistic decreased to 0.741. During hospitalization, 7.6% of the patients died. The C-statistic for in-hospital mortality was 0.815 (95% CI: 0.761-0.868) and Hosmer-Lemeshow χ(2)=3.71 (P=0.716). The updated ADHF/NT-proBNP risk score outperformed the Acute Decompensated Heart Failure National Registry, the Organized Program to Initiate Lifesaving Treatment in Patients Hospitalized for Heart Failure, and the American Heart Association Get with the Guidelines Program predictive models. Updated ADHF/NT-proBNP risk score is a valuable tool for predicting short-term mortality in severe ADHF, outperforming existing inpatient predictive models.

Mortality in severe trauma patients attended by emergency services in Navarre, Spain: validation of a new prediction model and comparison with the Revised Injury Severity Classification Score II.

Science.gov (United States)

Ali Ali, Bismil; Lefering, Rolf; Fortún Moral, Mariano; Belzunegui Otano, Tomás

2018-01-01

To validate the Mortality Prediction Model of Navarre (MPMN) to predict death after severe trauma and compare it to the Revised Injury Severity Classification Score II (RISCII). Retrospective analysis of a cohort of severe trauma patients (New Injury Severity Score >15) who were attended by emergency services in the Spanish autonomous community of Navarre between 2013 and 2015. The outcome variable was 30-day all-cause mortality. Risk was calculated with the MPMN and the RISCII. The performance of each model was assessed with the area under the receiver operating characteristic (ROC) curve and precision with respect to observed mortality. Calibration was assessed with the Hosmer-Lemeshow test. We included 516 patients. The mean (SD) age was 56 (23) years, and 363 (70%) were males. Ninety patients (17.4%) died within 30 days. The 30-day mortality rates predicted by the MPMN and RISCII were 16.4% and 15.4%, respectively. The areas under the ROC curves were 0.925 (95% CI, 0.902-0.952) for the MPMN and 0.941 (95% CI, 0.921-0.962) for the RISCII (P=0.269, DeLong test). Calibration statistics were 13.6 (P=.09) for the MPMN and 8.9 (P=.35) for the RISCII. Both the MPMN and the RISCII show good ability to discriminate risk and predict 30-day all-cause mortality in severe trauma patients.

Increased Concentrations of Insulin-Like Growth Factor Binding Protein (IGFBP-2, IGFBP-3, and IGFBP-4 Are Associated With Fetal Mortality in Pregnant Cows

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Kirsten Mense

2018-06-01

Full Text Available Insulin-like growth factors (IGFs play a critical role in fetal growth, and components of the IGF system have been associated with fetal growth restriction in women. In human pregnancy, the proteolytic cleavage of insulin-like growth factor binding proteins (IGFBPs, particularly IGFBP-4, releases free IGF for respective action at the tissue level. The aim of the present study was to determine IGFBP-2, IGFBP-3, and IGFBP-4 concentrations by Western ligand blotting during pregnancy until day 100 in cows and to compare these concentrations with those of non-pregnant cows and cows undergoing embryonic/fetal mortality. Therefore, two study trials (I and II and an in vitro study were conducted. In study I, 43 cows were not pregnant, 34 cows were pregnant, and 4 cows were undergoing fm. In study II, 500 cows were examined, and 7 cases of pregnancy loss between days 24–27 and 34–37 after artificial insemination (AI, late embryonic mortality; em and 8 cases of pregnancy loss between days 34–37 and 54–57 after AI (late embryonic mortality and early fetal mortality; em/fm were defined from the analyses of 30 pregnant and 20 non-pregnant cows randomly selected for insulin-like growth factor 1 and IGFBP analyses. In vitro serum from pregnant (n = 3 and non-pregnant (n = 3 cows spiked after incubation with recombinant human (rh IGFBP-4 for 24 h, and IGFBP-4 levels were analyzed before and after incubation to detect proteolytic degradation. The IGFBP-2, -3, and -4 concentrations did not decline during early pregnancy in cows, while IGFBP-4 concentrations were comparable between pregnant and non-pregnant cows, irrespective of low proteolytic activity, which was also demonstrated in cows. Interestingly, cows with em or fm showed distinct IGFBP patterns. The IGFBP-2 and -3 concentrations were higher (P < 0.05 in cows with fm compared to pregnant. The IGFBP-4 levels were significantly higher in cows developing fm. Thus, distinct differences

Predicting the activity coefficients of free-solvent for concentrated globular protein solutions using independently determined physical parameters.

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Devin W McBride

Full Text Available The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.

Among nonagenarians, congruence between self-rated and proxy-rated health was low but both predicted mortality.

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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.

Poor performances of EuroSCORE and CARE score for prediction of perioperative mortality in octogenarians undergoing aortic valve replacement for aortic stenosis.

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Chhor, Vibol; Merceron, Sybille; Ricome, Sylvie; Baron, Gabriel; Daoud, Omar; Dilly, Marie-Pierre; Aubier, Benjamin; Provenchere, Sophie; Philip, Ivan

2010-08-01

Although results of cardiac surgery are improving, octogenarians have a higher procedure-related mortality and more complications with increased length of stay in ICU. Consequently, careful evaluation of perioperative risk seems necessary. The aims of our study were to assess and compare the performances of EuroSCORE and CARE score in the prediction of perioperative mortality among octogenarians undergoing aortic valve replacement for aortic stenosis and to compare these predictive performances with those obtained in younger patients. This retrospective study included all consecutive patients undergoing cardiac surgery in our institution between November 2005 and December 2007. For each patient, risk assessment for mortality was performed using logistic EuroSCORE, additive EuroSCORE and CARE score. The main outcome measure was early postoperative mortality. Predictive performances of these scores were assessed by calibration and discrimination using goodness-of-fit test and area under the receiver operating characteristic curve, respectively. During this 2-year period, we studied 2117 patients, among whom 134/211 octogenarians and 335/1906 nonoctogenarians underwent an aortic valve replacement for aortic stenosis. When considering patients with aortic stenosis, discrimination was poor in octogenarians and the difference from nonoctogenarians was significant for each score (0.58, 0.59 and 0.56 vs. 0.82, 0.81 and 0.77 for additive EuroSCORE, logistic EuroSCORE and CARE score in octogenarians and nonoctogenarians, respectively, P performances of these scores are poor in octogenarians undergoing cardiac surgery, especially aortic valve replacement. Risk assessment and therapeutic decisions in octogenarians should not be made with these scoring systems alone.

The Relationship between Serum Hemoglobin and Creatinine Levels and Intra-Hospital Mortality and Morbidity in Acute Myocardial Infarction

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Afsoon Fazlinezhad

2014-09-01

Full Text Available Background: Studies have shown that Glomerular Filtration Rate (GFR and Hemoglobin (Hb concentrations are two predictive values for ST-elevation Myocardial Infarction (MI mortality.. Objectives: This study aimed to investigate the relationship between GFR and Hb concentrations and intra-hospital mortality and electrocardiographic (ECG and echocardiographic abnormalities in ST-elevation MI patients admitted to a highly equipped hospital in Mashhad. The results will help define some factors to manage these patients more efficiently.. Patients and Methods: This descriptive study aimed to assess the relationship between Hb and GFR concentrations and mortality and morbidity among 294 randomly selected patients with ST-elevation MI. Echocardiography, ECG, and routine laboratory tests, including Hb and creatinine, were performed for all the patients. Then, the data were entered into the SPSS statistical software, version 16 and were analyzed using chi-square, t-test, and ANOVA. P < 0.05 was considered as statistically significant.. Results: Intra-hospital mortality rate was 10.5%. Besides, the results showed higher levels of serum blood sugar (P < 0.001, higher levels of creatinine (P < 0.001, lower levels of GFR (P < 0.001, lower ejection fraction (P < 0.001, higher grades of left ventricular diastolic dysfunction (P = 0.002, and lower mean Hb concentration (P = 0.022 in the dead compared to the alive cases. Besides, the patients with mechanical complications had lower Hb levels (P = 0.008. The results showed no significant relationship between creatinine level and mechanical and electrical complications (P = 0.430 and P = 0.095, respectively. However, ejection fraction was significantly associated with GFR (P = 0.016.. Conclusions: According to the results, low levels of Hb and GFR could predict mortality caused by ST-elevation MI and ECG abnormalities could notify intra-hospital death. Moreover, lower Hb levels were associated with mechanical

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.)

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

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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.)

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

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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.

Cardiopulmonary mortality and COPD attributed to ambient ozone.

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Khaniabadi, Yusef Omidi; Hopke, Philip K; Goudarzi, Gholamreza; Daryanoosh, Seyed Mohammad; Jourvand, Mehdi; Basiri, Hassan

2017-01-01

Tropospheric ozone is the second most important atmospheric pollutant after particulate matter with respect to its impact on human health and is increasing of its concentrations globally. The main objective of this study was to assess of health effects attributable to ground-level ozone (O 3 ) in Kermanshah, Iran using one-hour O 3 concentrations measured between March 2014 and March 2015. The AirQ program was applied for estimation of the numbers of cardiovascular mortality (CM), respiratory mortality (RM), and hospital admissions for chronic obstructive pulmonary disease (HA-COPD) using relative risk (RR) and baseline incidence (BI) as defined by the World Health Organization (WHO). The largest percentage of person-days for different O 3 concentrations was in the concentration range of 30-39µg/m 3 . The health modeling results suggested that ~2% (95% CI: 0-2.9%) of cardiovascular mortality, 5.9% (95% CI: 2.3-9.4) of respiratory mortality, and 4.1% (CI: 2.5-6.1%) of the HA-COPD were attributed to O 3 concentrations higher than 10µg/m 3 . For each 10µg/m 3 increase in O 3 concentration, the risk of cardiovascular mortality, respiratory mortality, and HA-COPD increased by 0.40%, 1.25%, and 0.86%, respectively. Furthermore, 88.8% of health effects occurred on days with O 3 level less than 100µg/m 3 . Thus, action is needed to reduce the emissions of O 3 precursors especially transport and energy production in Kermanshah. Copyright © 2016. Published by Elsevier Inc.

External validation and clinical utility of a prediction model for 6-month mortality in patients undergoing hemodialysis for end-stage kidney disease.

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Forzley, Brian; Er, Lee; Chiu, Helen Hl; Djurdjev, Ognjenka; Martinusen, Dan; Carson, Rachel C; Hargrove, Gaylene; Levin, Adeera; Karim, Mohamud

2018-02-01

End-stage kidney disease is associated with poor prognosis. Health care professionals must be prepared to address end-of-life issues and identify those at high risk for dying. A 6-month mortality prediction model for patients on dialysis derived in the United States is used but has not been externally validated. We aimed to assess the external validity and clinical utility in an independent cohort in Canada. We examined the performance of the published 6-month mortality prediction model, using discrimination, calibration, and decision curve analyses. Data were derived from a cohort of 374 prevalent dialysis patients in two regions of British Columbia, Canada, which included serum albumin, age, peripheral vascular disease, dementia, and answers to the "the surprise question" ("Would I be surprised if this patient died within the next year?"). The observed mortality in the validation cohort was 11.5% at 6 months. The prediction model had reasonable discrimination (c-stat = 0.70) but poor calibration (calibration-in-the-large = -0.53 (95% confidence interval: -0.88, -0.18); calibration slope = 0.57 (95% confidence interval: 0.31, 0.83)) in our data. Decision curve analysis showed the model only has added value in guiding clinical decision in a small range of threshold probabilities: 8%-20%. Despite reasonable discrimination, the prediction model has poor calibration in this external study cohort; thus, it may have limited clinical utility in settings outside of where it was derived. Decision curve analysis clarifies limitations in clinical utility not apparent by receiver operating characteristic curve analysis. This study highlights the importance of external validation of prediction models prior to routine use in clinical practice.

Identification of enhanced cytokine generation following sepsis. Dream of magic bullet for mortality prediction and therapeutic evaluation

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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.

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)

Predicting mortality among older adults hospitalized for community-acquired pneumonia: an enhanced confusion, urea, respiratory rate and blood pressure score compared with pneumonia severity index.

Science.gov (United States)

Abisheganaden, John; Ding, Yew Yoong; Chong, Wai-Fung; Heng, Bee-Hoon; Lim, Tow Keang

2012-08-01

Pneumonia Severity Index (PSI) predicts mortality better than Confusion, Urea >7 mmol/L, Respiratory rate >30/min, low Blood pressure: diastolic blood pressure blood pressure 65 years (CURB-65) for community-acquired pneumonia (CAP) but is more cumbersome. The objective was to determine whether CURB enhanced with a small number of additional variables can predict mortality with at least the same accuracy as PSI. Retrospective review of medical records and administrative data of adults aged 55 years or older hospitalized for CAP over 1 year from three hospitals. For 1052 hospital admissions of unique patients, 30-day mortality was 17.2%. PSI class and CURB-65 predicted 30-day mortality with area under curve (AUC) of 0.77 (95% confidence interval (CI): 0.73-0.80) and 0.70 (95% CI: 0.66-0.74) respectively. When age and three co-morbid conditions (metastatic cancer, solid tumours without metastases and stroke) were added to CURB, the AUC improved to 0.80 (95% CI: 0.77-0.83). Bootstrap validation obtained an AUC estimate of 0.78, indicating negligible overfitting of the model. Based on this model, a clinical score (enhanced CURB score) was developed that had possible values from 5 to 25. Its AUC was 0.79 (95% CI: 0.76-0.83) and remained similar to that of PSI class. An enhanced CURB score predicted 30-day mortality with at least the same accuracy as PSI class did among older adults hospitalized for CAP. External validation of this score in other populations is the next step to determine whether it can be used more widely. © 2012 The Authors. Respirology © 2012 Asian Pacific Society of Respirology.

The utility of liver function tests for mortality prediction within one year in primary care using the algorithm for liver function investigations (ALFI.

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David J McLernon

Full Text Available BACKGROUND: Although liver function tests (LFTs are routinely measured in primary care, raised levels in patients with no obvious liver disease may trigger a range of subsequent expensive and unnecessary management plans. The aim of this study was to develop and validate a prediction model to guide decision-making by general practitioners, which estimates risk of one year all-cause mortality in patients with no obvious liver disease. METHODS: In this population-based historical cohort study, biochemistry data from patients in Tayside, Scotland, with LFTs performed in primary care were record-linked to secondary care and prescription databases to ascertain baseline characteristics, and to mortality data. Using this derivation cohort a survival model was developed to predict mortality. The model was assessed for calibration, discrimination (using the C-statistic and performance, and validated using a separate cohort of Scottish primary care practices. RESULTS: From the derivation cohort (n = 95 977, 2.7% died within one year. Predictors of mortality included: age; male gender; social deprivation; history of cancer, renal disease, stroke, ischaemic heart disease or respiratory disease; statin use; and LFTs (albumin, transaminase, alkaline phosphatase, bilirubin, and gamma-glutamyltransferase. The C-statistic for the final model was 0.82 (95% CI 0.80-0.84, and was similar in the validation cohort (n = 11 653 0.86 (0.79-0.90. As an example of performance, for a 10% predicted probability cut-off, sensitivity = 52.8%, specificity = 94.0%, PPV = 21.0%, NPV = 98.5%. For the model without LFTs the respective values were 43.8%, 92.8%, 15.6%, 98.1%. CONCLUSIONS: The Algorithm for Liver Function Investigations (ALFI is the first model to successfully estimate the probability of all-cause mortality in patients with no apparent liver disease having LFTs in primary care. While LFTs added to the model's discrimination and sensitivity, the

Spatial association between malaria pandemic and mortality

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B M Dansu

2007-12-01

Full Text Available Malaria pandemic (MP has been linked to a range of serious health problems including premature mortality. The main objective of this research is to quantify uncertainties about impacts of malaria on mortality. A multivariate spatial regression model was developed for estimation of the risk of mortality associated with malaria across Ogun State in Nigeria, West Africa. We characterize different local governments in the data and model the spatial structure of the mortality data in infants and pregnant women. A flexible Bayesian hierarchical model was considered for a space-time series of counts (mortality by constructing a likelihood-based version of a generalized Poisson regression model that combines methods for point-level misaligned data and change of support regression. A simple two-stage procedure for producing maps of predicted risk is described. Logistic regression modeling was used to determine an approximate risk on a larger scale, and geo-statistical ("Kriging" approaches were used to improve prediction at a local level. The results suggest improvement of risk prediction brought about in the second stage. The advantages and shortcomings of this approach highlight the need for further development of a better analytical methodology.

Prediction of ore fluid metal concentrations from solid solution concentrations in ore-stage calcite: Application to the Illinois-Kentucky and Central Tennessee Mississippi Valley-type districts

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Smith-Schmitz, Sarah E.; Appold, Martin S.

2018-03-01

Knowledge of the concentrations of Zn and Pb in Mississippi Valley-type (MVT) ore fluids is fundamental to understanding MVT deposit origin. Most previous attempts to quantify the concentrations of Zn and Pb in MVT ore fluids have focused on the analysis of fluid inclusions. However, these attempts have yielded ambiguous results due to possible contamination from secondary fluid inclusions, interferences from Zn and Pb in the host mineral matrix, and uncertainties about whether the measured Zn and Pb signals represent aqueous solute or accidental solid inclusions entrained within the fluid inclusions. The purpose of the present study, therefore, was to try to determine Zn and Pb concentrations in MVT ore fluids using an alternate method that avoids these ambiguities by calculating Zn and Pb concentrations in MVT ore fluids theoretically based on their solid solution concentrations in calcite. This method was applied to the Illinois-Kentucky and Central Tennessee districts, which both contain ore-stage calcite. Experimental partition coefficient (D) values from Rimstidt et al. (1998) and Tsusue and Holland (1966), and theoretical thermodynamic distribution coefficient (KD) values were employed in the present study. Ore fluid concentrations of Zn were likely most accurately predicted by Rimstidt et al. (1998) D values, based on their success in predicting known fluid inclusion concentrations of Mg and Mn, and likely also most accurately predicted ore fluid concentrations of Fe. All four of these elements have a divalent ionic radius smaller than that of Ca2+ and form carbonate minerals with the calcite structure. For both the Illinois-Kentucky and the Central Tennessee district, predicted ore fluid Zn and Fe concentrations were on the order of up to 10's of ppm. Ore fluid concentrations of Pb could only be predicted using Rimstidt et al. (1998) D values. However, these concentrations are unlikely to be reliable, as predicted ore fluid concentrations of Sr and Ba

Watershed regressions for pesticides (WARP) for predicting atrazine concentration in Corn Belt streams

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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.

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.

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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.

The ability of self-rated health to predict mortality among community-dwelling elderly individuals differs according to the specific cause of death: data from the NEDICES Cohort

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Fernández-Ruiz, Mario; Guerra-Vales, Juan M.; Trincado, Rocío; Fernández, Rebeca; Medrano, María José; Villarejo, Alberto; Benito-León, Julián; Bermejo-Pareja, Félix

2013-01-01

Background The biomedical and psychosocial mechanisms underlying the relationship between self-rated health (SRH) and mortality in elderly individuals remain unclear. Objective To assess the association between different measurements of subjective health (global, age-comparative, and time-comparative SRH) and cause-specific mortality. Methods Neurological Disorders in Central Spain (NEDICES) is a prospective population-based survey of the prevalence and incidence of major age-associated conditions. Data on demographic and health-related variables were collected from 5,278 subjects (≥65 years) at the baseline questionnaire. Thirteen-year mortality and cause of death were obtained from the National Death Registry. Adjusted hazard ratios (aHR) for SRH and all-cause and cause-specific mortality were estimated by Cox proportional hazard models. Results At baseline, 4,958 participants (93.9%) answered the SRH questionnaire. At the end of follow-up 2,468 (49.8%) participants had died (of whom 723 [29.2%] died from cardiovascular diseases, 609 [24.7%] from cancer, and 359 [14.5%] from respiratory diseases). Global SRH predicted independently all-cause mortality (aHR for “poor or very poor” vs. “very good” category: 1.39; 95% confidence interval [CI]: 1.15–1.69). Analysis of cause-specific mortality revealed that global SRH was an independent predictor for death due to respiratory diseases (aHR for “poor or very poor” vs. “very good” category: 2.61; 95% CI: 1.55–4.39), whereas age-comparative SRH exhibited a gradient effect on the risk of death due to stroke. Time-comparative SRH provided small additional predictive value. Conclusions The predictive ability of SRH for mortality largely differs according to the specific cause of death, with the strongest associations found for respiratory disease and stroke mortality. PMID:23615509

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.

Predicting redox-sensitive contaminant concentrations in groundwater using random forest classification

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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.

Individual-Level Concentrations of Fine Particulate Matter Chemical Components and Subclinical Atherosclerosis: A Cross-Sectional Analysis Based on 2 Advanced Exposure Prediction Models in the Multi-Ethnic Study of Atherosclerosis

Science.gov (United States)

Kim, Sun-Young; Sheppard, Lianne; Kaufman, Joel D.; Bergen, Silas; Szpiro, Adam A.; Larson, Timothy V.; Adar, Sara D.; Diez Roux, Ana V.; Polak, Joseph F.; Vedal, Sverre

2014-01-01

Long-term exposure to outdoor particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) has been associated with cardiovascular morbidity and mortality. The chemical composition of PM2.5 that may be most responsible for producing these associations has not been identified. We assessed cross-sectional associations between long-term concentrations of PM2.5 and 4 of its chemical components (sulfur, silicon, elemental carbon, and organic carbon (OC)) and subclinical atherosclerosis, measured as carotid intima-media thickness (CIMT) and coronary artery calcium, between 2000 and 2002 among 5,488 Multi-Ethnic Study of Atherosclerosis participants residing in 6 US metropolitan areas. Long-term concentrations of PM2.5 components at participants' homes were predicted using both city-specific spatiotemporal models and a national spatial model. The estimated differences in CIMT associated with interquartile-range increases in sulfur, silicon, and OC predictions from the spatiotemporal model were 0.022 mm (95% confidence interval (CI): 0.014, 0.031), 0.006 mm (95% CI: 0.000, 0.012), and 0.026 mm (95% CI: 0.019, 0.034), respectively. Findings were generally similar using the national spatial model predictions but were often sensitive to adjustment for city. We did not find strong evidence of associations with coronary artery calcium. Long-term concentrations of sulfur and OC, and possibly silicon, were associated with CIMT using 2 distinct exposure prediction modeling approaches. PMID:25164422

Predictive Values of the New Sarcopenia Index by the Foundation for the National Institutes of Health Sarcopenia Project for Mortality among Older Korean Adults

Science.gov (United States)

Kim, Jung Hee; Moon, Jae Hoon; Choi, Sung Hee; Lim, Soo; Lim, Jae-Young; Kim, Ki Woong; Park, Kyong Soo; Jang, Hak Chul

2016-01-01

Objective We evaluated the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project’s recommended criteria for sarcopenia’s association with mortality among older Korean adults. Methods We conducted a community-based prospective cohort study which included 560 (285 men and 275 women) older Korean adults aged ≥65 years. Muscle mass (appendicular skeletal muscle mass-to-body mass index ratio (ASM/BMI)), handgrip strength, and walking velocity were evaluated in association with all-cause mortality during 6-year follow-up. Both the lowest quintile for each parameter (ethnic-specific cutoff) and FNIH-recommended values were used as cutoffs. Results Forty men (14.0%) and 21 women (7.6%) died during 6-year follow-up. The deceased subjects were older and had lower ASM, handgrip strength, and walking velocity. Sarcopenia defined by both low lean mass and weakness had a 4.13 (95% CI, 1.69–10.11) times higher risk of death, and sarcopenia defined by a combination of low lean mass, weakness, and slowness had a 9.56 (3.16–28.90) times higher risk of death after adjusting for covariates in men. However, these significant associations were not observed in women. In terms of cutoffs of each parameter, using the lowest quintile showed better predictive values in mortality than using the FNIH-recommended values. Moreover, new muscle mass index, ASM/BMI, provided better prognostic values than ASM/height2 in all associations. Conclusions New sarcopenia definition by FNIH was better able to predict 6-year mortality among Korean men. Moreover, ethnic-specific cutoffs, the lowest quintile for each parameter, predicted the higher risk of mortality than the FNIH-recommended values. PMID:27832145

Serum 25-hydroxyvitamin D, mortality, and incident cardiovascular disease, respiratory disease, cancers, and fractures: a 13-y prospective population study.

Science.gov (United States)

Khaw, Kay-Tee; Luben, Robert; Wareham, Nicholas

2014-11-01

Vitamin D is associated with many health conditions, but optimal blood concentrations are still uncertain. We examined the prospective relation between serum 25-hydroxyvitamin D [25(OH)D] concentrations [which comprised 25(OH)D3 and 25(OH)D2] and subsequent mortality by the cause and incident diseases in a prospective population study. Serum vitamin D concentrations were measured in 14,641 men and women aged 42-82 y in 1997-2000 who were living in Norfolk, United Kingdom, and were followed up to 2012. Participants were categorized into 5 groups according to baseline serum concentrations of total 25(OH)D increasing vitamin D category were 1, 0.84 (0.74, 0.94), 0.72 (0.63, 0.81), 0.71 (0.62, 0.82), and 0.66 (0.55, 0.79) (P-trend disease, diabetes, or cancer, HRs for a 20-nmol/L increase in 25(OH)D were 0.92 (0.88, 0.96) (P disease, 0.89 (0.85, 0.93) (P respiratory disease, 0.89 (0.81, 0.98) (P = 0.012) (563 events) for fractures, and 1.02 (0.99, 1.06) (P = 0.21) (3121 events) for incident total cancers. Plasma 25(OH)D concentrations predict subsequent lower 13-y total mortality and incident cardiovascular disease, respiratory disease, and fractures but not total incident cancers. For mortality, lowest risks were in subjects with concentrations >90 nmol/L, and there was no evidence of increased mortality at high concentrations, suggesting that a moderate increase in population mean concentrations may have potential health benefit, but 120 nmol/L.

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

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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.

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

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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.

Herd factors associated with dairy cow mortality.

Science.gov (United States)

McConnel, C; Lombard, J; Wagner, B; Kopral, C; Garry, F

2015-08-01

Summary studies of dairy cow removal indicate increasing levels of mortality over the past several decades. This poses a serious problem for the US dairy industry. The objective of this project was to evaluate associations between facilities, herd management practices, disease occurrence and death rates on US dairy operations through an analysis of the National Animal Health Monitoring System's Dairy 2007 survey. The survey included farms in 17 states that represented 79.5% of US dairy operations and 82.5% of the US dairy cow population. During the first phase of the study operations were randomly selected from a sampling list maintained by the National Agricultural Statistics Service. Only farms that participated in phase I and had 30 or more dairy cows were eligible to participate in phase II. In total, 459 farms had complete data for all selected variables and were included in this analysis. Univariable associations between dairy cow mortality and 162 a priori identified operation-level management practices or characteristics were evaluated. Sixty of the 162 management factors explored in the univariate analysis met initial screening criteria and were further evaluated in a multivariable model exploring more complex relationships. The final weighted, negative binomial regression model included six variables. Based on the incidence rate ratio, this model predicted 32.0% less mortality for operations that vaccinated heifers for at least one of the following: bovine viral diarrhea, infectious bovine rhinotracheitis, parainfluenza 3, bovine respiratory syncytial virus, Haemophilus somnus, leptospirosis, Salmonella, Escherichia coli or clostridia. The final multivariable model also predicted a 27.0% increase in mortality for operations from which a bulk tank milk sample tested ELISA positive for bovine leukosis virus. Additionally, an 18.0% higher mortality was predicted for operations that used necropsies to determine the cause of death for some proportion of dead

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.

Effect of heart rate correction on pre- and post-exercise heart rate variability to predict risk of mortality – an experimental study on the FINCAVAS cohort

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Paruthi ePradhapan

2014-06-01

Full Text Available The non-linear inverse relationship between RR-intervals and heart rate (HR contributes significantly to the heart rate variability (HRV parameters and their performance in mortality prediction. To determine the level of influence HR exerts over HRV parameters’ prognostic power, we studied the predictive performance for different HR levels by applying eight correction procedures, multiplying or dividing HRV parameters by the mean RR-interval (RRavg to the power 0.5-16. Data collected from 1288 patients in The Finnish Cardiovascular Study (FINCAVAS, who satisfied the inclusion criteria, was used for the analyses. HRV parameters (RMSSD, VLF Power and LF Power were calculated from 2-minute segment in the rest phase before exercise and 2-minute recovery period immediately after peak exercise. Area under the receiver operating characteristic curve (AUC was used to determine the predictive performance for each parameter with and without HR corrections in rest and recovery phases. The division of HRV parameters by segment’s RRavg to the power 2 (HRVDIV-2 showed the highest predictive performance under the rest phase (RMSSD: 0.67/0.66; VLF Power: 0.70/0.62; LF Power: 0.79/0.65; cardiac mortality/non-cardiac mortality with minimum correlation to HR (r = -0.15 to 0.15. In the recovery phase, Kaplan-Meier (KM survival analysis revealed good risk stratification capacity at HRVDIV-2 in both groups (cardiac and non-cardiac mortality. Although higher powers of correction (HRVDIV-4 and HRVDIV-8 improved predictive performance during recovery, they induced an increased positive correlation to HR. Thus, we inferred that predictive capacity of HRV during rest and recovery is augmented when its dependence on HR is weakened by applying appropriate correction procedures.

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...

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.

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

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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

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

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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

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