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Background: Vitamin D status is known to be important for bone health but may also affect the development of several chronic diseases, including cancer and cardiovascular diseases, which are 2 major causes of death., Objective: We aimed to examine how vitamin D status relates to overall and cause-specific mortality., Design: The Uppsala Longitudinal Study of Adult Men, a community-based cohort of elderly men (mean age at baseline: 71 y; n = 1194), was used to investigate the association between plasma 25-hydroxyvitamin D [25(OH)D] and mortality. Total plasma 25(OH)D was determined with HPLC atmospheric pressure chemical ionization mass spectrometry. Proportional hazards regression was used to compute hazard ratios (HRs)., Results: During follow-up (median: 12.7 y), 584 (49%) participants died. There was a U-shaped association between vitamin D concentrations and total mortality. An approximately 50% higher total mortality rate was observed among men in the lowest 10% (<46 nmol/L) and the highest 5% (>98 nmol/L) of plasma 25(OH)D concentrations compared with intermediate concentrations. Cancer mortality was also higher at low plasma concentrations (multivariable-adjusted HR: 2.20; 95% CI: 1.44, 3.38) and at high concentrations (HR: 2.64; 95% CI: 1.46, 4.78). For cardiovascular death, only low (HR: 1.89; 95% CI: 1.21, 2.96) but not high (HR: 1.33; 95% CI: 0.69, 2.54) concentrations indicated higher risk., Conclusions: Both high and low concentrations of plasma 25(OH)D are associated with elevated risks of overall and cancer mortality. Low concentrations are associated with cardiovascular mortality.

Background: The ability to account for comorbidity when estimating survival in a population diagnosed with cancer could be improved by using a drug comorbidity index based on filled drug prescriptions.Methods: We created a drug comorbidity index from age-stratified univariable associations between filled drug prescriptions and time to death in 326,450 control males randomly selected from the general population to men with prostate cancer. We also evaluated the index in 272,214 control females randomly selected from the general population to women with breast cancer.Results: The new drug comorbidity index predicted survival better than the Charlson Comorbidity Index (CCI) and a previously published prescription index during 11 years of follow-up. The concordance (C)-index for the new index was 0.73 in male and 0.76 in the female population, as compared with a C-index of 0.67 in men and 0.69 in women for the CCI. In men of age 75-84 years with CCI = 0, the median survival time was 7.1 years (95% confidence interval [CI] = 7.0, 7.3) in the highest index quartile. Comparing the highest to the lowest drug comorbidity index quartile resulted in a hazard ratio (HR) of 2.2 among men (95% CI = 2.1, 2.3) and 2.4 among women (95% CI = 2.3, 2.6).Conclusions: A new drug comorbidity index based on filled drug prescriptions improved prediction of survival beyond age and the CCI alone. The index will allow a more accurate baseline estimation of expected survival for comparing treatment outcomes and evaluating treatment guidelines in populations of people with cancer. [ABSTRACT FROM AUTHOR]

Background: Routinely collected laboratory biomarkers could improve control of confounding from disease severity in non-interventional studies of general intensive care unit (ICU) patients. Their ability to predict both short- and long-term mortality was evaluated.Methods: The performance of age, sex, Charlson co-morbidity index, and baseline values of ten predefined blood biomarkers as predictors of 30-day and 1-year mortality was evaluated in 5505 general ICU stays.Results: Regression models based on age, sex, Charlson index, and biomarkers were somewhat less accurate in predicting 30-day mortality (c-index 0.83, Brier score 0.27) compared to the SAPS II score (c-index = 0.88, Brier score = 0.09) and in predicting 1-year mortality (c-index = 0.82, Brier score = 0.31) compared to the SAPS II score (c-index = 0.85, Brier score = 0.13). Cystatin C improved predictive ability slightly compared to creatinine, but age and Charlson comorbidity index were more important predictors. Using multiple imputation to replace missing biomarker values notably improved predictive ability of the models.Conclusions: Automatically collected baseline variables are almost as predictive of both short- and long-term mortality in general ICU patients, as the SAPS II score. This can facilitate internal control of confounding in non-interventional studies of mortality using administrative data. [ABSTRACT FROM AUTHOR]

Background: To predict mortality risk in victims of violent crimes based on individual injury diagnoses and other information available in health care registries.Methods: Data from the Swedish hospital discharge registry and the cause of death registry were combined to identify 15,000 hospitalisations or prehospital deaths related to violent crimes. The ability of patient characteristics, injury type and severity, and cause of injury to predict death was modelled using conventional, Lasso, or Bayesian logistic regression in a development dataset and evaluated in a validation dataset.Results: Of 14,470 injury events severe enough to cause death or hospitalization 3.7% (556) died before hospital admission and 0.5% (71) during the hospital stay. The majority (76%) of hospital survivors had minor injury severity and most (67%) were discharged from hospital within 1day. A multivariable model with age, sex, the ICD-10 based injury severity score (ICISS), cause of injury, and major injury region provided predictions with very good discrimination (C-index=0.99) and calibration. Adding information on major injury interactions further improved model performance. Modeling individual injury diagnoses did not improve predictions over the combined ICISS score.Conclusions: Mortality risk after violent crimes can be accurately estimated using administrative data. The use of Bayesian regression models provides meaningful risk assessment with more straightforward interpretation of uncertainty of the prediction, potentially also on the individual level. This can aid estimation of incidence trends over time and comparisons of outcome of violent crimes for injury surveillance and in forensic medicine. [ABSTRACT FROM AUTHOR]

Objective To assess whether higher mortality rates among individuals in motor vehicle crashes in areas with low population density depend on injury type and severity or are related to the performance of emergency medical services (EMS). Methods Prehospital and hospital deaths were studied in a population-based cohort of 41 243 motor vehicle crashes that occurred in Sweden between 1998 and 2004. The final multivariable analysis was restricted to 6884 individuals in motor vehicle crashes, to minimise the effects of confounding factors. Results Crude mortality rates following motor vehicle crashes were inversely related to regional population density. In regions with low population density, the unadjusted rate ratio for prehospital death was 2.2 (95% CI 1.9 to 2.5) and for hospital death 1.5 (95% CI 1.1 to 1.9), compared with a high-density population. However, after controlling for regional differences in age, gender and the type/severity of injuries among 6884 individuals in motor vehicle crashes, low population density was no longer associated with increased mortality. At 25 years of age, predicted prehospital mortality was 9% lower (95% CI 5% to 12%) in regions with low population density compared with high population density. This difference decreased with increasing age, but was still 3% lower (95% CI 0.5% to 5%) at 65 years of age. Conclusions The inverse relationship between population density and mortality among individuals in motor vehicle crashes is related to pre-crash factors that influence the type and severity of injuries and not to differences in EMS. [ABSTRACT FROM PUBLISHER]

Abstract: Background: The Prehospital Trauma Life Support (PHTLS) course has been widely implemented and approximately half a million prehospital caregivers in over 50 countries have taken this course. Still, the effect on injury outcome remains to be established. The objective of this study was to investigate the association between PHTLS training of ambulance crew members and the mortality in trauma patients. Methods: A population-based observational study of 2830 injured patients, who either died or were hospitalized for more than 24h, was performed during gradual implementation of PHTLS in Uppsala County in Sweden between 1998 and 2004. Prehospital patient records were linked to hospital-discharge records, cause-of-death records, and information on PHTLS training and the educational level of ambulance crews. The main outcome measure was death, on scene or in hospital. Results: Adjusting for multiple potential confounders, PHTLS training appeared to be associated with a reduction in mortality, but the precision of this estimate was poor (odds ratio, 0.71; 95% confidence interval, 0.42–1.19). The mortality risk was 4.7% (36/763) without PHTLS training and 4.5% (94/2067) with PHTLS training. The predicted absolute risk reduction is estimated to correspond to 0.5 lives saved annually per 100,000 population with PHTLS fully implemented. Conclusions: PHTLS training of ambulance crew members may be associated with reduced mortality in trauma patients, but the precision in this estimate was low due to the overall low mortality. While there may be a relative risk reduction, the predicted absolute risk reduction in this population was low. [Copyright &y& Elsevier]