| 1. |
- Aronsson Dannewitz, Anna, et al.
(författare)
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Optimized diagnosis-based comorbidity measures for all-cause mortality prediction in a national population-based ICU population
- 2022
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Ingår i: Critical Care. - : Springer Nature. - 1364-8535 .- 1466-609X. ; 26
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Tidskriftsartikel (refereegranskat)abstract
- Background: We aimed to optimize prediction of long-term all-cause mortality of intensive care unit (ICU) patients, using quantitative register-based comorbidity information assessed from hospital discharge diagnoses prior to intensive care treatment.Material and methods: Adult ICU admissions during 2006 to 2012 in the Swedish intensive care register were followed for at least 4 years. The performance of quantitative comorbidity measures based on the 5-year history of number of hospital admissions, length of stay, and time since latest admission in 36 comorbidity categories was compared in time-to-event analyses with the Charlson comorbidity index (CCI) and the Simplified Acute Physiology Score (SAPS3).Results: During a 7-year period, there were 230,056 ICU admissions and 62,225 deaths among 188,965 unique individuals. The time interval from the most recent hospital stays and total length of stay within each comorbidity category optimized mortality prediction and provided clear separation of risk categories also within strata of age and CCI, with hazard ratios (HRs) comparing lowest to highest quartile ranging from 1.17 (95% CI: 0.52-2.64) to 6.41 (95% CI: 5.19-7.92). Risk separation was also observed within SAPS deciles with HR ranging from 1.07 (95% CI: 0.83-1.38) to 3.58 (95% CI: 2.12-6.03).Conclusion: Baseline comorbidity measures that included the time interval from the most recent hospital stay in 36 different comorbidity categories substantially improved long-term mortality prediction after ICU admission compared to the Charlson index and the SAPS score. Trial registration ClinicalTrials.gov ID NCT04109001, date of registration 2019-09-26 retrospectively.
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| 2. |
- Gedeborg, Rolf, et al.
(författare)
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Federated analyses of multiple data sources in drug safety studies
- 2023
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Ingår i: Pharmacoepidemiology and Drug Safety. - : John Wiley & Sons. - 1053-8569 .- 1099-1557. ; 32:3, s. 279-286
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Forskningsöversikt (refereegranskat)abstract
- PurposeStudies of rare side effects of new drugs with limited exposure may require pooling of multiple data sources. Federated Analyses (FA) allow real-time, interactive, centralized statistical processing of individual-level data from different data sets without transfer of sensitive personal data.MethodsWe review IT-architecture, legal considerations, and statistical methods in FA, based on a Swedish Medical Products Agency methodological development project.ResultsIn a review of all post-authorisation safety studies assessed by the EMA during 2019, 74% (20/27 studies) reported issues with lack of precision in spite of mean study periods of 9.3 years. FA could potentially improve precision in such studies. Depending on the statistical model, the federated approach can generate identical results to a standard analysis. FA may be particularly attractive for repeated collaborative projects where data is regularly updated. There are also important limitations. Detailed agreements between involved parties are strongly recommended to anticipate potential issues and conflicts, document a shared understanding of the project, and fully comply with legal obligations regarding ethics and data protection. FA do not remove the data harmonisation step, which remains essential and often cumbersome. Reliable support for technical integration with the local server architecture and security solutions is required. Common statistical methods are available, but adaptations may be required.ConclusionsFederated Analyses require competent and active involvement of all collaborating parties but have the potential to facilitate collaboration across institutional and national borders and improve the precision of postmarketing drug safety studies.
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| 3. |
- Gedeborg, Rolf, et al.
(författare)
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Prediction of mortality risk in victims of violent crimes
- 2017
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Ingår i: Forensic Science International. - : Elsevier BV. - 0379-0738 .- 1872-6283. ; 281, s. 92-97
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 4. |
- Michaëlsson, Karl, 1959-, et al.
(författare)
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Combined associations of body mass index and adherence to a Mediterranean-like diet with all-cause and cardiovascular mortality : A cohort study
- 2020
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Ingår i: PLoS Medicine. - : Public Library of Science (PLoS). - 1549-1277 .- 1549-1676. ; 17:9
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundIt is unclear whether the effect on mortality of a higher body mass index (BMI) can be compensated for by adherence to a healthy diet and whether the effect on mortality by a low adherence to a healthy diet can be compensated for by a normal weight. We aimed to evaluate the associations of BMI combined with adherence to a Mediterranean-like diet on all-cause and cardiovascular disease (CVD) mortality.Methods and findingsOur longitudinal cohort design included the Swedish Mammography Cohort (SMC) and the Cohort of Swedish Men (COSM) (1997–2017), with a total of 79,003 women (44%) and men (56%) and a mean baseline age of 61 years. BMI was categorized into normal weight (20–24.9 kg/m2), overweight (25–29.9 kg/m2), and obesity (30+ kg/m2). Adherence to a Mediterranean-like diet was assessed by means of the modified Mediterranean-like diet (mMED) score, ranging from 0 to 8; mMED was classified into 3 categories (0 to <4, 4 to <6, and 6–8 score points), forming a total of 9 BMI × mMED combinations. We identified mortality by use of national Swedish registers. Cox proportional hazard models with time-updated information on exposure and covariates were used to calculate the adjusted hazard ratios (HRs) of mortality with their 95% confidence intervals (CIs). Our HRs were adjusted for age, baseline educational level, marital status, leisure time physical exercise, walking/cycling, height, energy intake, smoking habits, baseline Charlson’s weighted comorbidity index, and baseline diabetes mellitus. During up to 21 years of follow-up, 30,389 (38%) participants died, corresponding to 22 deaths per 1,000 person-years. We found the lowest HR of all-cause mortality among overweight individuals with high mMED (HR 0.94; 95% CI 0.90, 0.98) compared with those with normal weight and high mMED. Using the same reference, obese individuals with high mMED did not experience significantly higher all-cause mortality (HR 1.03; 95% CI 0.96–1.11). In contrast, compared with those with normal weight and high mMED, individuals with a low mMED had a high mortality despite a normal BMI (HR 1.60; 95% CI 1.48–1.74). We found similar estimates among women and men. For CVD mortality (12,064 deaths) the findings were broadly similar, though obese individuals with high mMED retained a modestly increased risk of CVD death (HR 1.29; 95% CI 1.16–1.44) compared with those with normal weight and high mMED. A main limitation of the present study is the observational design with self-reported lifestyle information with risk of residual or unmeasured confounding (e.g., genetic liability), and no causal inferences can be made based on this study alone.ConclusionsThese findings suggest that diet quality modifies the association between BMI and all-cause mortality in women and men. A healthy diet may, however, not completely counter higher CVD mortality related to obesity.
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| 5. |
- Sundström, Johan, Professor, 1971-, et al.
(författare)
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Risk factors for subarachnoid haemorrhage : a nationwide cohort of 950 000 adults
- 2019
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Ingår i: International Journal of Epidemiology. - : Oxford University Press. - 0300-5771 .- 1464-3685. ; 48:6, s. 2018-2025
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Subarachnoid haemorrhage (SAH) is a devastating disease, with high mortality rate and substantial disability among survivors. Its causes are poorly understood. We aimed to investigate risk factors for SAH using a novel nationwide cohort consortium.METHODS: We obtained individual participant data of 949 683 persons (330 334 women) between 25 and 90 years old, with no history of SAH at baseline, from 21 population-based cohorts. Outcomes were obtained from the Swedish Patient and Causes of Death Registries.RESULTS: During 13 704 959 person-years of follow-up, 2659 cases of first-ever fatal or non-fatal SAH occurred, with an age-standardized incidence rate of 9.0 [95% confidence interval (CI) (7.4-10.6)/100 000 person-years] in men and 13.8 [(11.4-16.2)/100 000 person-years] in women. The incidence rate increased exponentially with higher age. In multivariable-adjusted Poisson models, marked sex interactions for current smoking and body mass index (BMI) were observed. Current smoking conferred a rate ratio (RR) of 2.24 (95% CI 1.95-2.57) in women and 1.62 (1.47-1.79) in men. One standard deviation higher BMI was associated with an RR of 0.86 (0.81-0.92) in women and 1.02 (0.96-1.08) in men. Higher blood pressure and lower education level were also associated with higher risk of SAH.CONCLUSIONS: The risk of SAH is 45% higher in women than in men, with substantial sex differences in risk factor strengths. In particular, a markedly stronger adverse effect of smoking in women may motivate targeted public health initiatives.
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