International comparisons of COVID-19 deaths in the presence of comorbidities require uniform mortality coding guidelines.
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ABSTRACT:
SUBMITTER: Singh B
PROVIDER: S-EPMC7928837 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature
Publications
International comparisons of COVID-19 deaths in the presence of comorbidities require uniform mortality coding guidelines.
International journal of epidemiology 20210501 2
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Project description: Not available
| S-EPMC8250608 | biostudies-literature
Project description:BACKGROUND: Results of epidemiological studies linking census with mortality records may be affected by unlinked deaths and changes in cause of death classification. We examined these issues in the Swiss National Cohort (SNC). METHODS: The SNC is a longitudinal study of the entire Swiss population, based on the 1990 (6.8 million persons) and 2000 (7.3 million persons) censuses. Among 1,053,393 deaths recorded 1991-2007 5.4% could not be linked using stringent probabilistic linkage. We included the unlinked deaths using pragmatic linkages and compared mortality rates for selected causes with official mortality rates. We also examined the impact of the 1995 change in cause of death coding from version 8 (with some additional rules) to version 10 of the International Classification of Diseases (ICD), using Poisson regression models with restricted cubic splines. Finally, we compared results from Cox models including and excluding unlinked deaths of the association of education, marital status, and nationality with selected causes of death. RESULTS: SNC mortality rates underestimated all cause mortality by 9.6% (range 2.4%-17.9%) in the 85+ population. Underestimation was less pronounced in years nearer the censuses and in the 75-84 age group. After including 99.7% of unlinked deaths, annual all cause SNC mortality rates were reflecting official rates (relative difference between -1.4% and +1.8%). In the 85+ population the rates for prostate and breast cancer dropped, by 16% and 21% respectively, between 1994 and 1995 coincident with the change in cause of death coding policy. For suicide in males almost no change was observed. Hazard ratios were only negligibly affected by including the unlinked deaths. A sudden decrease in breast (21% less, 95% confidence interval: 12%-28%) and prostate (16% less, 95% confidence interval: 7%-23%) cancer mortality rates in the 85+ population coincided with the 1995 change in cause of death coding policy. CONCLUSIONS: Unlinked deaths bias analyses of absolute mortality rates downwards but have little effect on relative mortality. To describe time trends of cause-specific mortality in the SNC, accounting for the unlinked deaths and for the possible effect of change in death certificate coding was necessary.
| S-EPMC3547805 | biostudies-other
Project description:Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.
| S-EPMC9192605 | biostudies-literature
Project description: Not available
| S-EPMC1730232 | biostudies-literature
Project description:BackgroundPatients with bronchiectasis often have concurrent comorbidities, but the nature, prevalence, and impact of these comorbidities on disease severity and outcome are poorly understood. We aimed to investigate comorbidities in patients with bronchiectasis and establish their prognostic value on disease severity and mortality rate.MethodsAn international multicentre cohort analysis of outpatients with bronchiectasis from four European centres followed up for 5 years was done for score derivation. Eligible patients were those with bronchiectasis confirmed by high-resolution CT and a compatible clinical history. Comorbidity diagnoses were based on standardised definitions and were obtained from full review of paper and electronic medical records, prescriptions, and investigator definitions. Weibull parametric survival analysis was used to model the prediction of the 5 year mortality rate to construct the Bronchiectasis Aetiology Comorbidity Index (BACI). We tested the BACI as a predictor of outcomes and explored whether the BACI added further prognostic information when used alongside the Bronchiectasis Severity Index (BSI). The BACI was validated in two independent international cohorts from the UK and Serbia.FindingsBetween June 1, 2006, and Nov 22, 2013, 1340 patients with bronchiectasis were screened and 986 patients were analysed. Patients had a median of four comorbidities (IQR 2-6; range 0-20). 13 comorbidities independently predicting mortality rate were integrated into the BACI. The overall hazard ratio for death conferred by a one-point increase in the BACI was 1·18 (95% CI 1·14-1·23; p<0·0001). The BACI predicted 5 year mortality rate, hospital admissions, exacerbations, and health-related quality of life across all BSI risk strata (p<0·0001 for mortality and hospital admissions, p=0·03 for exacerbations, p=0·0008 for quality of life). When used in conjunction with the BSI, the combined model was superior to either model alone (p=0·01 for combined vs BACI; p=0·008 for combined vs BSI).InterpretationMultimorbidity is frequent in bronchiectasis and can negatively affect survival. The BACI complements the BSI in the assessment and prediction of mortality and disease outcomes in patients with bronchiectasis.FundingEuropean Bronchiectasis Network (EMBARC).
| S-EPMC5369638 | biostudies-literature
Project description:Single-cell transcriptomics has revolutionized our understanding of neurodevelopmental cell identities, yet, predicting a cell type's developmental state from its transcriptome remains a challenge. We perform a meta-analysis of developing human brain datasets comprising over 2.8 million cells, identifying both tissue-level and cell-autonomous predictors of developmental age. While tissue composition predicts age within individual studies, it fails to generalize, whereas specific cell type proportions reliably track developmental time across datasets. Training regularized regression models to infer cell-autonomous maturation, we find that a cell type-agnostic model achieves the highest accuracy (error = 2.6 weeks), robustly capturing developmental dynamics across diverse cell types and datasets. This model generalizes to human neural organoids, accurately predicting normal developmental trajectories (R = 0.91) and disease-induced shifts in vitro. Furthermore, it extends to the developing mouse brain, revealing an accelerated developmental tempo relative to humans. Our work provides a unified framework for comparing neurodevelopment across contexts, model systems, and species.
| S-EPMC11888278 | biostudies-literature
Project description:Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. Notably, amino acids located at the surface of proteins are known to evolve more rapidly than those in the core. In particular, amino acids at the N- and C-termini of protein sequences are likely to be more exposed than those at the core of the folded protein due to their location in the peptidic chain, and they are known to be less structured. Because of these reasons, we would expect that amino acids located at protein termini would evolve faster than residues located inside the chain. Here we test this hypothesis and found that amino acids evolve almost twice as fast at protein termini compared with those in the center, hinting at a strong topological bias along the sequence length. We further show that the distribution of solvent-accessible residues and functional domains in proteins readily explain how structural and functional constraints are weaker at their termini, leading to the observed excess of amino acid substitutions. Finally, we show that the specific evolutionary rates at protein termini may have direct consequences, notably misleading in silico methods used to infer sites under positive selection within genes. These results suggest that accounting for positional information should improve evolutionary models.
| S-EPMC10025431 | biostudies-literature
Project description:ObjectiveTo estimate a safe minimum hospital volume for hospitals performing coronary artery bypass graft (CABG) surgery.Data sourceHospital data on all publicly funded CABG in five European countries, 2007-2009 (106,149 patients).DesignHierarchical logistic regression models to estimate the relationship between hospital volume and mortality, allowing for case mix. Segmented regression analysis to estimate a threshold.FindingsThe 30-day in-hospital mortality rate was 3.0 percent overall, 5.2 percent (95 percent CI: 4.0-6.4) in low-volume hospitals, and 2.1 percent (95 percent CI: 1.8-2.3) in high-volume hospitals. There is a significant curvilinear relationship between volume and mortality, flatter above 415 cases per hospital per year.ConclusionsThere is a clear relationship between hospital CABG volume and mortality in Europe, implying a "safe" threshold volume of 415 cases per year.
| S-EPMC5346497 | biostudies-literature
Project description:As of March 2021, coronavirus disease (COVID-19) had led to >500,000 deaths in the United States, and the state of Tennessee had the fifth highest number of cases per capita. We reviewed the Tennessee Department of Health COVID-19 surveillance and chart-abstraction data during March 15‒August 15, 2020. Patients who died from COVID-19 were more likely to be older, male, and Black and to have underlying conditions (hereafter comorbidities) than case-patients who survived. We found 30.4% of surviving case-patients and 20.3% of deceased patients had no comorbidity information recorded. Chart-abstraction captured a higher proportion of deceased case-patients with >1 comorbidity (96.3%) compared with standard surveillance deaths (79.0%). Chart-abstraction detected higher rates of each comorbidity except for diabetes, which had similar rates among standard surveillance and chart-abstraction. Investing in public health data collection infrastructure will be beneficial for the COVID-19 pandemic and future disease outbreaks.
| S-EPMC8462317 | biostudies-literature
Project description:BackgroundThe morbidity and mortality associated with COPD exacts a considerable economic burden. Comorbidities in COPD are associated with poor health outcomes and increased costs. Our objective was to assess the impact of comorbidities on COPD-associated costs in a large administrative claims dataset.MethodsThis was a retrospective observational study of data from the Truven Health MarketScan Commercial Claims and Encounters and the MarketScan Medicare Supplemental Databases from January 1, 2009, to September 30, 2012. Resource consumption was measured from the index date (date of first occurrence of non-rule-out COPD diagnosis) to 360 days after the index date. Resource use (all-cause and disease-specific [ie, COPD- or asthma-related] ED visits, hospitalizations, office visits, other outpatient visits, and total length of hospital stay) and health-care costs (all-cause and disease-specific costs for ED visits, hospitalizations, office visits, and other outpatient visits and medical, prescription, and total health-care costs) were assessed. Generalized linear models were used to evaluate the impact of comorbidities on total health-care costs, adjusting for age, sex, geographic location, baseline health-care use, employment status, and index COPD medication.ResultsAmong 183,681 patients with COPD, the most common comorbidities were cardiovascular disease (34.8%), diabetes (22.8%), asthma (14.7%), and anemia (14.2%). Most patients (52.8%) had one or two comorbidities of interest. The average all-cause total health-care costs from the index date to 360 days after the index date were highest for patients with chronic kidney disease ($41,288) and anemia ($38,870). The impact on total health-care costs was greatest for anemia ($10,762 more, on average, than a patient with COPD without anemia).ConclusionsOur analysis demonstrated that high resource use and costs were associated with COPD and multiple comorbidities.
| S-EPMC4493870 | biostudies-literature