Trend and Predictors of Short-term Mortality of Adult Bacteremia at Emergency Departments: A 14-Year Cohort Study of 14 625 Patients
Abstract
Abstract Background Bacteremia is a life-threatening condition with a high mortality rate in critical care and emergency settings. The current study investigated the trend of mortality and developed predictive models of mortality for adults with bacteremia at emergency departments (EDs). Methods We conducted a retrospective cohort study of adults with bacteremia at the ED of China Medical University Hospital. Patient data were obtained from the Clinical Research Data Repository, and mortality information was obtained from the National Death Registry. We developed a new model to predict 7-day mortality in the derivation population and compared the model performance of the new model with Pitt Bacteremia Score (PBS) and Bloodstream Infection Mortality Risk Score (BSIMRS) in the validation population. Results We identified 14625 adult patients with first-time bacteremia at the ED, of whom 8.4% died within 7 days. From 2003 to 2016, both the cumulative incidence and 7-day mortality rate of bacteremia decreased significantly. The ED bacteremia mortality (ED-BM) model included PBS parameters, age, infection source, baseline steroid use, and biochemical profiles (estimated glomerular filtration rate, platelet, blood urea nitrogen, potassium, and hemoglobin) for predicting 7-day mortality. The discrimination performance of the ED-BM model (area under curve [AUC], 0.903) was significantly better than that of PBS (AUC, 0.848) or BSIMRS (AUC, 0.885). Conclusions Although the cumulative…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 14,625 participants or records.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.