Long-term outcomes and independent predictors of mortality in patients presenting to emergency departments with acute heart failure in Beijing: a multicenter cohort study with a 5-year follow-up
Abstract
Supplemental Digital Content is available in the text Abstract Background: Acute heart failure (AHF) is the most common disease in emergency departments (EDs). However, clinical data exploring the outcomes of patients presenting AHF in EDs are limited, especially the long-term outcomes. The purposes of this study were to describe the long-term outcomes of patients with AHF in the EDs and further analyze their prognostic factors. Methods: This prospective, multicenter, cohort study consecutively enrolled 3335 patients with AHF who were admitted to EDs of 14 hospitals from Beijing between January 1, 2011 and September 23, 2012. Kaplan-Meier and Cox regression analysis were adopted to evaluate 5-year outcomes and associated predictors. Results: The 5-year mortality and cardiovascular death rates were 55.4% and 49.6%, respectively. The median overall survival was 34 months. Independent predictors of 5-year mortality were patient age (hazard ratio [HR]: 1.027, 95 confidence interval [CI]: 1.023–1.030), body mass index (BMI) (HR: 0.971, 95% CI: 0.958–0.983), fatigue (HR: 1.127, 95% CI: 1.009–1.258), ascites (HR: 1.190, 95% CI: 1.057–1.340), hepatic jugular reflux (HR: 1.339, 95% CI: 1.140–1.572), New York Heart Association (NYHA) class III to IV (HR: 1.511, 95% CI: 1.291–1.769), heart rate (HR: 1.003, 95% CI: 1.001–1.005), diastolic blood pressure (DBP) (HR: 0.996, 95% CI: 0.993–0.999), blood urea nitrogen (BUN) (HR: 1.014, 95% CI: 1.008–1.020), B-type natriuretic peptide…
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: 3,335 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.