Dataset Information

Clustered Emergency Room Visits Following an Acute Heart Failure Admission: A Population-Based Study.

ABSTRACT:

Background

While it is well known that heart failure patients presenting to the emergency room (ER) have high short-term mortality after discharge, the outcomes of patients with heart failure with repeated ER visits within a short time are not known. In this study, we aimed to determine whether clustering is associated with an increased risk of death.

Methods and results

This is a retrospective, population-based cohort study with an accrual window between 2003 and 2014 and maximal follow-up up to and including March 31, 2015. Data were obtained from administrative databases from Ontario, Canada. Clustering was defined a priori as 3 or more ER visits within a 6-month period. The main outcome of interest was time to death conditional on 6-month survival. A total of 72 810 patients with an index hospitalization for acute heart failure were evaluated. ER clustering was observed in 15.1% of the population. Increased burden of comorbidities, primary rural residence, and lack of primary care provider were identified as factors associated with ER clustering. Age- and sex-adjusted mortality for clustered patients was higher than for nonclustered (hazard ratio [HR] 1.51; 95% confidence interval, 1.47-1.55, P<0.0001). Adjusted mortality risk was also higher for patients with clustered ER visits (HR 1.42; 95% confidence interval 1.38-1.46; P<0.0001).

Conclusions

Clustering, as defined by 3 or more ER visits for any reason within 6 months of index heart failure hospitalization reflects a novel risk factor associated with increased mortality. Future research into the strategies to better manage complex patients with heart failure with recurrent ER visits are warranted.

SUBMITTER: Duero Posada JG

PROVIDER: S-EPMC5907582 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Publications

Clustered Emergency Room Visits Following an Acute Heart Failure Admission: A Population-Based Study.

Duero Posada Juan G JG Moayedi Yasbanoo Y Zhou Limei L McDonald Michael M Ross Heather J HJ Lee Douglas S DS Bhatia R Sacha RS

Journal of the American Heart Association 20180327 7

<h4>Background</h4>While it is well known that heart failure patients presenting to the emergency room (ER) have high short-term mortality after discharge, the outcomes of patients with heart failure with repeated ER visits within a short time are not known. In this study, we aimed to determine whether clustering is associated with an increased risk of death.<h4>Methods and results</h4>This is a retrospective, population-based cohort study with an accrual window between 2003 and 2014 and maximal ...[more]

PMID: 29588312

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Project description:AimsAcute heart failure (AHF) leads to a drastic increase in mortality and rehospitalization. The aim of the study was to identify prognostic variables in a real-life population of AHF patients admitted to the emergency department with acute shortness of breath.Methods and resultsWe evaluated potential predictors of mortality in 728 consecutive patients admitted to the emergency department with AHF. Possible predictors of all-cause and cardiovascular (CV) mortality were investigated by Cox and Fine and Gray models at multivariable analysis. Among the 728 patients, 256 died during the entire follow-up, 142 of these due to CV cause. The 1 year mortality rate was 20%, with the highest risk of death during the index hospitalization (with 8% estimate in-hospital mortality at 30 days). A higher risk of events during the index hospitalization was more evident for the CV deaths, for which we found a cumulative 1 year incidence of 12% with a cumulative incidence in the first 30 days of hospitalization of about 5%. At multivariable analysis, age (P < 0.001), New York Heart Association (NYHA) class IV vs. I-II-III (P = 0.001), systolic blood pressure (P < 0.001), non-cardiac co-morbidities (≥3 vs. 0, P = 0.05), oxygen saturation (P = 0.03), serum creatinine (P < 0.001), and left ventricular ejection fraction (LVEF) (40-49% vs. <40%, P = 0.004; ≥50% vs. <40%, P = 0.003) were independent predictors of all-cause mortality during the entire follow-up. Age (P = 0.03), systolic blood pressure (P = 0.01), oxygen saturation (P = 0.03), serum creatinine (P = 0.02), and LVEF (40-49% vs. <40%, P = 0.03; ≥50% vs. <40%, P = 0.004) were independent predictors of CV mortality during the entire follow-up. NYHA class IV vs. I-II-III (P < 0.001), serum creatinine (P = 0.01), and LVEF (40-49% vs. <40%, P = 0.02; ≥50% vs. <40%, P < 0.001) remained independent predictors for in-hospital death, while only serum creatinine (P = 0.04), LVEF (40-49% vs. <40%: 0.32, P = 0.04; ≥50% vs. <40%, P < 0.001), and NYHA class vs. I-II-III (P = 0.02) remained predictors for in-hospital CV mortality.ConclusionsIn this real-life cohort of patients with AHF, the results showed a similar mortality rate comparing with other analysis and with the most important registries. Age, NYHA class IV, systolic blood pressure, creatinine levels, sodium levels, and ejection fraction were independent predictors of 1 year mortality, while LVEF <40% was the only predictor of both all-cause mortality and CV mortality.

Project description:ImportanceMore than 80% of patients who present to the emergency department (ED) with acute heart failure (AHF) are hospitalized. With more than 1 million annual hospitalizations for AHF in the US, safe and effective alternatives are needed. Care for AHF in short-stay units (SSUs) may be safe and more efficient than hospitalization, especially for lower-risk patients, but randomized clinical trial data are lacking.ObjectiveTo compare the effectiveness of SSU care vs hospitalization in lower-risk patients with AHF.Design, setting, and participantsThis multicenter randomized clinical trial randomly assigned low-risk patients with AHF 1:1 to SSU or hospital admission from the ED. Patients received follow-up at 30 and 90 days post discharge. The study began December 6, 2017, and was completed on July 22, 2021. The data were analyzed between March 27, 2020, and November 11, 2023.InterventionRandomized post-ED disposition to less than 24 hours of SSU care vs hospitalization.Main outcomes and measuresThe study was designed to detect at least 1-day superiority for a primary outcome of days alive and out of hospital (DAOOH) at 30-day follow-up for 534 participants, with an allowance of 10% participant attrition. Due to the COVID-19 pandemic, enrollment was truncated at 194 participants. Before unmasking, the primary outcome was changed from DAOOH to an outcome with adequate statistical power: quality of life as measured by the 12-item Kansas City Cardiomyopathy Questionnaire (KCCQ-12). The KCCQ-12 scores range from 0 to 100, with higher scores indicating better quality of life.ResultsOf the 193 patients enrolled (1 was found ineligible after randomization), the mean (SD) age was 64.8 (14.8) years, 79 (40.9%) were women, and 114 (59.1%) were men. Baseline characteristics were balanced between arms. The mean (SD) KCCQ-12 summary score between the SSU and hospitalization arms at 30 days was 51.3 (25.7) vs 45.8 (23.8) points, respectively (P = .19). Participants in the SSU arm had 1.6 more DAOOH at 30-day follow-up than those in the hospitalization arm (median [IQR], 26.9 [24.4-28.8] vs 25.4 [22.0-27.7] days; P = .02). Adverse events were uncommon and similar in both arms.Conclusions and relevanceThe findings show that the SSU strategy was no different than hospitalization with regard to KCCQ-12 score, superior for more DAOOH, and safe for lower-risk patients with AHF. These findings of lower health care utilization with the SSU strategy need to be definitively tested in an adequately powered study.Trial registrationClinicalTrials.gov Identifier: NCT03302910.

Dataset Information

Clustered Emergency Room Visits Following an Acute Heart Failure Admission: A Population-Based Study.

Background

Methods and results

Conclusions

Publications

Clustered Emergency Room Visits Following an Acute Heart Failure Admission: A Population-Based Study.

Similar Datasets

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