Dataset Information

Factors related to early readmissions after acute heart failure: a nested case-control study.

ABSTRACT:

Aims

To describe the main characteristics of patients who were readmitted to hospital within 1 month after an index episode for acute decompensated heart failure (ADHF).

Methods and results

This is a nested case-control study in the ReIC cohort, cases being consecutive patients readmitted after hospitalization for an episode of ADHF and matched controls selected from those who were not readmitted. We collected clinical data and also patient-reported outcome measures, including dyspnea, Minnesota Living with Heart Failure Questionnaire (MLHFQ), Tilburg Frailty Indicator (TFI) and Hospital Anxiety and Depression Scale scores, as well as symptoms during a transition period of 1 month after discharge. We created a multivariable conditional logistic regression model. Despite cases consulted more than controls, there were no statistically significant differences in changes in treatment during this first month. Patients with chronic decompensated heart failure were 2.25 [1.25, 4.05] more likely to be readmitted than de novo patients. Previous diagnosis of arrhythmia and time since diagnosis ≥ 3 years, worsening in dyspnea, and changes in MLWHF and TFI scores were significant in the final model.

Conclusion

We present a model with explanatory variables for readmission in the short term for ADHF. Our study shows that in addition to variables classically related to readmission, there are others related to the presence of residual congestion, quality of life and frailty that are determining factors for readmission for heart failure in the first month after discharge.

Trial registration

ClinicalTrials.gov Identifier: NCT03300791. First registration: 03/10/2017.

SUBMITTER: Garcia-Gutierrez S

PROVIDER: S-EPMC9837935 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

Factors related to early readmissions after acute heart failure: a nested case-control study.

Garcia-Gutierrez Susana S Villanueva Ane A Lafuente Iratxe I Rodriguez Ibon I Lozano-Bahamonde Ainara A Murga Nekane N Orus Josefina J Camacho Emilia Rosa ER Quintana Jose María JM Quiros Raul R

BMC cardiovascular disorders 20230112 1

<h4>Aims</h4>To describe the main characteristics of patients who were readmitted to hospital within 1 month after an index episode for acute decompensated heart failure (ADHF).<h4>Methods and results</h4>This is a nested case-control study in the ReIC cohort, cases being consecutive patients readmitted after hospitalization for an episode of ADHF and matched controls selected from those who were not readmitted. We collected clinical data and also patient-reported outcome measures, including dys ...[more]

PMID: 36635633

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Project description:BackgroundSeveral studies have focused on stratifying patients according to their level of readmission risk, fueled in part by incentive programs in the U.S. that link readmission rates to the annual payment update by Medicare. Patient-specific predictions about readmission have not seen widespread use because of their limited accuracy and questions about the efficacy of using measures of risk to guide clinical decisions. We construct a predictive model for readmissions for congestive heart failure (CHF) and study how its predictions can be used to perform patient-specific interventions. We assess the cost-effectiveness of a methodology that combines prediction and decision making to allocate interventions. The results highlight the importance of combining predictions with decision analysis.MethodsWe construct a statistical classifier from a retrospective database of 793 hospital visits for heart failure that predicts the likelihood that patients will be rehospitalized within 30 days of discharge. We introduce a decision analysis that uses the predictions to guide decisions about post-discharge interventions. We perform a cost-effectiveness analysis of 379 additional hospital visits that were not included in either the formulation of the classifiers or the decision analysis. We report the performance of the methodology and show the overall expected value of employing a real-time decision system.FindingsFor the cohort studied, readmissions are associated with a mean cost of $13,679 with a standard error of $1,214. Given a post-discharge plan that costs $1,300 and that reduces 30-day rehospitalizations by 35%, use of the proposed methods would provide an 18.2% reduction in rehospitalizations and save 3.8% of costs.ConclusionsClassifiers learned automatically from patient data can be joined with decision analysis to guide the allocation of post-discharge support to CHF patients. Such analyses are especially valuable in the common situation where it is not economically feasible to provide programs to all patients.

Project description:AimsEconomic burden of heart failure is attributed to hospital readmissions. Previous studies assessing risk factors for readmissions have focused on single group of risk factors, were limited to 30-day readmissions, or did not account for competing risk of mortality. This study investigates the biological, socio-economic, and behavioural risk factors predicting hospital readmissions while accounting for the competing risk of mortality.Methods and resultsIn this prospective cohort study, we recruited 250 patients hospitalized with symptoms of advanced heart failure [New York Heart Association (NYHA) Class III and IV] between July 2017 and April 2019. We analysed their baseline survey data and their hospitalization records over the next 4.5 years (July 2017 to January 2022). We used a joint-frailty model to determine the multifactorial risk factors for all-cause and unplanned hospital readmissions and mortality. At the time of recruitment, patients' mean (SD) age was 66 (12) years, majority being male (72%) and NYHA class IV (68%) with reduced ejection fraction (72%). 87% of the patients had poor self-care behaviours, 51% had diabetes and 56% had weak grip strength. Within 2 years of a hospital admission, 74% of the patients had at least one readmission. Among all readmissions during follow-up, 68% were unplanned. Results from the multivariable regression analysis shows that the independent risk factors for hospital readmissions were biologic-weak grip strength [hazard ratio (95% CI): 1.59 (1.06, 2.13)], poor functional status [1.79 (0.98, 2.61)], diabetes [1.42 (0.97, 1.86)]; behavioural-poor self-care [1.66 (0.84, 2.49)], and socio-economic-preference for maximal life extension at high cost for those with high education [1.98 (1.17, 2.80)]. Risk factors for unplanned hospital readmissions were similar. A higher hospital readmission rate increased the risk of mortality [1.86 (1.23, 2.50)]. Other risk factors for mortality were biologic-weak grip strength [3.65 (0.57, 6.73)], diabetes [2.52 (0.62, 4.42)], socio-economic-lower education [2.45 (0.37, 4.53)], and being married [2.53 (0.37, 4.69)]. Having a private health insurance [0.40 (0.08, 0.73)] lowered the risk for mortality.ConclusionsRisk factors for hospital readmissions and mortality are multifactorial. Many of these factors, such as weak grip strength, diabetes, poor self-care behaviours, are potentially modifiable and should be routinely assessed and managed in cardiac clinics and hospital admissions.

Dataset Information

Factors related to early readmissions after acute heart failure: a nested case-control study.

Aims

Methods and results

Conclusion

Trial registration

Publications

Factors related to early readmissions after acute heart failure: a nested case-control study.

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