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Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation.

ABSTRACT: Outpatients with heart failure (HF) who are at high risk for HF hospitalization and death may benefit from early identification. We sought to develop and externally validate a model to predict both HF hospitalization and mortality that accounts for the semicompeting nature of the 2 outcomes and captures the risk associated with the transition from the stable outpatient state to the post-HF hospitalization state.A multistate model to predict HF hospitalization and all-cause mortality was derived using data (n=3834) from the HEAAL study (Heart Failure Endpoint evaluation of Angiotensin II Antagonist Losartan), a multinational randomized trial in symptomatic patients with reduced left ventricular ejection fraction. Twelve easily and reliably obtainable demographic and clinical predictors were prespecified for model inclusion. Model performance was assessed in the SCD-HeFT cohort (Sudden Cardiac Death in Heart Failure Trial; n=2521). At 1 year, the probability of being alive without HF hospitalization was 94% for a typical patient in the lowest risk quintile and 77% for a typical patient in the highest risk quintile and this variability in risk continued through 7 years of follow-up. The model c-index was 0.72 in the derivation cohort, 0.66 in the validation cohort, and 0.69 in the implantable cardiac defibrillator arm of the validation cohort. There was excellent calibration across quintiles of predicted risk.Our findings illustrate the advantages of a multistate modeling approach, providing estimates of HF hospitalization and death in the same model, comparison of predictors for the different outcomes and demonstrating the different trajectories of patients based on baseline characteristics and intermediary events.URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00000609 and NCT00090259.

SUBMITTER: Upshaw JN

PROVIDER: S-EPMC5328587 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation.

Upshaw Jenica N JN Konstam Marvin A MA Klaveren David van Dv Noubary Farzad F Huggins Gordon S GS Kent David M DM

Circulation. Heart failure 20160801 8

<h4>Background</h4>Outpatients with heart failure (HF) who are at high risk for HF hospitalization and death may benefit from early identification. We sought to develop and externally validate a model to predict both HF hospitalization and mortality that accounts for the semicompeting nature of the 2 outcomes and captures the risk associated with the transition from the stable outpatient state to the post-HF hospitalization state.<h4>Methods and results</h4>A multistate model to predict HF hospi ...[more]

PMID: 27514751

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Project description:AimsThe proportion of patients hospitalized for heart failure (HF) with preserved left ventricular ejection fraction (LVEF) is rising, but no approved treatment exists, in part owing to incomplete characterization of this particular HF phenotype. In order to better define the characteristics of HF phenotypes in Finland, a large cohort with 12 years' follow-up time was analysed.Methods and resultsPatients diagnosed between 2005 and 2017 at the Hospital District of Southwest Finland were stratified according to LVEF measure and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels. For this retrospective registry study, previously diagnosed HF patients were defined as follows: patients with reduced ejection fraction (HFrEF; LVEF ≤ 40%; n = 4042), mid-range ejection fraction (HFmrEF; LVEF > 40-50% and NT-proBNP ≥ 125 pg/mL; n = 1468), and preserved ejection fraction (HFpEF; LVEF > 50% and NT-proBNP ≥ 125 pg/mL; n = 3122) and followed up for 15 022, 4962, and 10 097 patient-years, respectively. Cardiovascular (CV) hospitalization and mortality, influence of pre-selected covariates on hospitalization and mortality, and the proportion of HFpEF and HFmrEF patients with a drop in LVEF to HFrEF phenotype were analysed. All data were extracted from the electronic patient register. HFrEF patients were rehospitalized slightly earlier than HFpEF/HFmrEF patients, but the second, third, and fourth rehospitalization rates did not differ between the subgroups. Female gender and better kidney function were associated with reduced rehospitalizations in HFmrEF and HFrEF, with a non-significant trend in HFpEF. Each additional hospitalization was associated with a two-fold increased risk of death and 2.2- to 2.3-fold increased risk of CV death. All-cause mortality was higher in patients with HFpEF. Although CV mortality was less frequent in HFpEF patients, it was associated with increased NT-proBNP concentrations at index in all patient groups. During the 10 years following the index date, 26% of HFmrEF patients and 10% of HFpEF patients progressed to an HFrEF phenotype.ConclusionsThese findings suggest that disease progression, in terms of increased frequency of hospitalizations, and the relationship between increased number of hospitalizations and mortality are similar by LVEF phenotypes. These data highlight the importance of effective treatments that can reduce hospitalizations and suggest a role for monitoring NT-proBNP levels in the management of HFpEF patients in particular.

Project description:Aims: Evidence-based guidelines for heart failure management depend mainly on current left ventricular ejection fraction (LVEF). However, fewer studies have examined the impact of prior LVEF. Patients may enter the heart failure with midrange ejection fraction (HFmrEF) category when heart failure with preserved ejection fraction (HFpEF) deteriorates or heart failure with reduced ejection fraction (HFrEF) improves. In this study, we examined the association between change in LVEF and adverse outcomes. Methods: HFmrEF patients with at least two or more echocardiograms 3 months apart at the First Affiliated Hospital of Dalian Medical University between September 1, 2015 and November 30, 2019 were identified. According to the prior LVEF, the subjects were divided into improved group (prior LVEF < 40%), stable group (prior LVEF between 40 and 50%), and deteriorated group (prior LVEF ≥ 50%). The primary outcomes were cardiovascular death, all-cause mortality, hospitalization for worsening heart failure, and composite event of all-cause mortality or all-cause hospitalization. Results: A total of 1,168 HFmrEF patients (67.04% male, mean age 63.60 ± 12.18 years) were included. The percentages of improved, stable, and deteriorated group were 310 (26.54%), 334 (28.60%), and 524 (44.86%), respectively. After a period of follow-up, 208 patients (17.81%) died and 500 patients met the composite endpoint. The rates of all-cause mortality were 35 (11.29%), 55 (16.47%), and 118 (22.52%), and the composite outcome was 102 (32.90%), 145 (43.41%), and 253 (48.28%) for the improved, stable, and deteriorated groups, respectively. Cox regression analysis showed that the deterioration group had higher risk of cardiovascular death (HR: 1.707, 95% CI: 1.064-2.739, P = 0.027), all-cause death (HR 1.948, 95% CI 1.335-2.840, P = 0.001), and composite outcome (HR 1.379, 95% CI 1.096-1.736, P = 0.006) compared to the improvement group. The association still remained significant after fully adjusted for both all-cause mortality (HR = 1.899, 95% CI 1.247-2.893, P = 0.003) and composite outcome (HR: 1.324, 95% CI: 1.020-1.718, P = 0.035). Conclusion: HFmrEF patients are heterogeneous with three different subsets identified, each with different outcomes. Strategies for managing HFmrEF should include previously measured LVEF to allow stratification based on direction changes in LVEF to better optimize treatment.

Dataset Information

Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation.

Publications

Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation.

Similar Datasets

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