Identifying patients hospitalized with heart failure at risk for unfavorable future quality of life

Larry A Allen, Mihai Gheorghiade, Kimberly J Reid, Shannon M Dunlay, Paul S Chan, Paul J Hauptman, Faiez Zannad, Marvin A Konstam, John A Spertus, Larry A Allen, Mihai Gheorghiade, Kimberly J Reid, Shannon M Dunlay, Paul S Chan, Paul J Hauptman, Faiez Zannad, Marvin A Konstam, John A Spertus

Abstract

Background: Communicating prognosis to enable shared decision-making is strongly endorsed by heart failure (HF) guidelines. Patients are concerned with both their quantity and quality of life (QoL). To facilitate the recognition of patients at high risk for unfavorable future QoL or death, we created a simple prognostic tool to estimate this combined outcome.

Methods and results: We identified factors associated with 6-month mortality or persistently unfavorable QoL, defined by Kansas City Cardiomyopathy Questionnaire (KCCQ) scores <45 at 1 and 24 weeks after hospital discharge, among 1458 patients from the Efficacy of Vasopressin Antagonism in HF Outcome Study with Tolvaptan (EVEREST). Within 24 weeks of discharge, 478 (32.8%) patients had died and 192 (13.2%) patients had serial KCCQ scores <45. After adjusting for 23 predischarge covariates, independent predictors of the combined end point included low admission KCCQ score, high B-type natriuretic peptide, hyponatremia, tachycardia, hypotension, absence of β-blocker therapy, and history of diabetes mellitus and arrhythmia. A simplified predischarge HF score for subsequent death or unfavorable QoL had moderate discrimination (c-statistic 0.72). Predischarge clinical covariates were substantially different in predicting the QoL end point as compared with traditional death or rehospitalization end points.

Conclusions: At the time of hospital discharge, readily available clinical characteristics are associated with HF patients at high risk for persistently unfavorable QoL or death over the next 6 months. Such information can target patients for whom aggressive treatment options (eg, devices or transplantation) and/or end-of-life discussions should be strongly considered before hospital discharge.

Trial registration: ClinicalTrials.gov NCT00071331.

Conflict of interest statement

Conflict of Interest Disclosures: The EVEREST trial was funded by Otsuka. Otsuka did not participate in the analysis or interpretation of the data for this post hoc analysis, and Otsuka had no role in the preparation, review, or approval of this manuscript. Dr Gheorghiade reports receiving research grants from research grants from the National Institutes of Health, Otsuka, Sigma Tau, Merck, and Scios Inc; being a consultant for Debbio Pharm, Errekappa Terapeutici, GlaxoSmithKline, Protein Design Laboratories, and Medtronic; and receiving honoraria from Abbott, AstraZeneca, GlaxoSmithKline, Medtronics, Otsuka, Protein Design Laboratories, Scios Inc, and Sigma Tau. Dr Hauptman reports being a member of the EVEREST CEC and consultant to Otsuka. Dr Zannad reports receiving research grants from Bayer; being a consultant for Servier and Johnson & Johnson; and receiving honoraria from AstraZeneca, Pfizer, Boehringer Ingelheim, Novartis, Abbott, Sanofi-Aventis, and Otsuka. Dr Konstam reports research grants and contracts from, being a consultant for, and receiving honoraria from Otsuka. Dr. Spertus owns the copyright for the KCCQ and reports having been a consultant for Otsuka in the past.

Figures

Figure 1
Figure 1
Distribution of patients with KCCQ =45 at 1 week post discharge and 24 weeks post discharge.
Figure 2
Figure 2
The refractory heart failure score: a reduced model with a simplified clinical risk score predicting unfavorable future health status, defined as death or KCCQ persistently

Figure 3

Distribution of refractory heart failure…

Figure 3

Distribution of refractory heart failure risk scores and their probabilities

Figure 3
Distribution of refractory heart failure risk scores and their probabilities

Figure 4

Separate adjusted multivariable risk models…

Figure 4

Separate adjusted multivariable risk models for the association of in-hospital clinical covariates with…

Figure 4
Separate adjusted multivariable risk models for the association of in-hospital clinical covariates with selected 24-week outcomes.

Figure 5

Relative prognostic contribution of various…

Figure 5

Relative prognostic contribution of various in-hospital clinical covariates with selected 24-week outcomes as…

Figure 5
Relative prognostic contribution of various in-hospital clinical covariates with selected 24-week outcomes as assessed by F-testing.
Figure 3
Figure 3
Distribution of refractory heart failure risk scores and their probabilities
Figure 4
Figure 4
Separate adjusted multivariable risk models for the association of in-hospital clinical covariates with selected 24-week outcomes.
Figure 5
Figure 5
Relative prognostic contribution of various in-hospital clinical covariates with selected 24-week outcomes as assessed by F-testing.

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