The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Preferences of Heart Failure Patients in Daily Clinical Practice: Quality of Life or Longevity?
Abstract
AIMS: Knowledge of patient preferences is vital for delivering optimal healthcare. This study uses utility measurement to assess the preferences of heart failure (HF) patients regarding quality of life or longevity. The utility approach represents the perspective of a patient; facilitates the combination of mortality, morbidity, and treatment regimen into a single score; and makes it possible to compare the effects of different interventions in healthcare. METHODS AND RESULTS: Patient preferences of 100 patients with HF were assessed in interviews using the time trade-off (TTO) approach. Health-related quality of life (HR-QoL) was assessed with the EQ-5D and the Minnesota Living with Heart Failure Questionnaire (MLHFQ). Patients' own estimation of life expectancy was assessed with a visual analogue scale (VAS). Of the 100 patients (mean age 70 ± 9 years; 71% male), 61% attach more weight to quality of life over longevity; while 9% and 14% were willing to trade 6 and 12 months, respectively, for perfect health and attach more weight to quality of life. Patients willing to trade time had a significantly higher level of NT-proBNP and reported significantly more dyspnoea during exertion. Predictors of willingness to trade time were higher NT-proBNP and lower EQ VAS. CONCLUSION: The majority of HF patients attach more weight to quality of life over longevity. There was no difference between both groups with respect to life expectancy described by the patients. These insights enable open and personalized discussions of patients' preferences in treatment and care decisions, and could guide the future development of more patient-centred care.
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“Moreover, in patients reaching end of life, PROs could direct medical care away from measures to enhance survival and towards those that enhance remaining life. 118”
From Prioritizing symptom management in the treatment of chronic heart failure (2020) · cites this paper as [118]
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Metadata
- Authors
- Kraai, I. H., Vermeulen, K. M., Luttik, M. L. A., Hoekstra, T., Jaarsma, T., & Hillege, H. L.
- Affiliations
- University Medical Center Groningen (NL)
- Linköping University (SE)
- Corresponding author
- Kraai, Imke H.
- Venue
- European Journal of Heart Failure
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-10-01
- Volume
- 15
- Issue
- 10
- Pages
- 1113-1121
- ISSN
- 1388-9842 (ISSN-L)
- 1879-0844
- OpenAlex
- W2014113395
- Cited by
- 147
- References
- 31
- Citations by year
- 2026: 14 · 2025: 15 · 2024: 16 · 2023: 18 · 2022: 10 · 2021: 11 · 2020: 12 · 2019: 8 · 2018: 6 · 2017: 14 · 2016: 12 · 2015: 9 · 2014: 2
- FWCI
- 17.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Journal of Heart Failure (publishedVersion)
- PubMed (publishedVersion)
- Research Bank (Australian Catholic University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Failure Treatment and Management
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Palliative Care and End-of-Life Issues
- Keywords
- heart failure, patient preferences, quality of life, longevity, time trade-off, health-related quality of life, life expectancy, NT-proBNP, dyspnea, patient-centered care, utility measurement
- MeSH terms
- Aged, Aged, 80 and over, Attitude to Death, Attitude to Health, Depression, Dyspnea, Fatigue, Female, Health Status, Heart Failure, Humans, Longevity, Male, Middle Aged, Quality of Life, Severity of Illness Index, Social Support, Multivariate Analysis, Logistic Models, Patient Preference
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