Multimorbidity in Heart Failure: Leveraging Cluster Analysis to Guide Tailored Treatment Strategies

Publication date

2023-10

Authors

van de Veerdonk, Mariëlle C
Savarese, Gianluigi
Handoko, M L
Beulens, JolineISNI 0000000393357801
Asselbergs, Folkert WORCID 0000-0002-1692-8669ISNI 0000000391548591
Uijl, AliciaORCID 0000-0003-2835-7741

Editors

Advisors

Supervisors

Document Type

Article

Collections

Open Access logo

License

cc_by

Abstract

Review Purpose: This review summarises key findings on treatment effects within phenotypical clusters of patients with heart failure (HF), making a distinction between patients with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF). Findings: Treatment response differed among clusters; ACE inhibitors were beneficial in all HFrEF phenotypes, while only some studies show similar beneficial prognostic effects in HFpEF patients. Beta-blockers had favourable effects in all HFrEF patients but not in HFpEF phenotypes and tended to worsen prognosis in older, cardiorenal patients. Mineralocorticoid receptor antagonists had more favourable prognostic effects in young, obese males and metabolic HFpEF patients. While a phenotype-guided approach is a promising solution for individualised treatment strategies, there are several aspects that still require improvements before such an approach could be implemented in clinical practice. Summary: Stronger evidence from clinical trials and real-world data may assist in establishing a phenotype-guided treatment approach for patient with HF in the future.

Keywords

Clustering, Heart failure, Machine learning, Phenotyping, Precision medicine, Treatment response, Journal Article, Review

Citation

van de Veerdonk, M C, Savarese, G, Handoko, M L, Beulens, J W J, Asselbergs, F & Uijl, A 2023, 'Multimorbidity in Heart Failure : Leveraging Cluster Analysis to Guide Tailored Treatment Strategies', Current Heart Failure Reports, vol. 20, no. 5, pp. 461-470. https://doi.org/10.1007/s11897-023-00626-w