Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning.
Heart
; 106(5): 342-349, 2020 03.
Article
em En
| MEDLINE
| ID: mdl-31911501
ABSTRACT
OBJECTIVE:
Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome. We aimed to derive HFpEF phenotype-based groups ('phenogroups') based on clinical and echocardiogram data using machine learning, and to compare clinical characteristics, proteomics and outcomes across the phenogroups.METHODS:
We applied model-based clustering to 32 echocardiogram and 11 clinical and laboratory variables collected in stable condition from 320 HFpEF outpatients in the Karolinska-Rennes cohort study (56% female, median 78 years (IQR 71-83)). Baseline proteomics and the composite end point of all-cause mortality or heart failure (HF) hospitalisation were used in secondary analyses.RESULTS:
We identified six phenogroups, for which significant differences in the prevalence of concomitant atrial fibrillation (AF), anaemia and kidney disease were observed (p<0.05). Fifteen out of 86 plasma proteins differed between phenogroups (false discovery rate, FDR<0.05), including biomarkers of HF, AF and kidney function. The composite end point was significantly different between phenogroups (log-rank p<0.001), at short-term (100 days), mid-term (18 months) and longer-term follow-up (1000 days). Phenogroup 2 was older, with poorer diastolic and right ventricular function and higher burden of risk factors as AF (85%), hypertension (83%) and chronic obstructive pulmonary disease (30%). In this group a third experienced the primary outcome to 100 days, and two-thirds to 18 months (HR (95% CI) versus phenogroups 1, 3, 4, 5, 6 1.5 (0.8-2.9); 5.7 (2.6-12.8); 2.9 (1.5-5.6); 2.7 (1.6-4.6); 2.1 (1.2-3.9)).CONCLUSIONS:
Using machine learning we identified distinct HFpEF phenogroups with differential characteristics and outcomes, as well as differential levels of inflammatory and cardiovascular proteins.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Volume Sistólico
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Insuficiência Cardíaca
Tipo de estudo:
Diagnostic_studies
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Etiology_studies
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Incidence_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Aged
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Aged80
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Female
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Humans
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Male
Idioma:
En
Revista:
Heart
Assunto da revista:
CARDIOLOGIA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Suécia