Heart failure & cardiomyopathiesDiagnostic or prognostic study
Evaluation of large-scale plasma proteomics for prediction of heart failure in individuals with a full range of glucose metabolism profiles
- Prognostic cohort study
- UK Biobank
- discovery and validation cohorts
Authors' conclusion
This study identified plasma protein biomarkers linked to HF development in abnormal glucose metabolism population and established the predictive models.
Study context
- Population
- UK Biobank participants with abnormal glucose metabolism and no prior heart failure (HF)discovery 6517, validation 2783
- Comparison
- Protein-panel-clinical-factors (PPCF) model vs clinical factors-only model
- Outcome
- Incident HF
- Follow-up
- Median 13.90 years
Performance
HF prediction in validation cohort
AUC improvement
0.05
P < 0.001
By group
PPCF
0.823 (95% CI: 0.785-0.860)
AUC
As reported in the abstract
Further findings
| Outcome | PPCF | Clinical factors-only model |
|---|---|---|
| HF prediction in general population (n = 23 107) | ||
| AUC | 0.807 (95% CI: 0.786-0.829) | Not reported in the abstract |
Net benefit (decision curve)
- Protein panel model and PPCF model superior net benefits over clinical factors model in abnormal glucose metabolism population
Original publication
Evaluation of large-scale plasma proteomics for prediction of heart failure in individuals with a full range of glucose metabolism profiles. Eur J Prev Cardiol. Published 25 June 2025. doi:10.1093/eurjpc/zwaf381
Summarised from the published abstract; every number is checked against it