ArticleEuropean journal of heart failure2022
Incorporation of natriuretic peptides with clinical risk scores to predict heart failure among individuals with dysglycaemia.
Article in European journal of heart failure, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.
- Risk prediction models for detecting a new diagnosis of heart failure within 5 years in the community: a systematic review.BMJ open · 2026Pooled it
- The WATCH-DM risk score estimates clinical outcomes in type 2 diabetic patients with heart failure with preserved ejection fraction.Scientific reports · 2024Pooled it
- Prediction of incident heart failure in type 2 diabetes mellitus: Rationale and design of the DM-HEART study.Journal of diabetes investigation · 2026Article
- The WATCH-DM integer-based risk score identifies risk of all-cause mortality in patients with type 2 diabetes: a retrospective cohort study.Therapeutic advances in endocrinology and metabolism · 2026Article
- Screening Natriuretic Peptide Levels Predicts Heart Failure and Death in Individuals With Type 1 and Type 2 Diabetes Without Known Heart Failure.Diabetes care · 2025Article
- AI Tools for Heart Failure Management: A Comprehensive Review of Potential, Pitfalls, and Predictive Analytics.Cureus · 2025Review
- 2024 update in heart failure.ESC heart failure · 2025Review
- The Balance Between the Natriuretic Peptides and the Renin-Angiotensin-Aldosterone System in the Preservation of Ideal Cardiovascular Health.Journal of clinical medicine · 2025Review
- Artificial Intelligence to Diagnose Complications of Diabetes.Journal of diabetes science and technology · 2025Review
- Machine learning in the prevention of heart failure.Heart failure reviews · 2025Review
- Type 2 diabetes mediated heart failure: focus on early recognition and clinical strategies.Frontiers in endocrinology · 2025Review
- Artificial intelligence bias in the prediction and detection of cardiovascular disease.NPJ cardiovascular health · 2024Review
- Cardiovascular Disease Management With Sodium-Glucose Cotransporter-2 Inhibitors in Patients With Type 2 Diabetes: A Cardiology Primer.Texas Heart Institute journal · 2024Review
- Article
- Global historical retrospect and future prospects on biomarkers of heart failure: A bibliometric analysis and science mapping.Heliyon · 2023Article
- Heart failure: an update from the last years and a look at the near future.ESC heart failure · 2022Review
- The Texas Health Resources Clinical Scholars Program: Learning healthcare system workforce development through embedded translational research.Learning health systems · 2022Article
- Validation of the WATCH-DM and TRS-HFJournal of the American Heart Association · 2022Article
- Prioritizing the primary prevention of heart failure: Measuring, modifying and monitoring risk.Progress in cardiovascular diseasesReview
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Authors and funding
14 authors at 7 institutions in 1 country.
Funding
Abstract
aimsTo evaluate the performance of the WATCH-DM risk score, a clinical risk score for heart failure (HF), in patients with dysglycaemia and in combination with natriuretic peptides (NPs). METHODS AND
resultsAdults with diabetes/pre-diabetes free of HF at baseline from four cohort studies (ARIC, CHS, FHS, and MESA) were included. The machine learning- [WATCH-DM(ml)] and integer-based [WATCH-DM(i)] scores were used to estimate the 5-year risk of incident HF. Discrimination was assessed by Harrell's concordance index (C-index) and calibration by the Greenwood-Nam-D'Agostino (GND) statistic. Improvement in model performance with the addition of NP levels was assessed by C-index and continuous net reclassification improvement (NRI). Of the 8938 participants included, 3554 (39.8%) had diabetes and 432 (4.8%) developed HF within 5 years. The WATCH-DM(ml) and WATCH-DM(i) scores demonstrated high discrimination for predicting HF risk among individuals with dysglycaemia (C-indices = 0.80 and 0.71, respectively), with no evidence of miscalibration (GND P ≥0.10). The C-index of elevated NP levels alone for predicting incident HF among individuals with dysglycaemia was significantly higher among participants with low/intermediate (<13) vs. high (≥13) WATCH-DM(i) scores [0.71 (95% confidence interval 0.68-0.74) vs. 0.64 (95% confidence interval 0.61-0.66)]. When NP levels were combined with the WATCH-DM(i) score, HF risk discrimination improvement and NRI varied across the spectrum of risk with greater improvement observed at low/intermediate risk [WATCH-DM(i) <13] vs. high risk [WATCH-DM(i) ≥13] (C-index = 0.73 vs. 0.71; NRI = 0.45 vs. 0.17).
conclusionThe WATCH-DM risk score can accurately predict incident HF risk in community-based individuals with dysglycaemia. The addition of NP levels is associated with greater improvement in the HF risk prediction performance among individuals with low/intermediate risk than those with high risk.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.