SynthesisJournal of the American Heart Association2019
Clinical Prediction Models for Valvular Heart Disease.
Synthesis in Journal of the American Heart Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Systematic review and meta-analysis of prognostic models in Southeast Asian populations with acute myocardial infarction.Frontiers in cardiovascular medicine · 2022Pooled it
- Clinical Predictive Models of Sudden Cardiac Arrest: A Survey of the Current Science and Analysis of Model Performances.Journal of the American Heart Association · 2020Pooled it
- Clinical Prediction Models for Valvular Heart Disease.Journal of the American Heart Association · 2019Pooled it
- Prognostic value of the TAPSE/PASP-ratio in patients with severe mitral regurgitation undergoing transcatheter edge-to-edge mitral valve repair.BMC cardiovascular disorders · 2026Article
- Prediction of long-term survival in patients with concomitant pulmonary hypertension and its subtypes after successful transcatheter edge-to-edge mitral valve repair.Cardiovascular diagnosis and therapy · 2026Article
- A New Risk Score for Predicting Postoperative Mortality in Suspected Heart Failure Patients Undergoing Valvular Surgery.Reviews in cardiovascular medicine · 2023Article
- A novel model for predicting a composite outcome of major complications after valve surgery.Frontiers in cardiovascular medicine · 2023Article
- A systemic congestive index (systemic pulse pressure to central venous pressure ratio) predicts adverse outcomes in patients undergoing valvular heart surgery.Journal of cardiac surgery · 2022Article
- A Survival Prediction for Acute Heart Failure Patients via Web-Based Dynamic Nomogram with Internal Validation: A Prospective Cohort Study.Journal of inflammation research · 2022Article
- Prediction Nomogram for Postoperative 30-Day Mortality in Acute Type A Aortic Dissection Patients Receiving Total Aortic Arch Replacement With Frozen Elephant Trunk Technique.Frontiers in cardiovascular medicine · 2022Article
- External Validations of Cardiovascular Clinical Prediction Models: A Large-Scale Review of the Literature.Circulation. Cardiovascular quality and outcomes · 2021Review
- Cardiac Magnetic Resonance Imaging Right Ventricular Longitudinal Strain Predicts Mortality in Patients Undergoing TAVI.Frontiers in cardiovascular medicine · 2021Article
- A novel nomogram to predict perioperative acute kidney injury following isolated coronary artery bypass grafting surgery with impaired left ventricular ejection fraction.BMC cardiovascular disorders · 2020Article
- Can Clinical Predictive Models Identify Patients Who Should Not Receive TAVR? A Systematic Review.Structural heart : the journal of the Heart Team · 2020Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Background While many clinical prediction models (CPMs) exist to guide valvular heart disease treatment decisions, the relative performance of these CPMs is largely unknown. We systematically describe the CPMs available for patients with valvular heart disease with specific attention to performance in external validations. Methods and Results A systematic review identified 49 CPMs for patients with valvular heart disease treated with surgery (n=34), percutaneous interventions (n=12), or no intervention (n=3). There were 204 external validations of these CPMs. Only 35 (71%) CPMs have been externally validated. Sixty-five percent (n=133) of the external validations were performed on distantly related populations. There was substantial heterogeneity in model performance and a median percentage change in discrimination of -27.1% (interquartile range, -49.4%--5.7%). Nearly two-thirds of validations (n=129) demonstrate at least a 10% relative decline in discrimination. Discriminatory performance of EuroSCORE II and Society of Thoracic Surgeons (2009) models (accounting for 73% of external validations) varied widely: EuroSCORE II validation c-statistic range 0.50 to 0.95; Society of Thoracic Surgeons (2009) Models validation c-statistic range 0.50 to 0.86. These models performed well when tested on related populations (median related validation c-statistics: EuroSCORE II, 0.82 [0.76, 0.85]; Society of Thoracic Surgeons [2009], 0.72 [0.67, 0.79]). There remain few (n=9) external validations of transcatheter aortic valve replacement CPMs. Conclusions Many CPMs for patients with valvular heart disease have never been externally validated and isolated external validations appear insufficient to assess the trustworthiness of predictions. For surgical valve interventions, there are existing predictive models that perform reasonably well on related populations. For transcatheter aortic valve replacement (CPMs additional external validations are needed to broadly understand the trustworthiness of predictions.
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