International journal of cardiology · 2026
PREDICT - patient referral evaluation to determine indication for computed tomography to identify small aortic annulus size in patients with severe aortic stenosis.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Khan Sarosh, Balasubramanian Abhinav, Lim Benjamin, Demir Ozan, Fawaz Samer, Jagathesan Rohan, Aggarwal Rajesh, Gedela Swamy, Farrugia Alexia, Mehmood Muhammad, Nabi Ibraheam, Kharoud Damandeep Singh, Singh Arvind, Jones Richard, Davies John, Keeble Thomas, Costanzo Pierluigi, Cook Christopher M
Аннотация
BACKGROUND: Mitigating prosthesis-patient mismatch (PPM) in surgical or transcatheter aortic valve replacement (SAVR/TAVR) requires early identification of small annulus size (SAS). While computed tomography (CT) is the gold-standard for annular sizing in TAVR, its routine use in SAVR planning is limited by resource constraints.
OBJECTIVES: To develop and validate the Patient Referral Evaluation to Determine Indication for CT (PREDICT) model - a predictive tool utilizing anthropometric and transthoracic echocardiography (TTE)-derived data to identify SAS at the point of referral.
METHODS: This retrospective, multicentre study included 1708 patients with severe aortic stenosis undergoing CT for annular assessment. A development cohort (n = 912) was used to construct the PREDICT multivariate regression model incorporating left ventricular outflow tract diameter (LVOTd), height, and sex. PREDICT performance was evaluated in a separate validation cohort (n = 796) using R2, Bland-Altman analysis, and receiver operating characteristic (ROC) curves. Diagnostic accuracy was assessed for small annulus (≤430mm2), very small annulus (VSAS≤400mm2), and extremely small annulus (ESAS≤370mm2).
RESULTS: In the validation cohort, PREDICT demonstrated good-to-excellent predictive accuracy, with AUCs of 0.838, 0.849, and 0.858 for SAS, VSAS, and ESAS, respectively; outperforming height and LVOTd alone (p < 0.001). Negative predictive values were consistently high, exceeding 88% across all annulus size thresholds, confirming PREDICT's excellent rule-out capability. Bland-Altman analysis showed good agreement with CT (mean bias -7 mm2). Diagnostic performance was unaffected by age or sex (p > 0.40).
CONCLUSIONS: PREDICT is a simple, accurate, non-invasive tool for identifying SAS at referral-optimizing CT use and enabling earlier planning to reduce PPM in severe aortic stenosis patients.
OBJECTIVES: To develop and validate the Patient Referral Evaluation to Determine Indication for CT (PREDICT) model - a predictive tool utilizing anthropometric and transthoracic echocardiography (TTE)-derived data to identify SAS at the point of referral.
METHODS: This retrospective, multicentre study included 1708 patients with severe aortic stenosis undergoing CT for annular assessment. A development cohort (n = 912) was used to construct the PREDICT multivariate regression model incorporating left ventricular outflow tract diameter (LVOTd), height, and sex. PREDICT performance was evaluated in a separate validation cohort (n = 796) using R2, Bland-Altman analysis, and receiver operating characteristic (ROC) curves. Diagnostic accuracy was assessed for small annulus (≤430mm2), very small annulus (VSAS≤400mm2), and extremely small annulus (ESAS≤370mm2).
RESULTS: In the validation cohort, PREDICT demonstrated good-to-excellent predictive accuracy, with AUCs of 0.838, 0.849, and 0.858 for SAS, VSAS, and ESAS, respectively; outperforming height and LVOTd alone (p < 0.001). Negative predictive values were consistently high, exceeding 88% across all annulus size thresholds, confirming PREDICT's excellent rule-out capability. Bland-Altman analysis showed good agreement with CT (mean bias -7 mm2). Diagnostic performance was unaffected by age or sex (p > 0.40).
CONCLUSIONS: PREDICT is a simple, accurate, non-invasive tool for identifying SAS at referral-optimizing CT use and enabling earlier planning to reduce PPM in severe aortic stenosis patients.