Clinical significance of machine learning algorithm in predicting PPM during TAVR in small annuli
Yu Mao1, Yang Liu1, Mengen Zhai1
1Department of Cardiovascular Surgery, Xijing Hospital, 127 Changle West Road, Xi'an, 710032, Shaanxi, China.
Abstract:
Compared with left heart catheterization (LHC), the pressure gradient of an aortic valve (PGAV) measured by echocardiography during transcatheter aortic valve replacement (TAVR) in small annuli is overestimated. The purpose of this study was to improve the accuracy of PGAV measurements by echocardiography in small annuli and to evaluate the influence of PGAV on prognosis. The internal derivation cohort included 273 consecutive patients with aortic stenosis and a small annulus (computed tomographic scan showing an annulus circumference < 72 mm or area < 400 mm2) who underwent TAVR. Patients completed transthoracic echocardiography (TTE) and LHC measurements during TAVR, and an extreme gradient boosting (XGBoost) algorithm was trained. The primary outcome was a composite end point of all-cause mortality and readmission for heart failure. The mean PGAV level measured by TTE was overestimated compared to the LHC measurement {52.5 [interquartile range: 47.5-57.0] mmHg vs. 42.5 (interquartile range: 38.0-46.0) mmHg, P < 0.001}. After adjustments to the XGBoost, the mean PGAV measured by TTE could be significantly improved [Pearson correlation coefficient = 0.94, P < 0.001]. Importantly, patients with a predicted mean PGAV ≥ 68.6 mmHg showed a significantly increased incidence of composite end points at 2 years after the procedures (40.7% vs. 16.0%, P < 0.001). The XGBoost model could effectively improve the accuracy of the mean PGAV measured by TTE during TAVR, and the predicted mean increase in the PGAV level may lead to a worse prognosis.Clinical Trial Registration: ClinicalTrials.gov Protocol Registration System (NCT05044338).
Insights
Echocardiography overestimates aortic valve gradients in small annuli during TAVR. An XGBoost model improved accuracy, showing higher predicted gradients correlate with worse patient prognosis.
Area of Science:
- Cardiology
- Medical Imaging
- Artificial Intelligence in Medicine
Background:
- Accurate measurement of aortic valve pressure gradient (PG_AV) is crucial for transcatheter aortic valve replacement (TAVR) outcomes.
- Echocardiography often overestimates PG_AV in patients with small aortic annuli compared to left heart catheterization (LHC).
Purpose of the Study:
- To enhance the accuracy of PG_AV measurements using echocardiography in small annuli during TAVR.
- To assess the prognostic impact of accurately measured PG_AV on patient outcomes.
Main Methods:
- Trained an extreme gradient boosting (XGBoost) algorithm on data from 273 patients with aortic stenosis and small annuli undergoing TAVR.
- Compared PG_AV measurements from transthoracic echocardiography (TTE) with LHC data.
- Evaluated the association between predicted PG_AV and a composite endpoint of mortality and heart failure readmission.
Main Results:
- Baseline TTE measurements of PG_AV were significantly overestimated compared to LHC (52.5 mmHg vs. 42.5 mmHg, P < 0.001).
- The XGBoost model significantly improved TTE PG_AV accuracy (Pearson correlation coefficient = 0.94, P < 0.001).
- Patients with a predicted mean PG_AV ≥ 68.6 mmHg had a substantially higher incidence of composite endpoints at 2 years (40.7% vs. 16.0%, P < 0.001).
Conclusions:
- The XGBoost model effectively improves the accuracy of echocardiographic PG_AV measurements during TAVR in small annuli.
- An elevated predicted PG_AV, accurately measured, is associated with a worse prognosis in TAVR patients.
- Improved PG_AV measurement accuracy can aid in better patient selection and risk stratification for TAVR.
