Key result
Automated hemodynamic assessment matches manual analysis for detecting relevant paravalvular regurgitation after TAVR.
Why the study?
Periprocedural monitoring of invasive hemodynamics shows promise for diagnosing paravalvular regurgitation after TAVR, but automated software options are lacking.
Does an automated rule-based algorithm provide comparable construct validity and discriminatory value for paravalvular regurgitation compared to manual hemodynamic assessment in patients undergoing TAVR?
Observational (n=77)
Does an automated rule-based algorithm provide comparable construct validity and discriminatory value for paravalvular regurgitation compared to manual hemodynamic assessment in patients undergoing TAVR?
Absolute Event Rate: 0.81% vs 0.8%
An automated algorithm for assessing invasive hemodynamics during TAVR is highly valid and comparable to manual assessment for detecting paravalvular regurgitation, facilitating real-time risk stratification.
Supports automated hemodynamic assessment during TAVR; leaves open prospective validation for real-time risk stratification.
Aims: Paravalvular regurgitation (PVR) is frequently observed following Transcatheter Aortic Valve Replacement (TAVR). Periprocedural monitoring of invasive hemodynamics has shown promise for diagnosis of PVR, but automated software options are lacking. We aimed to develop a rule-based algorithm for automated assessment of hemodynamic indices of PVR, and evaluate its construct validity and discriminatory value for cardiac magnetic resonance (CMR)-derived relevant PVR compared to standard manual hemodynamic assessment. Methods and results: Left ventricular and aortic pressures were invasively measured during TAVR using fluid-filled pigtail catheters. To evaluate construct validity of automated vs. manual assessment of invasive hemodynamics, we compared (i) proportion of cardiac cycles affected by arrhythmias/noise, (ii) pressure gradients, and (iii) PVR indices. Additionally, we compared the discriminatory value of automatically and manually determined PVR indices for CMR-determined relevant PVR at 30-days. In total, 77 patients were enrolled (664 cardiac cycles). Automated filtering of cardiac cycles affected by arrhythmias/noise had a high sensitivity (95.2%) and specificity (86.4%). In addition, excellent agreement was observed between automated and manual computation of mean gradients pre- and post-TAVR [39.3 ± 12.1 vs. 37.5 ± 11.9 mmHg, intra-class correlation coefficient (ICC): 0.916; 1.92 ± 5.87 vs. 1.14 ± 5.89, ICC: 0.957, respectively], and PVR indices [diastolic delta (DD): 41.7 ± 12.4 vs. 40.6 ± 12.3 mmHg, ICC: 0.982, respectively]. Automated and manual assessment of DD showed comparable discriminatory value for relevant PVR [area under the curve (AUC): 0.81 vs. 0.80, respectively]. Conclusion: Rule-based, automated assessment of hemodynamic indices of PVR showed excellent construct validity and discriminatory value for CMR-determined relevant PVR, supporting its use for real-time evaluation and risk stratification in TAVR patients.
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Stens et al. (2025) conducted an observational in Paravalvular regurgitation following Transcatheter Aortic Valve Replacement (n=77). Automated assessment of hemodynamic indices vs. Standard manual hemodynamic assessment was evaluated on Discriminatory value for CMR-determined relevant PVR (AUC of diastolic delta). Automated assessment of hemodynamic indices showed comparable discriminatory value to manual assessment for CMR-determined relevant PVR at 30 days (AUC 0.81 vs 0.80).
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