A QRS-corrected predictive formula for coronary CT angiography eliminated diastolic rest period overestimation bias in CLBBB patients (mean error -6.9 ms, p=0.176; RMSE 21.2 ms).
Observational (n=94)
Does a QRS-corrected predictive model improve the accuracy of diastolic rest period prediction for CCTA in patients with CLBBB compared to the conventional formula?
A simple QRS-corrected formula accurately predicts the optimal diastolic resting phase for CCTA in patients with complete left bundle branch block, eliminating the overestimation bias of conventional formulas.
Absolute Event Rate: -6.9% vs 37.9%
p-value: p=0.176
Background: Optimal phase selection in coronary computed tomography angiography (CCTA) is crucial. While the mid-diastolic slow-filling (SF) phase is typically predicted using a conventional formula based on heart rate and atrioventricular conduction time, its validity in complete left bundle branch block (CLBBB)—where pronounced QRS prolongation induces severe mechanical dyssynchrony—remains unclear. We evaluated the impact of bundle branch block on cardiac-phase selection and validated a QRS-corrected predictive model. Methods: We retrospectively analyzed 94 patients (sinus rhythm, n = 40; complete right bundle branch block CRBBB, n = 36; CLBBB, n = 18). Measured SF at the proximal right coronary artery was compared against predictions from the conventional formula (SF = −362 + 0.742 × RR − PQ) and a proposed QRS-corrected formula incorporating a “−(QRS − 100)” subtraction. To test the necessity of a novel model, regression analyses were reconstructed exclusively for the CLBBB cohort. Results: In CLBBB patients, the conventional formula critically overestimated SF by an average of 37.9 ms (RMSE 42.5 ms). Reconstructing simple and multivariate regression models exclusively for the CLBBB group yielded coefficients remarkably similar to the conventional formula, indicating that the fundamental physiological dependency on RR and PQ intervals remains intact despite the bundle branch block. Crucially, the simple proposed QRS-corrected formula successfully eliminated the overestimation bias (mean error −6.9 ms; p = 0.176) and demonstrated the highest predictive accuracy (RMSE 21.2 ms). Conclusions: A completely new predictive regression model is unnecessary for CLBBB patients. Simply incorporating a theoretical subtraction of pathological QRS prolongation optimally corrects the diastolic resting phase.
Morioka et al. (Mon,) conducted a observational in Complete Left Bundle Branch Block (n=94). QRS-corrected predictive formula vs. Conventional formula was evaluated on Prediction error of the mid-diastolic slow-filling phase (p=0.176). A QRS-corrected predictive formula for coronary CT angiography eliminated diastolic rest period overestimation bias in CLBBB patients (mean error -6.9 ms, p=0.176; RMSE 21.2 ms).
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