{Reference Type}: Journal Article
{Title}: A prediction model for permanent pacemaker implantation after transcatheter aortic valve replacement.
{Author}: Qi Y;Lin X;Pan W;Zhang X;Ding Y;Chen S;Zhang L;Zhou D;Ge J;
{Journal}: Eur J Med Res
{Volume}: 28
{Issue}: 1
{Year}: 2023 Jul 29
{Factor}: 4.981
{DOI}: 10.1186/s40001-023-01237-w
{Abstract}: <B>BACKGROUND: </B>This study aims to develop a post-procedural risk prediction model for permanent pacemaker implantation (PPMI) in patients treated with transcatheter aortic valve replacement (TAVR).<BR><B>METHODS: </B>336 patients undergoing TAVR at a single institution were included for model derivation. For primary analysis, multivariate logistic regression model was used to evaluate predictors and a risk score system was devised based on the prediction model. For secondary analysis, a Cox proportion hazard model was performed to assess characteristics associated with the time from TAVR to PPMI. The model was validated internally via bootstrap and externally using an independent cohort.<BR><B>RESULTS: </B>48 (14.3%) patients in the derivation set had PPMI after TAVR. Prior right bundle branch block (RBBB, OR: 10.46; p < 0.001), pre-procedural aortic valve area (AVA, OR: 1.41; p = 0.004) and post- to pre-procedural AVA ratio (OR: 1.72; p = 0.043) were identified as independent predictors for PPMI. AUC was 0.7 and 0.71 in the derivation and external validation set. Prior RBBB (HR: 5.07; p < 0.001), pre-procedural AVA (HR: 1.33; p = 0.001), post-procedural AVA to prosthetic nominal area ratio (HR: 0.02; p = 0.039) and post- to pre-procedural troponin-T difference (HR: 1.72; p = 0.017) are independently associated with time to PPMI.<BR><B>CONCLUSIONS: </B>The post-procedural prediction model achieved high discriminative power and accuracy for PPMI. The risk score system was constructed and validated, providing an accessible tool in clinical setting regarding the Chinese population.