PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 10, 2026BMC Cardiovascular Disorders0 citationsOpen Access

Construction and validation of risk prediction models for new- onset conduction block complications after transcatheter aortic valve replacement

LCLei ChenSZShuyi ZengMLMing Li

Key Result

A risk-prediction model incorporating age, basal valve diameter, and annulus size achieved an AUC of 0.988 for predicting conduction block after transcatheter aortic valve replacement.

Key Points

  • The study aims to identify risk factors for new-onset conduction block after transcatheter aortic valve replacement and develop a prediction model.
  • Data of 163 patients who underwent transcatheter aortic valve replacement was collected.
  • LASSO regression analysis was conducted for variable selection.
  • Univariate and multivariate logistic regression analyses were performed to establish the prediction model.
  • A visual nomogram was created based on the selected predictive factors.
  • Model verification included ROC curve, calibration curve, and decision curve analyses.
  • Three predictive factors were identified: age, basal valve diameter, and annulus size.
  • The model had a high predictive ability with an area under the ROC curve of 0.988 (training set) and 0.989 (validation set).
  • The nomogram showed clinical applicability at a risk threshold between 0.1 and 0.7.
  • Incorporating these factors significantly improved prediction accuracy for conduction block.

Structured PICO

P
Population
163 patients with moderate to severe aortic stenosis who underwent transcatheter aortic valve replacement (TAVR) via the femoral artery.
I
Intervention
Transcatheter aortic valve replacement (TAVR) using self-expanding valves (Vitaflow or VenusA-Valve).
O
Outcome
New-onset conduction block after TAVR.safety

A nomogram incorporating age, basal valve diameter, and annulus size accurately predicts the risk of new-onset conduction block following TAVR with self-expanding valves.

Limitations

  • Single-center study

Abstract

To systematically evaluate and model the risk factors for new - onset conduction block after transcatheter aortic valve replacement, aiming to establish a scientific risk - prediction nomogram model. This model is intended to guide clinical screening of high - risk patients, develop more targeted prevention and treatment strategies, and ultimately improve the overall prognosis and quality of life of patients by effectively reducing the incidence of postoperative conduction block. Data of 163 patients who underwent transcatheter aortic valve replacement in our hospital from January 2022 to November 2024 were collected, including patients’ anatomical characteristics, surgical operation parameters, and other self - factors. First, the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis method was used to optimize variable selection. By introducing the predictive factors selected in the LASSO regression analysis, univariate and multivariate logistic regression analyses were then carried out to establish a prediction model. According to the selected variables, a visual nomogram was established. Subsequently, the model was verified by the receiver operating characteristic curve, calibration curve, and decision curve analysis. Through LASSO regression analysis, three predictive factors, namely age, basal valve diameter(mm), and annulus size, were screened out from the 29 variables studied. The model constructed using these three predictive factors had good predictive ability, with an area under the ROC curve of 0.988 in the training set and 0.989 in the validation set. The DCA curve showed that the nomogram could be applied clinically when the risk threshold was between 0.1 and 0.7. Incorporating age, basal valve diameter(mm), and annulus size into the risk - prediction model significantly improves the accuracy of predicting the risk of new - onset conduction block in patients after transcatheter aortic valve replacement. This strategy provides a more reliable basis for preoperative risk stratification and helps optimize clinical decision - making and patient management.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Chen et al. (2025) studied this question. A risk-prediction model incorporating age, basal valve diameter, and annulus size achieved an AUC of 0.988 for predicting conduction block after transcatheter aortic valve replacement.

synapsesocial.com/papers/6963223291e05aa366cb8c88https://doi.org/10.1186/s12872-025-05397-x
Ask AI
Helpful
Bookmark
Share
View Full Paper