Key result
Machine learning model using left atrial dimensions predicts 1-year AF recurrence with ~0.80 test AUC.
Why the study?
Left atrial anteroposterior diameter may incompletely reflect atrial enlargement when assessing AF recurrence risk after thoracoscopic ablation, while volumetric assessment has equipment- and operator-related limitations.
Does a random survival forest model incorporating both left atrial anteroposterior and superoinferior diameters accurately predict 1-year atrial fibrillation recurrence in patients undergoing left unilateral thoracoscopic ablation?
Observational (n=563)
No
Does a random survival forest model incorporating both left atrial anteroposterior and superoinferior diameters accurately predict 1-year atrial fibrillation recurrence in patients undergoing left unilateral thoracoscopic ablation?
Combining left atrial anteroposterior and superoinferior diameters in a machine learning model and risk score (LATA) provides good discrimination for predicting 1-year atrial fibrillation recurrence after thoracoscopic ablation.
Answers are grounded in this paper and cite their sources.
May support refined post-thoracoscopic ablation risk stratification; extends LA diameter use but remains hypothesis-generating pending prospective validation.
Background: Left atrial anteroposterior diameter (LAAP) is commonly used to assess left atrial remodeling and recurrence risk after thoracoscopic atrial fibrillation (AF) ablation, but may incompletely reflect atrial enlargement, whereas volumetric assessment has equipment- and operator-related limitations. Our study aimed to develop a prediction approach for AF recurrence by incorporating complementary left atrial diameters. Methods: This single-center retrospective study included 563 patients undergoing left unilateral thoracoscopic ablation, with 430 patients from January 2018 to December 2022 assigned to the training set and 133 patients from January 2023 to December 2024 assigned to the testing set. Model development was performed in the training cohort. Model performance was evaluated using Harrell’s C-index and receiver operating characteristic curves. The model was further converted into a risk score system (LATA) for clinical application. Results: LAAP and left atrial superoinferior diameter (LASI) were significant predictors of 1-year AF recurrence, with cutoffs of 4.7 cm and 7.0 cm, respectively. An RSF model incorporating six selected variables, including LAAP and LASI, achieved AUCs of 0.834 in training set and 0.795 in testing set. The LATA score showed good discrimination and effectively stratified recurrence risk. Conclusions: Our machine learning model and score system (LATA) combining LAAP and LASI showed favorable predictive performance and potential clinical utility.
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Qiu et al. (2026) conducted an observational in Atrial fibrillation undergoing left unilateral thoracoscopic ablation (n=563). Random survival forest model and LATA score incorporating left atrial anteroposterior (LAAP) and superoinferior (LASI) diameters was evaluated on 1-year atrial fibrillation recurrence (AUC 0.834 (training), AUC 0.795 (testing)). A random survival forest model combining left atrial anteroposterior and superoinferior diameters predicted 1-year AF recurrence with AUCs of 0.834 (training) and 0.795 (testing).
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