Heart rhythm · 2026
A novel predictive model for left atrial low-voltage areas in paroxysmal atrial fibrillation.
СтатьяМногоцентровое исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Zhang Baowei, Wu Yizhang, Zhang Youming, Wang Rui, Xie Xin, Zhou Jian, Zhao Mingzhe, Liang Lin, Yu Jinbo, Li Xiaorong, Liu Zongjun, Sun Jian, Chen Songwen, Yang Bing
Аннотация
BACKGROUND: Left atrial low-voltage areas (LVAs), indicative of atrial fibrosis and structural remodeling, are present in a subset of patients with paroxysmal atrial fibrillation (AF).
OBJECTIVE: This study aimed to develop and validate a novel predictive model for identifying LVAs in patients with paroxysmal AF.
METHODS: Patients with paroxysmal AF receiving their initial radiofrequency ablation in the Department of Cardiology at Shanghai East Hospital were enrolled. LVAs were defined as regions with a bipolar voltage of <0.5 mV during left atrial voltage mapping. Logistic regression analysis was used to identify independent predictors and construct the prediction model. An independent prospective cohort and a multicenter cohort of patients with paroxysmal AF were used for validation.
RESULTS: A total of 383 patients with paroxysmal AF were enrolled, of whom 104 patients (27.2%) had left atrial LVAs. Multivariate logistic regression analysis identified that female sex, prior stroke, left atrial diameter, PR interval, hemoglobin level, and serum creatinine level were independent predictors of LVAs. The HeSLeF-PC (Hemoglobin, Stroke, Left atrial diameter, Female, PR interval, Creatinine) score was developed on the basis of these factors, which could predict the presence of left atrial LVAs in patients with paroxysmal AF (area under the receiver operating characteristic curve [AUROC] 0.810; 95% confidence interval [CI] 0.762-0.859) and was further validated in the prospective cohort (AUROC 0.826; 95% CI 0.757-0.896) and the multicenter cohort (AUROC 0.767; 95% CI 0.678-0.857). Decision curve analysis confirmed its clinical utility.
CONCLUSION: The HeSLeF-PC score could effectively predict the presence of left atrial LVAs in patients with paroxysmal AF and may assist in preprocedural risk stratification and ablation planning.
OBJECTIVE: This study aimed to develop and validate a novel predictive model for identifying LVAs in patients with paroxysmal AF.
METHODS: Patients with paroxysmal AF receiving their initial radiofrequency ablation in the Department of Cardiology at Shanghai East Hospital were enrolled. LVAs were defined as regions with a bipolar voltage of <0.5 mV during left atrial voltage mapping. Logistic regression analysis was used to identify independent predictors and construct the prediction model. An independent prospective cohort and a multicenter cohort of patients with paroxysmal AF were used for validation.
RESULTS: A total of 383 patients with paroxysmal AF were enrolled, of whom 104 patients (27.2%) had left atrial LVAs. Multivariate logistic regression analysis identified that female sex, prior stroke, left atrial diameter, PR interval, hemoglobin level, and serum creatinine level were independent predictors of LVAs. The HeSLeF-PC (Hemoglobin, Stroke, Left atrial diameter, Female, PR interval, Creatinine) score was developed on the basis of these factors, which could predict the presence of left atrial LVAs in patients with paroxysmal AF (area under the receiver operating characteristic curve [AUROC] 0.810; 95% confidence interval [CI] 0.762-0.859) and was further validated in the prospective cohort (AUROC 0.826; 95% CI 0.757-0.896) and the multicenter cohort (AUROC 0.767; 95% CI 0.678-0.857). Decision curve analysis confirmed its clinical utility.
CONCLUSION: The HeSLeF-PC score could effectively predict the presence of left atrial LVAs in patients with paroxysmal AF and may assist in preprocedural risk stratification and ablation planning.