Department of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, People's Republic of China.
Cardiovasc Drugs Ther. 2023 Dec;37(6):1117-1129. doi: 10.1007/s10557-022-07353-9. Epub 2022 Jun 22.
This study aimed to establish and assess a prediction model for patients with persistent atrial fibrillation (AF) treated with nifekalant during the first radiofrequency catheter ablation (RFCA).
In this study, 244 patients with persistent AF from January 17, 2017 to December 14, 2017, formed the derivation cohort, and 205 patients with persistent AF from December 15, 2017 to October 28, 2018, constituted the validation cohort. The least absolute shrinkage and selection operator regression was used for variable screening and the multivariable Cox survival model for nomogram development. The accuracy and discriminative capability of this predictive model were assessed according to discrimination (area under the curve [AUC]) and calibration. Clinical practical value was evaluated using decision curve analysis.
Body mass index, AF duration, sex, left atrial diameter, and the different responses after nifekalant administration were identified as AF recurrence-associated factors, all of which were selected for the nomogram. In the development and validation cohorts, the AUC for predicting 1-year AF-free survival was 0.863 (95% confidence interval (CI) 0.801-0.926) and 0.855 (95% CI 0.782-0.929), respectively. The calibration curves showed satisfactory agreement between the actual AF-free survival and the nomogram prediction in the derivation and validation cohorts. In both groups, the prognostic score enabled stratifying the patients into different AF recurrence risk groups.
This predictive nomogram can serve as a quantitative tool for estimating the 1-year AF recurrence risk for patients with persistent AF treated with nifekalant during the first RFCA.
本研究旨在建立并评估接受尼非卡兰行首次射频导管消融术(RFCA)治疗的持续性心房颤动(AF)患者的预测模型。
本研究纳入了 2017 年 1 月 17 日至 2017 年 12 月 14 日期间的 244 例持续性 AF 患者作为推导队列,以及 2017 年 12 月 15 日至 2018 年 10 月 28 日期间的 205 例持续性 AF 患者作为验证队列。采用最小绝对收缩和选择算子回归进行变量筛选,并采用多变量 Cox 生存模型建立列线图。通过判别(曲线下面积[AUC])和校准评估该预测模型的准确性和判别能力。通过决策曲线分析评估临床实用价值。
体重指数、AF 持续时间、性别、左心房直径以及尼非卡兰给药后的不同反应被确定为 AF 复发相关因素,所有这些因素均被纳入列线图。在推导和验证队列中,预测 1 年 AF 无复发生存率的 AUC 分别为 0.863(95%置信区间[CI] 0.801-0.926)和 0.855(95%CI 0.782-0.929)。校准曲线显示,在推导和验证队列中,实际 AF 无复发生存率与列线图预测之间具有良好的一致性。在两组中,预后评分都可以将患者分为不同的 AF 复发风险组。
该预测列线图可作为一种定量工具,用于评估接受尼非卡兰行首次 RFCA 治疗的持续性 AF 患者 1 年内 AF 复发风险。