Zhang Xiaoting, Wei Meng, Xue Pengjie, Lu Yanmei, Tang Baopeng
Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830000, China.
Xinjiang Key Laboratory of Cardiac Electrophysiology and Cardiac Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830000, China.
BMC Cardiovasc Disord. 2025 Apr 23;25(1):308. doi: 10.1186/s12872-025-04696-7.
The high prevalence of atrial fibrillation (AF) and obstructive sleep apnea syndrome (OSAS) imposes a substantial disease burden on public healthcare, making it a significant health concern in the current era. However, there is currently a lack of risk assessment tools for AF recurrence in patients with AF and OSAS. Therefore, this study aims to explore the factors influencing AF recurrence in patients with AF and OSAS, and to establish a predictive model and scoring system for AF recurrence rates.
The study included a total of 423 patients with AF and OSAS, who were randomly divided into train set (n = 296) and test set (n = 127) in a ratio of 7:3. Afterwards, the train set was split into a recurrence group and a non-recurrence group for further analysis of indicators while in hospital.
Following Lasso regression screening, 8 variables were selected from a pool of 62 variables from patients with AF and OSAS. Additionally, the study incorporated the CHADS-VASc score and its components of interest, the severity of OSAS and hypoxemia, and whether patients received catheter ablation (CA). Multivariable Cox regression analysis revealed: Hb < 115 g/L (HR = 2.27), P > 1.51mmol/L (HR = 3.77), PCT > 2ng/ml (HR = 15.72) as independent risk factors. Hb > 150 g/L (HR = 0.66), TT4 < 66 nmol/L (HR = 0.16) were identified as independent protective factors. The train set showed AUC values of 0.65, 0.71, and 0.71 at the 1st, 3rd, and 5th year, respectively, while the validation set displayed AUC values of 0.60, 0.59, and 0.64 at the 1st, 3rd, and 5th year, respectively, indicating good predictive performance of the model. The AF recurrence rate scoring system categorized patients in the train and test sets into low-risk, medium-risk, and high-risk groups, with HR values of 2.36 and 6.79 for AF recurrence rates in the medium-risk and high-risk groups of the train set, and an HR value of 2.77 for the medium-risk group in the test set.
The predictive models and scoring systems developed in this study demonstrate good predictive ability in assessing the recurrence of AF in patients with OSAS, offering invaluable clinical guidance and references.
Not applicable.
心房颤动（AF）和阻塞性睡眠呼吸暂停综合征（OSAS）的高患病率给公共医疗保健带来了沉重的疾病负担，使其成为当前时代的一个重大健康问题。然而，目前缺乏针对AF合并OSAS患者AF复发的风险评估工具。因此，本研究旨在探讨影响AF合并OSAS患者AF复发的因素，并建立AF复发率的预测模型和评分系统。
本研究共纳入423例AF合并OSAS患者，按照7:3的比例随机分为训练集（n = 296）和测试集（n = 127）。之后，将训练集分为复发组和未复发组，以便在住院期间进一步分析指标。
经过Lasso回归筛选，从AF合并OSAS患者的62个变量中选择了8个变量。此外，该研究纳入了CHADS-VASc评分及其相关成分、OSAS和低氧血症的严重程度，以及患者是否接受导管消融（CA）。多变量Cox回归分析显示：血红蛋白<115 g/L（HR = 2.27）、磷>1.51mmol/L（HR = 3.77）、降钙素原>2ng/ml（HR = 15.72）为独立危险因素。血红蛋白>150 g/L（HR = 0.66）、总甲状腺素<66 nmol/L（HR = 0.16）被确定为独立保护因素。训练集在第1年、第3年和第5年的AUC值分别为0.65、0.71和0.71，而验证集在第1年、第3年和第5年的AUC值分别为0.60、0.59和0.64，表明该模型具有良好的预测性能。AF复发率评分系统将训练集和测试集的患者分为低风险、中风险和高风险组，训练集中风险组和高风险组的AF复发率HR值分别为2.36和6.79，测试集中风险组的HR值为2.77。
本研究开发的预测模型和评分系统在评估OSAS患者AF复发方面具有良好的预测能力，提供了宝贵的临床指导和参考。
不适用。
