Department of Cardiology, the Third Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People's Republic of China.
Department of Cardiology, Hefei BOE Hospital, Hefei, Anhui, People's Republic of China.
Clin Interv Aging. 2024 Jan 10;19:67-79. doi: 10.2147/CIA.S437065. eCollection 2024.
Non-valvular atrial fibrillation (NVAF) patients face a 3-5 times greater risk of acute ischemic stroke (AIS) compared to those without NVAF. This study aims to establish a novel clinical prediction model for AIS in elderly patients with NVAF by incorporating relevant biomarker indicators.
A total of 301 individuals diagnosed with NVAF were selected for this investigation at the Third Affiliated Hospital of Anhui Medical University. Based on the presence of AIS, patients were categorized into two groups: the Stroke Cohort and the Non-Stroke Cohort. Predictor screening was performed using the least absolute shrinkage and selection operation (LASSO) regression algorithm. The binary logistic regression equation was applied to fit the model, followed by internal validation using the bootstrap resampling method (1000 times). Receiver operating characteristic (ROC) curve, calibration degree curve plots, and clinical decision curve analysis (DCA) were generated, respectively. Finally, a nomogram was constructed to present the prediction model.
The final results of this study revealed that neutrophil-to-lymphocyte ratio (NLR), red cell distribution width (RDW), lipoprotein(a) (Lp(a)), systolic pressure, history of stroke, hyperlipidemia were independent risk factors for AIS in elderly patients with NVAF (<0.05). And the high-density lipoprotein cholesterol (HDL-C) was an independent protective factor (<0.05). By incorporating these indicators, a nomogram prediction model for predicting AIS in elderly patients with NVAF was constructed. Comparative analysis between the nomogram predictive model and CHA2DS2-VASc score revealed that the AUC of the nomogram predictive model surpassed that of the CHA2DS2-VASc score (AUC: 0.881vs 0.850).
NLR, RDW, Lp(a), SP, history of stroke, hyperlipidemia, and HDL-C emerge as independent prognostic factors for acute ischemic stroke in elderly patients with non-valvular atrial fibrillation. The predictive utility of the nomogram model may potentially surpass that of the CHA2DS2-VASc scoring system.
与无非瓣膜性心房颤动（NVAF）的患者相比，NVAF 患者发生急性缺血性卒中（AIS）的风险高 3-5 倍。本研究旨在通过纳入相关生物标志物指标，为 NVAF 老年患者建立一种新的 AIS 临床预测模型。
本研究共选取了 301 名在安徽医科大学第三附属医院诊断为 NVAF 的患者。根据是否发生 AIS，将患者分为卒中队列和非卒中队列。采用最小绝对收缩和选择算子（LASSO）回归算法进行预测因子筛选。应用二项逻辑回归方程拟合模型，然后采用自举重采样法（1000 次）进行内部验证。分别生成受试者工作特征（ROC）曲线、校准度曲线图和临床决策曲线分析（DCA）。最后构建了一个列线图来呈现预测模型。
本研究最终结果显示，中性粒细胞与淋巴细胞比值（NLR）、红细胞分布宽度（RDW）、脂蛋白（a）（Lp（a））、收缩压、卒中史、高脂血症是 NVAF 老年患者发生 AIS 的独立危险因素（<0.05）。而高密度脂蛋白胆固醇（HDL-C）是独立的保护因素（<0.05）。通过纳入这些指标，构建了一个预测 NVAF 老年患者 AIS 的列线图预测模型。与 CHA2DS2-VASc 评分的列线图预测模型比较分析显示，列线图预测模型的 AUC 优于 CHA2DS2-VASc 评分（AUC：0.881vs 0.850）。
NLR、RDW、Lp（a）、SP、卒中史、高脂血症和 HDL-C 是 NVAF 老年患者发生急性缺血性卒中的独立预后因素。列线图预测模型的预测效能可能优于 CHA2DS2-VASc 评分系统。
