多变量分析和个性化名图构造,用于预测放射性干预后放射性动脉封闭风险
11Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, 99 Huaihai West Road, Xuzhou, Jiangsu, 221000, China.
BMC surgery
|February 1, 2026
概括
这项研究确定了冠状动脉动图 (CAG) 和皮肤冠状动脉干预 (PCI) 后放射性动脉封闭 (RAO) 的关键风险因素. 这些发现使得准确的风险预测能够更好地管理患者.
科学领域:
- 心脏病学 心脏病学
- 干预心脏病学 干预心脏病学
- 血管医学 血管医学
背景情况:
- 放射性动脉封闭 (RAO) 是心脏导管的并发症.
- 识别风险因素和开发预测模型对于预防RAO至关重要.
研究的目的:
- 在冠状动脉动图 (CAG) 和皮肤冠状动脉干预 (PCI) 后确定RAO的独立风险因素.
- 开发和验证RAO在CAG,PCI和整体患者群体中的风险预测模型.
主要方法:
- 781名接受CAG或PCI的患者的回顾性分析.
- 使用单变量和LASSO逻辑回归对变量进行选.
- 使用多变量逻辑回归,ROC曲线,校准曲线和决策曲线分析开发和验证名ogram预测模型.
主要成果:
- 整体RAO发生率为8.32%,在CAG (11.26%) 中高于PCI (5.64%).
- 确定的独立风险因素包括女性性别,肌酸激酶升高,多次刺穿,放射性动脉,刺穿部位疼痛.
- 保护因素包括特定群体中较高的BMI和较高的肌素;模型显示出强烈的区分能力 (AUC > 0.921).
结论:
- 开发的风险预测模型准确地识别了CAG和PCI后RAO的高风险患者.
- 多次刺穿,放射性动脉,刺穿部位疼痛是RAO的重大,可修改的风险因素.
- 这些模型为个性化的临床预防和治疗策略提供了宝贵的参考.
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