基于多重逻辑回归模型,探索患有肺栓塞并存的下肢深静脉血栓患者的风险因素
1School of Public Health, Shanxi Medical University, Taiyuan, China.
概括
这项研究确定了深静脉血栓塞 (DVT) 患者的关键风险因素,这些患者也经历了肺栓塞 (PE). 后勤回归模型准确地预测高风险个体,有助于早期检测和管理DVT与PE.
科学领域:
- 心脏病学 心脏病学
- 血管医学 血管医学
- 医疗信息学 医疗信息学
背景情况:
- 深静脉血栓症 (DVT) 和肺栓塞 (PE) 是致病率和死亡率的重要原因.
- 关于同时存在PE的DVT患者的数据有限,这阻碍了风险分层.
- 准确识别高风险患者对于及时干预至关重要.
研究的目的:
- 确定与患有并存PE的DVT患者相关的重大风险因素.
- 开发和验证后勤回归模型,用于预测具有并发性PE的高风险DVT患者.
- 改善对需要更密切监测和特定治疗策略的患者的选择.
主要方法:
- 在2022年7月至2023年6月期间,从150名DVT患者追溯收集数据.
- 将患者分为基于同时存在PE的存在或不存在的组.
- 单变量和多变量逻辑回归分析以确定预测因素.
- 使用歧视和校准统计数据构建和验证预测模型.
主要成果:
- 在130名分析患者中,有40名 (30.77%) 患有同时存在的PE.
- 确定了重要的预测因素:性别 (OR 3.83),体重指数 (BMI) (OR 1.50),慢性疾病 (OR 5.15) 和高密度脂蛋白 (HDL) (OR 0.03).
- 较高的BMI (>24 kg/m2和>28 kg/m2) 与并发性PE有很强的关联.
- 开发的后勤回归模型显示出高的预测准确性 (AUC从0.890到0.925不等).
结论:
- 性别,BMI,慢性疾病的存在和HDL水平是DVT患者PE的显著独立预测因素.
- 开发的后勤回归模型为识别具有同时存在PE的高风险DVT患者提供了可靠的工具.
- 这些发现可以指导临床决策和资源分配,用于管理复杂的静脉血栓塞栓症病例.
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