风险分层模型整合营养和炎症因素来预测膜心脏手术后的一年死亡率:一个回顾性队列研究
Jin Sun Cho1,2, Youn Joung Cho3, Jae-Kwang Shim1,2
1Department of Anaesthesiology and Pain Medicine.
International journal of surgery (London, England)
|October 6, 2023
概括
一个新的诺莫格拉姆模型通过包括炎症,营养和外科手术期间的因素,准确地预测了膜心脏手术后的一年死亡率. 这种综合模型的性能优于现有的系统,如EuroSCORE II,用于更好的患者风险评估.
科学领域:
- 心脏病学 心脏病学
- 外科手术的结果
- 生物统计学 生物统计学
背景情况:
- 目前的心脏手术风险评分缺乏对营养,炎症和术后状态的全面评估.
- 膜心脏手术的结果可能会受到超越标准手术前评估的因素的显著影响.
研究的目的:
- 开发和验证一种新的预测模型,用于膜心脏手术后的一年死亡率.
- 将客观的营养,炎症和外科手术期间的因素纳入全面的风险评估工具中.
主要方法:
- 对2046名接受了膜心脏手术的患者进行了回顾性分析.
- 利用考克斯和拉索回归来确定死亡率的独立预后因素.
- 开发并验证了一种包含确定因素 (单细胞与淋巴细胞的比率,EuroSCORE II,控制营养状况得分,心肺旁路时间,红细胞输血) 的名图.
主要成果:
- 一年死亡率为5.1%,与炎症和营养指数显著相关.
- 与单独的EuroSCORE II (C指数为0.744) 相比,新型名录显示出更高的预测能力 (C指数为0.834).
- 该模型在内部 (C指数0.836) 和外部 (C指数0.727) 验证队列中显示出良好的区分和校准.
结论:
- 一个整合炎症,营养和外科手术期间因素的诺莫图谱可以更好地预测膜心脏手术后1年死亡率.
- 这种全面的模型提供了比单独的EuroSCORE II更好的风险分层.
- 经过验证的诺姆图可以帮助临床决策和患者管理.
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