术后肺部并发症的预测模型:系统性审查和元分析
Zhiyu Huang1, Yang Han1, Huijia Zhuang1
1Department of Anaesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
British journal of anaesthesia
|June 5, 2025
概括
许多术后肺部并发症 (PPC) 的预测模型存在,但它们的临床实用性是不确定的. 需要进一步验证,以可靠地识别高风险患者并改善护理.
科学领域:
- 医学研究 医学研究
- 临床预测建模临床预测建模
- 肺部医学 肺部医学
背景情况:
- 手术后肺部并发症 (PPC) 显著增加死亡率,住院时间和医疗费用.
- 准确的预测模型对于识别高风险患者和指导术后管理至关重要.
- 现有的PPC预测模型的临床实用性和区分能力需要进行彻底的评估.
研究的目的:
- 系统地审查和综合术后肺部并发症预测模型的性能.
- 通过元分析评估各种PPC预测模型的区分能力 (c-统计).
- 评估潜在的临床影响,并确定可靠的患者护理模型.
主要方法:
- 在Cochrane,Embase和PubMed数据库进行系统的文献搜索,截至2024年6月.
- 使用CHARMS检查清单提取数据,并使用PROBAST进行偏差评估.
- 贝叶斯对c统计的元分析,用于使用来自三个或更多群体的数据来合成歧视的模型.
主要成果:
- 确定了PPC的116个预测模型,其中14个模型 (1,004,029名患者) 被纳入了元分析.
- 所有模型的中位数c-统计值为0.80,其中50%报告了良好的歧视 (c-统计值>0.8).
- 几种模型对复合PPC,肺炎和呼吸衰竭有中等到良好的区别,但可靠性受到外部验证不足和大多数模型中偏差高风险 (90.2%) 的限制.
结论:
- 已经开发了许多PPC的预测模型,但它们的广泛临床实用性仍然不确定.
- 目前的证据表明,特定模型的性能适度至良好,但存在显著的局限性.
- 外部验证和偏差减少对于提高PPC预测模型的可靠性和临床适用性至关重要.
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