在外科手术期间低温症的风险预测模型:系统审查
Jinghui Liu1,2, Fangli Liu2,3, Wenqi Xu1,2
1Surgery and Anesthesiology Department 3, Zhongshan People's Hospital, Zhongshan, Guangdong, People's Republic of China.
Journal of multidisciplinary healthcare
|August 4, 2025
概括
外科手术期间低温风险预测模型表现良好,但由于验证不足,存在高偏差. 需要进一步的标准化和验证,以提高临床准确性.
科学领域:
- 医疗信息学 医疗信息学
- 临床风险管理临床风险管理
- 麻醉学 麻醉学
背景情况:
- 周围手术性低温症是一种常见的并发症,对患者的结果有显著的负面影响.
- 它增加了手术部位感染,凝血功能障碍和长时间住院等风险.
- 有效的风险预测对于临床决策和改善患者预后至关重要.
研究的目的:
- 系统地审查和评估现有的外科手术期间低温风险预测模型.
- 为临床医生在选择或开发适当的预测模型时提供参考.
- 确定关键预测因素并评估当前模型的质量.
主要方法:
- 在主要数据库 (PubMed,Embase,Web of Science,Cochrane,CINAHL) 进行系统的文献搜索,直到2024年5月.
- 使用CHARMS检查清单进行独立选和数据提取.
- 使用PROBAST工具进行偏差风险和适用性评估.
主要成果:
- 包括11篇论文和14个风险预测模型,显示出良好的预测性能 (AUC 0.700-0.870).
- 常见的预测因素包括年龄,基线温度,BMI,液体体积,OR温度和手术时间.
- 在所有研究中都注意到存在偏差的高风险,主要是由于模型验证不足.
结论:
- 现有的外科手术期间低温风险模型具有良好的区分和适用性,但需要提高研究质量.
- 需要标准化的方法来优化模型,并开发具有较低偏差的新模型.
- 加强内部和外部验证对于提高临床预测准确性至关重要.
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