尾炎严重程度2.0评分系统的开发和验证
Jochem C G Scheijmans1, Wouter J Bom1, Umme Habiba Ghori1
1Department of Surgery, Amsterdam University Medical Center, Amsterdam, the Netherlands.
尾炎严重程度评分系统 (SAS) 没有通过外部验证来识别复杂尾炎. 开发并验证了一种新的SAS 2.0模型,准确评估个体患者复杂尾炎的风险.
科学领域:
- 医学诊断 医学诊断 医学诊断
- 外科手术的结果
- 临床预测模型临床预测模型
背景情况:
- 精确区分无并发性尾炎和复杂性尾炎对于非手术治疗决定至关重要.
- 现有的尾炎严重程度评分系统 (SAS) 需要潜在的外部验证.
研究的目的:
- 为外部验证SAS用于预测复杂尾炎.
- 如果原来的SAS在验证中失败,开发一个改进的SAS 2.0,提高估计复杂尾炎概率的准确性.
主要方法:
- 在荷兰11家医院对1360名因疑似急性尾炎接受手术的成年患者进行前性研究.
- 原始SAS的外部验证,其次是SAS 2.0的开发和验证,使用临床,生化和成像数据的多变量回归.
主要成果:
- 最初的SAS表现出83.6%的灵敏度和85.0%的现金价值,低于预定义的目标.
- 开发的SAS 2.0在内部 (C-统计数据0.87) 和外部验证 (C-统计数据0.86) 中实现了高准确度,用于预测复杂尾炎.
结论:
- 外部验证证实了原来的SAS在区分复杂尾炎方面不足.
- 经过验证的SAS 2.0准确评估了个体患者复杂尾炎的风险,支持其在治疗决策中的使用.
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