[建立和验证复杂急性尾炎的诺莫格拉姆预测模型]
1Depertment of Emergency Surgery, the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Institute of Surgery, Anhui Academy of Traditional Chinese Medicine, Hefei 230031, China.
Zhonghua wai ke za zhi [Chinese journal of surgery]
|November 6, 2023
概括
一种新的诺莫格拉姆模型有效地利用患者年龄,疼痛持续时间,发烧和胆红素水平预测复杂尾炎 (CA). 这种工具有助于临床医生早期识别和管理CA,改善患者的治疗结果.
科学领域:
- 外科胃肠道外科手术
- 医疗信息学 医疗信息学
- 预测分析是一种预测分析.
背景情况:
- 急性尾炎是一种常见的手术紧急情况.
- 区分复杂尾炎 (CA) 和无并发症病例对于适当的治疗和改善患者结果至关重要.
- 当前的诊断方法可能并不总是准确地在手术前识别CA.
研究的目的:
- 开发和内部验证复杂急性尾炎 (CA) 的预测性名录模型.
- 确定与CA发展相关的关键临床因素.
- 为临床医生提供一个工具,以进行尾炎严重程度的术前风险分层.
主要方法:
- 对663名急性尾炎患者的临床数据进行了回顾性分析.
- 利用LASSO回归来确定CA的潜在风险因素.
- 开发了一个基于后勤回归的名图,并使用ROC曲线分析和AUC评估了其预测性能.
- 使用Bootstrap方法进行了内部验证.
主要成果:
- 纳米图纳入了年龄 (≥60岁),长时间的腹痛持续时间,高发烧 (≥39°C) 和增加的总胆红素作为CA的独立预测因素.
- 该模型表现出高预测精度,曲线下的面积 (AUC) 为0.935 (95% CI:0.9150.956).
- 内部验证证实该模型具有强大的区分能力 (AUC=0.933).
结论:
- 一个经过验证的纳米图,包括年龄,疼痛持续时间,发烧和总胆红素,可以有效预测复杂的尾炎.
- 这种临床预测工具可以帮助医疗保健提供者在手术前识别CA.
- 早期和准确的鉴定CA可以导致及时和适当的外科干预,可能改善患者的结果.
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