储蓄性临床预测模型用于诊断复杂尾炎
Jia-Hui Cai1, Hui Zhou2, Dan Liang3
1Department of Radiology, Guangzhou Hospital of Integrated Traditional and West Medicine, Yingbin Avenue No. 87, Huadu District, Guangzhou, 510800, Guangdong, China.
Heliyon
|August 28, 2023
概括
一个新的后勤回归模型使用临床和放射学数据准确预测复杂尾炎. 关键预测因素包括发烧,吐,尾炎和周尾液,有助于早期诊断.
科学领域:
- 医学成像和诊断 医学成像和诊断
- 手术病理学的外科病理学
- 在医疗保健中的预测建模.
背景情况:
- 急性尾炎是一种常见的手术紧急情况.
- 在手术前区分复杂和非复杂的尾炎对于患者的管理至关重要.
- 目前的诊断方法可能在准确识别复杂病例方面存在局限性.
研究的目的:
- 开发和验证用于预测复杂尾炎的逻辑回归模型.
- 整合临床和放射学发现,以提高诊断准确度.
- 确定与复杂尾炎相关的关键预测因素.
主要方法:
- 对248名经组织学证明的尾炎患者的回顾性分析.
- 使用计算机断层扫描 (CT) 扫描数据和临床参数.
- 开发了一个使用单变量和多变量分析的逻辑回归模型.
主要成果:
- 一个包含体温>37.2°C,吐,尾炎和周尾液的模型实现了AUC为0.87.
- 该模型显示,复杂尾炎的灵敏度为88%,特异性为74%.
- 确定的主要预测因素是发烧,吐,尾炎和尾周液.
结论:
- 开发的后勤回归模型提供了一个准确而简单的方法来预测复杂的尾炎.
- 具体的临床和放射学特征的整合提高了诊断能力.
- 这个模型可能有助于及时和适当的外科干预.
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