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在手术前识别穿孔性尾炎:规范风险分层模型

Edip Akpinar¹, Erhan Gök¹

¹Department of General Surgery, SBU, Adana Faculty of Medicine, Adana City Training and Research Hospital, Adana, Turkey.

The American surgeon

|March 7, 2026

概括

在手术前预测穿孔性尾炎 (PA) 很困难. 使用C反应蛋白 (CRP),年龄和淋巴细胞百分比的新模型准确地识别了具有高特异性的PA,有助于进行手术决策.

科学领域:

手术病理学的外科病理学
医学诊断医学诊断医学诊断
贝叶斯统计学贝叶斯统计学

背景情况:

穿孔性尾炎 (PA) 的术前诊断是一个重大的临床挑战.
准确预测PA对于及时的手术干预和患者管理至关重要.
现有的诊断方法往往缺乏足够的准确性来进行最终的手术前评估.

研究的目的:

为了确定穿孔尾炎 (PA) 的可靠的手术前预测因素.
使用贝叶斯统计方法开发和验证PA的预测模型.
为了提高诊断PA的准确性,并指导外科急诊.

主要方法:

对770名尾切除术患者的回顾性分析,确认了急性尾炎 (2022-2023年).
贝叶斯单变量和多变量逻辑回归分析以确定重要的预测因素.
模型性能评估使用接收器操作特征曲线 (AUC) 下的面积,灵敏度和特异性.

主要成果:

穿孔性尾炎 (PA) 在155名患者 (20%) 中得到证实.
C-反应蛋白 (CRP),年龄和淋巴细胞百分比成为具有强有力的统计证据的关键预测因素.
一个三变量模型 (CRP,年龄,淋巴细胞百分比) 显示出良好的区分 (AUC 0.78),高特异性 (95.4%) 和适度敏感性 (29%).

结论:

整合CRP,年龄和淋巴细胞百分比的预测模型提供了一个高度特定的工具来裁决穿孔尾炎.
这种模型可以帮助确定手术干预的优先级,并优化术后护理.
建议进一步进行前性验证,以确认该预测模型的临床实用性.

关键词:

在C-反应性蛋白质中.尾炎是一种尾炎.贝叶斯式分析贝叶斯式分析穿孔穿孔是指穿孔穿孔的情况.预测模型预测模型

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