风险因素和风险预测模型用于肠静脉切割患者的粘膜皮质分离:一个单一中心的经验
Yun Liu1, Hong Li1, Jin-Jing Wu1
1Department of Reconstructive, Hand and Plastic Surgery, Zhejiang Chinese Medical University, Lishui Central Hospital, 289 Kuocang Road, Liandu District, Lishui 323000, Zhejiang Province, China.
World journal of clinical cases
|November 27, 2024
概括
这项研究开发了一种预测模型,以确定在肠静脉切除术后面临粘膜皮肤分离 (MCS) 风险的患者. 该模型结合了部脱落和白蛋白水平等因素,显示了早期MCS检测的良好准确性.
科学领域:
- 手术并发症 手术并发症
- 肠静静管管理 肠静静管管理
- 预测模型在医学中的预测模型.
背景情况:
- 粘膜皮质分离 (MCS) 是干肠切除术后的常见和病态并发症.
- 早期有效地识别患有MCS风险的患者至关重要,但目前的预测模型有限.
研究的目的:
- 开发和验证一个风险预测模型,用于粘膜皮肤分离 (MCS) 进行肠静脉切除的患者.
- 评估开发的MCS风险模型的临床预测准确性.
主要方法:
- 分析了492名肠静脉切除术患者 (2019年1月-2023年3月) 的队列.
- 根据早期术后结果,患者被分为MCS (n=110) 和非MCS (n=382) 组.
- 使用单变量,多变量分析和ROC曲线分析来识别预测因素并评估模型性能.
主要成果:
- 手术后MCS的总体发病率为22.4%.
- 确定MCS的独立预测因素包括部脱落,低血清白蛋白,较低的BMI,较低的血红蛋白,肠裂,切口感染,新辅助疗法,静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉
- 最终的模型表现出强大的预测性能,曲线下的面积 (AUC) 为0.827和良好的临床效用.
结论:
- 一个强大的预测模型,用于粘膜皮质分离在肠静脉瘤患者已经成功开发.
- 该模型为MCS的早期检测和管理提供了有价值的临床实用性,改善了患者的治疗结果.
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