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预测腹腔透析患者的肉症:基于多模式超声波的物流回归分析和诺莫格拉姆模型

Shengqiao Wang¹, Xiuyun Lu¹, Juan Chen¹

¹Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai JiaoTong University, School of Medicine, 1665th Kongjiang Road, Shanghai 200092, China.

Diagnostics (Basel, Switzerland)

|November 13, 2025

概括

这项研究开发了一种多式超声波模型,用于预测腹腔透析患者的肉症. 该模型有效地识别了高风险的个体,使得早期干预能够获得更好的结果.

科学领域:

腎臟病學 (nephrology) 是一種醫學專業.
老年病的医生老年病的医生
诊断成像诊断成像诊断成像

背景情况:

皮症是经过腹膜透析 (PD) 的患者常见的并发症.
早期检测sarcopenia对于管理PD患者和改善他们的生活质量至关重要.
当前的诊断方法可能在可访问性和侵入性方面存在局限性.

研究的目的:

评估基于多式超声波的逻辑回归和名谱模型的诊断价值,用于预测PD患者的肉症.
在这个人群中开发和验证一种非侵入性预测工具来预测sarcopenia.

主要方法:

178名PD患者被招募并根据2019年亚洲肉症工作组 (AWGS) 标准分为肉症和非肉症组.
测量了多模式超声波参数 (肌肉厚度,角,带长度,衰减系数,回声强度) 的胃半径中间头部.
构建了二进制后勤回归和名图模型,并使用接收器操作特征 (ROC) 曲线评估了它们的准确性.

主要成果:

与非萨科佩尼亚患者相比,患有萨科佩尼亚的患者的肌肉厚度,皮纳角和带长度显著降低,衰减系数和回声强度更高 (p < 0.05).
一个多式超声波后勤回归模型实现了0.785的F1得分和0.902.90的ROC曲线下的面积 (ROC-AUC).
与通过生物电阻分析 (BIA) 测量的尾骨肌指数 (ASMI) 相比,名图没有显示任何统计差异.

结论:

开发的多式超声波预测模型有效地识别了患有高风险的肉类的PD患者.
这种非侵入性工具可以帮助临床医生进行早期检测和干预,从而有可能改善临床结果.
基于超声波的评估为PD患者的查提供了一个有希望的替代方案.

关键词:

衰减系数 (Atten Coe) 是一个逻辑回归的逻辑回归这个名字是名ogramogram.腹膜透析 (PD) 是一种治疗方法.预测模型预测模型这种类型的麻症是sarcopenia.

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