一个新的评分系统预测发烧性尿路感染后逆行性内手术后
Cagdas Senel1,2, Anil Erkan3, Tanju Keten4
1Department of Urology, Balikesir University School of Medicine, Balikesir, Turkey. cagdas_senel@hotmail.com.
Urolithiasis
|December 24, 2024
概括
一个新的评分系统可以预测逆行性内手术 (RIRS) 后发烧性尿路感染 (F-UTI). 关键预测因素包括水,先前的尿路感染史和尿液白细胞计数,使早期风险识别成为可能.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 医疗信息学 医疗信息学
- 传染性疾病 传染性疾病
背景情况:
- 发烧性尿路感染 (F-UTI) 是逆行性内手术 (RIRS) 后的潜在并发症.
- 准确预测F-UTI风险对于患者管理和预防不良结果至关重要.
- 现有的风险分层方法可能无法完全捕捉RIRS后的F-UTI开发的复杂性.
研究的目的:
- 在RIRS之后确定F-UTI的风险因素.
- 开发和验证一种基于机器学习的新型评分系统,用于预测F-UTI后RIRS.
- 为了加强接受RIRS的患者的临床决策.
主要方法:
- 对接受RIRS的511名患者进行了回顾性分析.
- 机器学习技术的应用,包括特征选择 (一致性子集评估器,贪的逐步) 和后勤回归.
- 使用接收器操作特征 (ROC) 曲线分析验证评分系统.
主要成果:
- 确定了五个关键变量:糖尿病,水性,给药类型,尿道镜后尿路感染史和尿白细胞计数.
- 水性缩症,经过URS后的尿路感染史和尿液白细胞计数是F-UTI的显著独立预测因素 (AUC = 0.837).
- 开发的评分系统准确地预测了F-UTI在94.1%的受影响患者中,当至少有一个风险因素存在时.
结论:
- 一个基于水溶解,先前尿路感染史和尿液白细胞计数的新评分系统有效地预测了RIRS后的F-UTI风险.
- 这种工具可以帮助临床医生识别高风险患者,并可能指导预防策略.
- 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.
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