确定风险因素,并开发一种预测模型,用于使用Cefmetazole提高国际规范化比率的患者
Takaya Namiki1,2, Yuta Yokoyama1,3, Motonori Kimura4
1Division of Pharmaceutical Care Sciences, Keio University Graduate School of Pharmaceutical Sciences, Tokyo, Japan.
PloS one
|July 28, 2025
概括
这项研究确定了在甲 (CMZ) 治疗期间国际正常化比率 (INR) 升高的关键风险因素,开发了一个更安全的CMZ管理的预测模型. 该模型通过评估患者患出血并发症风险,帮助临床医生有效管理CMZ使用.
科学领域:
- 药理学 药理学是指药理学的学科.
- 临床医学 临床医学
- 医疗信息学 医疗信息学
背景情况:
- 甲 (CMZ) 的使用与凝血病和出血风险有关,但缺乏针对患者的特定风险因素和这些副作用的预测模型.
- 现有的文献缺乏关于需要在CMZ治疗期间谨慎采取措施以确保安全的患者群体的指导.
研究的目的:
- 为了确定患者的风险因素,与国际正常化比率 (INR) 在甲 (CMZ) 治疗期间.
- 开发一种使用风险评分预测INR升高的预测模型,以确保安全的CMZ管理.
主要方法:
- 一项多中心,回顾性,观察性研究,涉及使用CMZ治疗的患者.
- 用单变量和多变量逻辑回归分析来确定风险因素的调整概率比率 (aOR) 和置信区间 (CI).
- 开发并使用AUC验证了一个预测模型来对INR升高风险进行分类.
主要成果:
- 对于INR升高的显著风险因素包括肝脏疾病 (aOR,5.65),营养风险 (aOR,6.32),没有糖尿病的糖尿病 (aOR,4.53) 和华法林使用 (aOR,98.44).
- 创建了一个风险评分系统,将患者分为INR升高的低,中,高和非常高风险类别.
- 该预测模型表现出良好的有效性,AUC为0.79 (95% CI,0.73-0.85,P <0.001).
结论:
- 这项研究成功地确定了在接受CMZ的患者中导致INR升高的关键风险因素.
- 开发了一种包含风险评分的新型预测模型,以预测INR升高,促进更安全的CMZ使用.
- 经过验证的预测模型通过使风险分层成为可能,支持CMZ的适当和安全管理.
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