开发和验证一种风险预测模型,用于tigecycline诱导的性患者的低纤维素生成症:一个追溯的队列研究
Hongling Ma1, Zhaotang Gong1,2, Jia Sun1,3
1Department of Pharmacy, Inner Mongolia People's Hospital, Hohhot, 010000, Inner Mongolia, China.
BMC infectious diseases
|May 9, 2025
概括
一个新的预测模型有效地识别了毒症患者的风险,因为tigecycline治疗引起的低纤维素生成血症. 这种工具有助于临床医生管理tigecycline的这种常见不良影响,这对于多药耐药性感染至关重要.
科学领域:
- 药理学 药理学是指药理学的学科.
- 关键护理医学 关键护理医学
- 临床诊断 临床诊断 临床诊断
背景情况:
- 在中国,tigecycline是治疗多抗药性细菌感染的关键药物.
- 低纤维素生成性是tigecycline常见的副作用,影响患者的凝血.
- 现有的这种情况的预测模型需要外部验证.
研究的目的:
- 开发和验证tigecycline诱导的败血症患者的低纤维素原体血症的预测模型.
- 确定与这种不良事件相关的关键风险因素.
主要方法:
- 用tigecycline治疗的败血症患者的回顾性队列研究.
- 后勤回归分析以确定风险因素.
- 使用MIMIC-IV数据库进行名图模型开发和外部验证.
主要成果:
- 该模型确定了年龄,tigecycline持续时间,基线纤维素素,基线血小板和瘤存在作为独立的风险因素.
- 该模型在训练组中达到0.85的AUC,在验证组中达到0.83.
- 预测和观察到的低纤维素生成血症之间有很强的一致性,具有良好的临床适用性.
结论:
- 已经开发了一种已验证的预测模型,用于毒症患者的tigecycline诱导的低纤维素生成性血症.
- 这个模型为管理tigecycline治疗提供了有价值的临床决策支持.
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