开发和验证一种预测工具,用于在重症监护下新生儿的药物不良反应
Ramon Weyler Leopoldino1, Daniel Paiva Marques2, Luan Carvalho Rocha2
1Graduate Program of Pharmaceutical Science, Health Science Center, Federal University of Rio Grande do Norte, Natal, Brazil.
British journal of clinical pharmacology
|November 5, 2023
概括
研究人员开发了一种预测工具,以识别新生儿在新生儿重症监护室 (NICU) 处有不良药物反应 (ADR) 风险. 该工具使用了五个常见变量,有助于对脆弱的婴儿进行早期干预.
科学领域:
- 新生儿药理学 新生儿药理学
- 临床预测模型的临床预测模型.
- 在重症监护室的患者安全.
背景情况:
- 新生儿重症监护室 (NICU) 的新生儿经常出现不良药物反应 (ADR).
- 预测和预防不良反应对于改善这种脆弱人群的结果至关重要.
- 在新生儿中预测ADR的现有方法是有限的.
研究的目的:
- 开发和验证用于新生儿住院治疗NICU的ADRs的预测工具.
- 确定与该人群中ADR发展相关的关键风险因素.
- 为临床医生提供一个实用的工具来评估ADR风险.
主要方法:
- 在巴西 (2019年1月至2022年1月) 接受新生儿入院的NICU进行了一项嵌套病例控制研究.
- 用多变量逻辑回归来开发对三分之二样本的预测模型.
- 用Hosmer-Lemeshow测试,Brier分数和接收器操作特征 (ROC) 曲线分析进行验证,评估了模型性能.
主要成果:
- 该研究包括450名新生儿 (150例具有ADR,300例对照).
- 确定了五个独立的危险因素:机械通风,心率≥178次/小时,静脉注射药物,≥5次药物和孕产妇妊娠高血压.
- 经过验证的工具显示ROC曲线下的面积为0.74,灵敏度为52.02%,特异性为81.35%.
结论:
- 开发的工具证明了在NICU新生儿中预测ADRs的充分区分能力.
- 它利用了五个常见的监控变量,使其在临床使用中变得实用.
- 这种工具可以帮助早期识别和管理处于药物不良反应风险的新生儿.
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