慢性疾病患者药物坚持的预测模型:系统性审查和批判性评估
Jingwen Xu1, Xinyi Zhao1, Fei Li2
1School of Nursing, Jilin University, Changchun, China.
Journal of clinical nursing
|December 31, 2024
概括
慢性疾病中药物坚持的风险预测模型显示高偏差. 未来的研究必须改善模型开发和验证,以获得更好的患者结果.
科学领域:
- 医疗信息学 医疗信息学
- 临床流行病学临床流行病学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 药物坚持对于管理慢性疾病至关重要.
- 有许多风险预测模型,但它们的可靠性和适用性是不确定的.
研究的目的:
- 系统地审查和评估现有的风险预测模型,用于慢性疾病患者的药物坚持.
- 评估这些模型的性能和临床适用性.
主要方法:
- 系统审查2023年7月之前发表的研究,搜索多个数据库.
- 基于预先定义的标准对药物坚持的风险预测模型的选.
- 使用预测模型偏差风险评估工具 (PROBAST) 评估偏差风险和临床适用性.
主要成果:
- 包括11项研究和11个风险预测模型.
- 发现的常见预测因素是药物治疗方案和年龄.
- 所有模型都表现出高偏差风险,原因是方法限制和不完整的报告.
结论:
- 目前用于慢性疾病中药物坚持的风险预测模型具有高偏差风险.
- 建议包括提高方法质量和进行外部验证.
- 需要改进模型开发,以识别高风险个体和与不遵守相关的因素.
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