开发一个模型,预测进入长期护理设施后慢性阿片类药物使用的风险
Sharmala Thuraisingam1, Tesfahun C Eshetie2, Gillian E Caughey3
1Registry of Senior Australians Research Centre, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia; Registry of Senior Australians Research Centre, Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Bedford Park, South Australia, Australia.
Journal of the American Medical Directors Association
|November 28, 2025
概括
在长期护理机构居民中预测慢性阿片类药物使用是可能的. 关键因素包括先前的阿片类药物使用,疼痛史和复杂的健康需求,有助于针对性干预.
科学领域:
- 老年学是一门学科.
- 药理学 药理学是指药理学的学科.
- 医疗保健服务研究 医疗服务研究
背景情况:
- 慢性阿片类药物使用在长期护理设施 (LTCF) 中普遍存在,增加了跌倒,骨折和认知能力下降的风险.
- 在这个脆弱人群中,慢性阿片类药物启动的预测因素尚不清楚.
研究的目的:
- 在进入LTCF一年内开发一种新的慢性阿片类药物使用的预测模型.
- 确定与新住院者慢性阿片类药物开始相关的关键预测因素.
主要方法:
- 澳大利亚老年人国家历史队列登记册的回顾性队列分析.
- 竞争风险回归建模被用来预测慢性阿片类药物使用的时间.
- 包括65岁以上的非土著个人进入LTCF (2009-2019),不包括息治疗和以前的慢性阿片类药物使用者.
主要成果:
- 最终的队列包括355,208名居民;7%的人在一年内开始慢性阿片类药物使用.
- 预测模型显示出良好的区分 (C指数:0.75) 和可接受的校准.
- 关键预测因素包括先前的非慢性阿片类药物使用,高药物辅助,疼痛史,复杂的健康需求和高镇静剂负载.
结论:
- 一个经过验证的模型可以识别具有慢性阿片类药物使用高风险的新LTCF居民.
- 早期识别有助于有针对性的疼痛管理和阿片类药物管理干预.
- 这支持在LTCF中改善居民安全和优化药物治疗.
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