预测药物过量和死亡后"在医疗建议之前"医院出院
Hiten Naik1, Daniel Daly-Grafstein2, Xiao Hu2
1Departments of Medicine (Naik, Daly-Grafstein, Hu, Khan, Nasmith, Staples), Statistics (Daly-Grafstein, Hu), Emergency Medicine (Brubacher, Moe), Pathology, and Laboratory Medicine (Slaunwhite), University of British Columbia, Vancouver, BC; Department of Family and Community Medicine (Kaasa), University of Toronto, Toronto, Ont.; Department of Internal Medicine (Lyden), Denver Health, Denver, Colo.; Department of Internal Medicine (Lyden), University of Colorado School of Medicine, Aurora, Colo.; British Columbia Centre for Disease Control (Moe, Crabtree); School of Population and Public Health (Crabtree, Slaunwhite), University of British Columbia; British Columbia Centre on Substance Use (Crabtree); BC Mental Health and Substance Use Services (Slaunwhite), Provincial Health Services Authority; Centre for Clinical Epidemiology & Evaluation (Staples), Vancouver, BC. hiten.naik@ubc.ca.
在"医疗建议" (BMA) 之前出院的患者面临死亡和药物过量服用的风险更高. 新的预测模型可以识别高风险个体,使得有针对性的支持可以改善BMA医院出院后的结果.
科学领域:
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
- 临床信息学 临床信息学
背景情况:
- 医院出院的情况
- 在医疗咨询之前.
- (BMA) 与增加的死亡率和药物过量使用风险有关.
- 预测模型可以帮助识别有风险的患者.
研究的目的:
- 开发和验证风险预测模型的死亡和非法药物过量在BMA释放30天内.
- 估计个别患者的绝对风险.
主要方法:
- 来自不列颠哥伦比亚省 (2015-2019) 的行政卫生数据的回顾性分析.
- 为死亡 (模型A) 和药物过量 (模型B) 开发的后勤回归模型.
- 使用基于引导的乐观度纠正进行内部验证.
主要成果:
- 模型A (死亡):在30天内1.6%的死亡率;预测因素包括高并发症指数,癌症,心脏病 (C-统计=0.78).
- 模型B (过量服用):在30天内5.2%的过量服用率;预测因素包括无家可归,社会援助,物质使用障碍,先前过量服用 (C-统计=0.79).
- 这两种模型都表现出良好的区分和优秀的校准.
结论:
- 经过验证的风险预测模型可以识别患有高死亡风险或BMA出院后过量服用的患者.
- 这些模型可以为改善患者支持的临床和医院干预提供信息.
更多相关视频
06:52Assessment of Dependence in Activities of Daily Living Among Older Patients in an Acute Care Unit
Published on: September 30, 2020
05:16Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
相关概念视频
Pharmacovigilance
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
Drug Accumulation During Multiple Dosing: Repetitive IV Injections
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses
Drug Dosing: Geriatric Patients
Drug Toxicity: Risk factors
Pharmaceutical Poisoning: Potential Scenarios
