Geeson Cathy, Wei Li, Franklin Bryony Dean
Luton and Dunstable University Hospital, NHS Foundation Trust, Luton, UK.
UCL School of Pharmacy, London, UK.
Br J Clin Pharmacol. 2020 Jan;86(1):165-169. doi: 10.1111/bcp.14119. Epub 2019 Dec 17.
The aim of this prospective observational study was to establish associations between the use of high-risk medicine groups and the study outcome: occurrence of at least 1 moderate or severe preventable medication-related problem. Data on medication-related problems, high-risk medicines, and other potential risk factors were collected from adults on medical wards in 2 UK hospitals. Logistic regression modelling was used to determine relationships between high-risk medicines and the study outcome. Among 1503 eligible admissions, 6 high-risk medicine groups were associated with the study outcome on univariable analysis; multivariable analysis found only systemic antimicrobials and epilepsy medicines to be independently associated with the outcome (adjusted odds ratio 1.44, 95% confidence interval 1.08-1.92 and adjusted odds ratio 1.61, 95% confidence interval 1.16-2.25 respectively). Identification of high-risk medicine groups has potential to permit targeting of patients at highest risk of avoidable medication-related harm, but multivariable analysis suggests risk is likely to be multifactorial.
至少出现1例中度或重度可预防的药物相关问题。从英国2家医院内科病房的成年人中收集了与药物相关问题、高风险药物及其他潜在风险因素的数据。采用逻辑回归模型确定高风险药物与研究结果之间的关系。在1503例符合条件的入院病例中，单变量分析显示6个高风险药物组与研究结果相关；多变量分析发现只有全身用抗菌药物和抗癫痫药物与结果独立相关（校正比值比分别为1.44，95%置信区间1.08 - 1.92和校正比值比1.61，95%置信区间1.16 - 2.25）。识别高风险药物组有可能针对可避免的药物相关伤害风险最高的患者，但多变量分析表明风险可能是多因素的。
