Masnoon Nashwa, Shakib Sepehr, Kalisch Ellett Lisa, Caughey Gillian E
Quality Use of Medicines and Pharmacy Research Centre, School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, SA, Australia.
Department of Pharmacy, Royal Adelaide Hospital, Adelaide, SA, Australia.
Australas J Ageing. 2020 Sep;39(3):e436-e446. doi: 10.1111/ajag.12769. Epub 2020 Feb 13.
To identify demographic and medication-related predictors of unplanned hospitalisation and combine them into a hospitalisation risk score.
Patients aged ≥65 years from an outpatient multimorbidity clinic were included. Hospitalisation predictors within a year of clinic discharge were identified using logistic regression. A risk score was developed. The area under the curve (AUC) was used to assess its predictive ability, compared to that of the medicines count (definition of polypharmacy).
A total of 598 patients were included (median age of 80.0 years). 58.0% (n = 347) were hospitalised within a year of clinic discharge. The AUC for the risk score incorporating age, medicines count, heart failure (HF), atherosclerotic disease and systemic steroids was 0.67 [95% CI 0.62-0.71], compared to 0.62 [95% CI 0.58-0.67] for the medicines count.
A hospitalisation risk score incorporating demographics, medicines, namely steroids, and diseases such as HF had increased predictive ability compared to the medicines count, providing guidance for developing future polypharmacy tools.
确定非计划住院的人口统计学和药物相关预测因素，并将其整合为住院风险评分。
纳入来自门诊多病共存诊所的65岁及以上患者。使用逻辑回归确定出院后一年内的住院预测因素。制定风险评分。与药物数量（多重用药的定义）相比，曲线下面积（AUC）用于评估其预测能力。
共纳入598例患者（中位年龄80.0岁）。58.0%（n = 347）在出院后一年内住院。纳入年龄、药物数量、心力衰竭（HF）、动脉粥样硬化疾病和全身用类固醇的风险评分的AUC为0.67 [95%CI 0.62 - 0.71]，而药物数量的AUC为0.62 [95%CI 0.58 - 0.67]。
与药物数量相比，纳入人口统计学、药物（即类固醇）和HF等疾病的住院风险评分具有更高的预测能力，为未来多重用药工具的开发提供了指导。
