Supplementary Material for: The Influence of Patient Characteristics on Anticholinergic Events in Older People

<b><i>Aims:</i></b> To examine patient characteristics that predict adverse anticholinergic-type events in older people. <b><i>Methods:</i></b> This retrospective population-level study included 2,248 hospitalised patients. Individual data on medicines that are commonly associated with anticholinergic events (delirium, constipation and urinary retention) were identified. Patient characteristics examined were medicines with anticholinergic effects (ACh burden), age, sex, non-anticholinergic medicines (non-ACM), Charlson comorbidity index scores and ethnicity. The Akaike information criterion was used for model selection. The data were analysed using logistic regression models for anticholinergic events using the software NONMEM. <b><i>Results:</i></b> ACh burden was found to be a significant independent predictor for developing an anticholinergic event [adjusted odds ratio (aOR): 3.21, 95% CI: 1.23-5.81] for those taking an average of 5 anticholinergic medicines compared to those taking 1. Both non-ACM and age were also independent risk factors (aOR: 1.41, 95% CI: 1.31-1.51 and aOR: 1.08, 95% CI: 1.05-1.10, respectively). <b><i>Conclusion:</i></b> To our knowledge, this is the first study that has examined population-level data in a nonlinear model framework to predict anticholinergic-type adverse events. This study evaluated the relationship between important patient characteristics and the occurrence of anticholinergic-type events. These findings reinforce the clinical significance of reviewing anticholinergic medicines in older people.

研究目的：旨在探究可预测老年人群抗胆碱能型不良反应的患者特征。
研究方法：本研究为基于人群的回顾性研究，共纳入2248名住院患者。研究提取了与抗胆碱能不良反应（谵妄、便秘及尿潴留）密切相关的常用药物个体数据。本次分析考察的患者特征包括：抗胆碱能药物负荷（ACh burden）、年龄、性别、非抗胆碱能药物（non-ACM）、查尔森合并症指数（Charlson comorbidity index）评分以及种族。研究采用赤池信息准则（Akaike information criterion）进行模型选择，并借助NONMEM软件，针对抗胆碱能不良反应构建logistic回归模型开展数据分析。
研究结果：结果显示，相较于仅服用1种抗胆碱能药物的人群，平均服用5种抗胆碱能药物者发生抗胆碱能不良反应的风险显著升高，其校正后比值比（adjusted odds ratio, aOR）为3.21，95%置信区间（95% CI）为1.23~5.81，抗胆碱能负荷为该不良反应发生的独立显著预测因素。此外，非抗胆碱能药物与年龄同样为独立危险因素，其校正后比值比分别为1.41（95% CI: 1.31~1.51）与1.08（95% CI: 1.05~1.10）。
结论：据我们所知，本研究为首项基于人群数据、采用非线性模型框架预测抗胆碱能型不良反应的研究。本研究明确了关键患者特征与抗胆碱能型不良反应发生之间的关联，研究结果进一步佐证了老年人群抗胆碱能药物临床评估的重要临床意义。