Mayer Tanja, Meid Andreas Daniel, Saum Kai-Uwe, Brenner Hermann, Schöttker Ben, Seidling Hanna Marita, Haefeli Walter Emil
Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Heidelberg, Germany; Cooperation Unit Clinical Pharmacy, University of Heidelberg, Heidelberg, Germany.
Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Heidelberg, Germany.
Am J Geriatr Psychiatry. 2017 May;25(5):531-540. doi: 10.1016/j.jagp.2017.01.009. Epub 2017 Jan 23.
A patient's risk for anticholinergic adverse effects is frequently estimated by instruments evaluating the drugs included in his medication profile. It remains unknown, however, which characteristics should be included in such an assessment instrument aiming to reliably predict adverse anticholinergic outcomes.
Cross-sectional study.
ESTHER cohort (Germany).
Home-dwelling participants (N = 2,761) aged between 60 and 87 years.
The association between anticholinergic load calculated with nine different instruments and four anticholinergic adverse outcomes was investigated in univariate and multivariate analyses. Therefore, linear models complemented with Kendall's tau rank correlation coefficients (ԏ) were applied for continuous outcomes and generalized linear models were used to derive odds ratios (ORs) with 95% confidence intervals (CIs) for binary endpoints.
Based on the respective identification criteria for anticholinergic drugs, the nine instruments identified between 245 (9%) and 866 (31%) anticholinergic drug users (mean age ± SD: 73 ± 6 years; Mini-Mental State Examination [MMSE] score: 28.3 ± 2.07; Barthel Index: 97.1 ± 7.5; 291 reporting falls; 29 taking laxatives [surrogate for constipation]). In the multivariate analysis, only two instruments indicated a significant association between anticholinergic load and all four outcomes. The instrument considering the prescribed dose showed the strongest association with MMSE scores (ԏ = -0.10), falls (OR: 2.30; 95% CI: 1.50-3.52), and the use of laxatives (OR: 3.11; 95% CI: 1.04-9.36).
Instruments most reliably predicted anticholinergicadverse events if they were either based on the drugs' serum anticholinergic activity and the suggestions of clinician experts or considered the actual prescribed dose.
通常通过评估患者用药清单中药物的工具来估算其发生抗胆碱能不良反应的风险。然而，尚不清楚在这样一种旨在可靠预测抗胆碱能不良后果的评估工具中应纳入哪些特征。
横断面研究。
ESTHER队列研究（德国）。
年龄在60至87岁之间的居家参与者（N = 2761）。
在单变量和多变量分析中，研究了用九种不同工具计算的抗胆碱能负荷与四种抗胆碱能不良后果之间的关联。因此，对于连续结局，应用了补充肯德尔tau秩相关系数（ԏ）的线性模型，对于二元终点，使用广义线性模型得出比值比（OR）及其95%置信区间（CI）。
根据抗胆碱能药物的各自识别标准，这九种工具识别出245名（9%）至866名（31%）抗胆碱能药物使用者（平均年龄±标准差：73±6岁；简易精神状态检查表[MMSE]评分：28.3±2.07；巴氏指数：97.1±7.5；291人报告跌倒；29人使用泻药[便秘替代指标]）。在多变量分析中，只有两种工具表明抗胆碱能负荷与所有四种结局之间存在显著关联。考虑规定剂量的工具与MMSE评分（ԏ = -0.10）、跌倒（OR：2.30；95%CI：1.50 - 3.52）和泻药使用（OR：3.11；95%CI：1.04 - 9.36）显示出最强的关联。
如果工具基于药物的血清抗胆碱能活性和临床专家的建议，或者考虑实际规定剂量，则最能可靠地预测抗胆碱能不良事件。
