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老年人的多重用药和抗胆碱能负担量表:一项针对三级医院精神科门诊患者的横断面研究。

Polypharmacy and anticholinergic burden scales in older adults: a cross-sectional study among psychiatric outpatients in a tertiary care hospital.

作者信息

Bidarolli Manjunath, Das Biswadeep, Rawat Vikram Singh, Manocha Sachin, Sony Hannah Theresa, Agnihotri Akash, Gupta Mahima, Agera Franklin

机构信息

Department of Pharmacology, Amrita School of Medicine, Amrita Vishwa Vidyapeetham, Sector 88, Faridabad, Haryana, 121002, India.

Department of Pharmacology, All India Institute of Medical Sciences (AIIMS), Virbhadra Road, Rishikesh, Uttarakhand, 249203, India.

出版信息

BMC Geriatr. 2025 Jan 20;25(1):43. doi: 10.1186/s12877-024-05584-z.

DOI:10.1186/s12877-024-05584-z
PMID:39833708
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11744821/
Abstract

INTRODUCTION

Mental disorders are prevalent among older adults, often leading to the use of multiple medications, many with anticholinergic properties. Polypharmacy, common in this population, is a major contributor to anticholinergic burden, which is linked to cognitive and physical decline. This study investigates the relationship between polypharmacy and anticholinergic burden across seven anticholinergic burden scales in elderly patients attending the psychiatric outpatient.

METHODS

Study was conducted at a psychiatry outpatient clinic at All India Institute of Medical Sciences, Rishikesh, India, from December 2021 to March 2023. Elderly patients (aged ≥ 60 years) who were on at least one psychotropic medication and had a primary working diagnosis of psychiatric illness were included. All psychotropic medications, including antidepressants, antipsychotics, mood stabilizers, and hypnotics, were evaluated. Anticholinergic burden scales were calculated by the respective tools. Univariate analysis was adopted to determine the factors that may affect polypharmacy.

RESULTS

Study included 1165 elderly patients aged ≥ 60 years. The prevalence of polypharmacy was 20.43% (n = 238). Clonazepam (n = 364, 17.28%), escitalopram (n = 197, 9.35%), metformin (n = 165, 7.83%), sertraline (n = 141, 6.69%), mirtazapine (n = 129, 6.12%), and lorazepam (n = 110, 5.22%) were among the most frequently prescribed anticholinergic drugs. Univariate analysis demonstrated that all anticholinergic risk assessment scales were closely correlated with polypharmacy, with the strongest association observed for the Anticholinergic Load Scale (ALS) (Odds Ratio = 4.3; p < 0.001). Polypharmacy was also positively associated with adverse drug reactions (Odds Ratio = 1.81; 95% Confidence Interval = 1.27-2.56).

CONCLUSION

The anticholinergic burden in this cohort of elderly psychiatry patients was high, with 95.1% (n = 1108) experiencing a significant burden. Adverse drug events and anticholinergic burden scales were positively associated with polypharmacy, with a stronger correlation between polypharmacy and ALS scores than with other anticholinergic burden scales in older adults.

摘要

引言

精神障碍在老年人中普遍存在,常导致多种药物的使用,其中许多药物具有抗胆碱能特性。多重用药在该人群中很常见,是抗胆碱能负担的主要促成因素,而抗胆碱能负担与认知和身体机能衰退有关。本研究调查了在精神科门诊就诊的老年患者中多重用药与七种抗胆碱能负担量表之间的关系。

方法

研究于2021年12月至2023年3月在印度瑞诗凯诗全印医学科学研究所的精神科门诊进行。纳入年龄≥60岁、正在服用至少一种精神药物且主要工作诊断为精神疾病的老年患者。对所有精神药物进行评估,包括抗抑郁药、抗精神病药、心境稳定剂和催眠药。通过各自的工具计算抗胆碱能负担量表。采用单因素分析确定可能影响多重用药的因素。

结果

研究纳入了1165名年龄≥60岁的老年患者。多重用药的患病率为20.43%(n = 238)。氯硝西泮(n = 364,17.28%)、艾司西酞普兰(n = 197,9.35%)、二甲双胍(n = 165,7.83%)、舍曲林(n = 141,6.69%)、米氮平(n = 129,6.12%)和劳拉西泮(n = 110,5.22%)是最常开具的抗胆碱能药物。单因素分析表明,所有抗胆碱能风险评估量表均与多重用药密切相关,其中抗胆碱能负荷量表(ALS)的相关性最强(比值比 = 4.3;p < 0.001)。多重用药也与药物不良反应呈正相关(比值比 = 1.81;95%置信区间 = 1.27 - 2.56)。

结论

该老年精神科患者队列中的抗胆碱能负担较高,95.1%(n = 1108)的患者承受着显著负担。药物不良事件和抗胆碱能负担量表与多重用药呈正相关,在老年人中,多重用药与ALS评分的相关性强于与其他抗胆碱能负担量表的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/6401daa9aa17/12877_2024_5584_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/34a76e5356fb/12877_2024_5584_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/8a4b146a2b22/12877_2024_5584_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/60441e85b5db/12877_2024_5584_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/6401daa9aa17/12877_2024_5584_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/34a76e5356fb/12877_2024_5584_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/8a4b146a2b22/12877_2024_5584_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/60441e85b5db/12877_2024_5584_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/545c/11744821/6401daa9aa17/12877_2024_5584_Fig4_HTML.jpg

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