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慢性肾脏病患者的抗胆碱能负担:模式、危险因素及其与认知障碍的关联。

The anticholinergic burden in patients with chronic kidney disease: Patterns, risk factors, and the link with cognitive impairment.

作者信息

Mouheb Agathe, Levassort Hélène, Massy Ziad A, Jacquelinet Christian, Laville Maurice, Alencar de Pinho Natalia, Pépin Marion, Laville Solène M, Liabeuf Sophie

机构信息

Pharmacoepidemiology Unit, Department of Clinical Pharmacology, Amiens-Picardie University Hospital, Amiens, France.

MP3CV Laboratory, Jules Verne University of Picardie, Amiens, France.

出版信息

J Am Geriatr Soc. 2025 Feb;73(2):533-544. doi: 10.1111/jgs.19283. Epub 2024 Nov 28.

DOI:10.1111/jgs.19283
PMID:39605299
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11825999/
Abstract

BACKGROUND

People with chronic kidney disease (CKD) have an elevated risk of cognitive impairment (CI). Medications with anticholinergic activity are recognized for their adverse reactions on central nervous system. The putative association between the anticholinergic burden and CI has not previously been evaluated in patients with CKD. The study aimed to (i) describe prescriptions of medications with anticholinergic activity, (ii) analyze factors associated with these prescriptions, and (iii) evaluate the anticholinergic burden's association with cognitive performance.

METHODS

CKD-REIN, a prospective cohort study, enrolled nephrology outpatients with a confirmed diagnosis of CKD (eGFR <60 mL/min/1.73m). Drug prescriptions were recorded prospectively during the 5-year follow-up. Mini Mental State Examination (MMSE) was assessed at baseline and CI was defined as an MMSE score <24/30. For each patient, the anticholinergic burden was determined by summing the Anticholinergic Cognitive Burden (ACB) scores of all prescription drugs at baseline. Multinomial logistic regression was used to analyze factors associated with the ACB score. Logistic regression was used to evaluate the association between the cognitive impairment and the anticholinergic burden at baseline.

RESULTS

At baseline, 3007 patients (median age [IQR], 69[60-76]; 65% men) had MMSE data and were included. 1549 (52%) of these patients were taking at least one drug with anticholinergic properties. Most (1092; 70%) had a low anticholinergic burden, 294 (19%) had a moderate anticholinergic burden, and 163 (11%) had a high anticholinergic burden. A history of neurological/psychiatric disorders and a higher number of daily drugs were associated with a greater probability of having a high anticholinergic burden (odds ratio (OR) [95% confidence interval (95% CI)] = 1.88[1.29;2.74] and 1.53[1.45;1.61], respectively). Patients with a high anticholinergic burden had a significantly higher probability of presenting cognitive impairment, compared with patients without an anticholinergic burden (OR[95% CI] = 1.76[1.12;2.75]) after adjustment for sociodemographic factors, comorbidities, laboratory data, and the number of medications taken daily.

CONCLUSIONS

The results of our study emphasize the need for caution in the prescription of drugs with anticholinergic properties to patients with CKD.

摘要

背景

慢性肾脏病(CKD)患者发生认知障碍(CI)的风险升高。具有抗胆碱能活性的药物因其对中枢神经系统的不良反应而为人所知。此前尚未在CKD患者中评估抗胆碱能负担与CI之间的假定关联。本研究旨在:(i)描述具有抗胆碱能活性药物的处方情况;(ii)分析与这些处方相关的因素;(iii)评估抗胆碱能负担与认知表现之间的关联。

方法

CKD-REIN是一项前瞻性队列研究,纳入确诊为CKD(估算肾小球滤过率[eGFR]<60 mL/min/1.73m²)的肾脏病门诊患者。在5年随访期间前瞻性记录药物处方。在基线时评估简易精神状态检查表(MMSE),CI定义为MMSE评分<24/30。对于每位患者,通过将基线时所有处方药的抗胆碱能认知负担(ACB)评分相加来确定抗胆碱能负担。采用多项逻辑回归分析与ACB评分相关的因素。采用逻辑回归评估基线时认知障碍与抗胆碱能负担之间的关联。

结果

在基线时,3007例患者(中位年龄[四分位间距],69[60-76]岁;65%为男性)有MMSE数据并被纳入研究。其中1549例(52%)患者正在服用至少一种具有抗胆碱能特性的药物。大多数(1092例;70%)患者的抗胆碱能负担较低,294例(19%)患者的抗胆碱能负担中等,163例(11%)患者的抗胆碱能负担较高。神经/精神疾病病史和每日用药数量较多与抗胆碱能负担较高的可能性较大相关(优势比[OR][95%置信区间(95%CI)]分别为1.88[1.29;2.74]和1.53[1.45;1.61])。在对社会人口学因素、合并症、实验室数据和每日服用药物数量进行调整后,与无抗胆碱能负担的患者相比,抗胆碱能负担较高的患者出现认知障碍的可能性显著更高(OR[95%CI]=1.76[1.12;2.75])。

结论

我们的研究结果强调,在给CKD患者处方具有抗胆碱能特性的药物时需要谨慎。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f8d/11825999/040bf16af9ec/JGS-73-533-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f8d/11825999/cf5d7f64a8b3/JGS-73-533-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f8d/11825999/c6af0e4541be/JGS-73-533-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f8d/11825999/040bf16af9ec/JGS-73-533-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f8d/11825999/cf5d7f64a8b3/JGS-73-533-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f8d/11825999/c6af0e4541be/JGS-73-533-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f8d/11825999/040bf16af9ec/JGS-73-533-g001.jpg

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