PDF(Pubmed)
Abstract：
BACKGROUND: Adverse anticholinergic drug reactions are common, yet evidence on how to reduce exposure to anticholinergic activity and reliably measure successful deprescribing is still scant. This study proposes an algorithm-based approach to evaluate and reduce anticholinergic load, and reports the results of its pilot testing.
METHODS: Based on published evidence and expert opinion, a list of 85 anticholinergic drugs and 21 algorithms for reducing anticholinergic load, e.g., by recommending alternative drugs with lower risk, were developed. An accompanying test battery was assembled by focusing on instruments that sensitively reflect anticholinergic load and may be sensitive to depict changes (Neuropsychological Assessment Battery to measure memory and attention, validated assessments for constipation, urinary symptoms, and xerostomia, as well as blood biomarkers). The approach was pilot-tested in a geriatric rehabilitation unit, with clinician feedback as the primary outcome and characterization of anticholinergic symptoms as the secondary outcome. The intervention was delivered by a pharmacist and a clinical pharmacologist who used the algorithms to generate personalized recommendation letters.
RESULTS: We included a total of 20 patients, 13 with anticholinergic drugs and 7 without. Recommendations were made for 22 drugs in nine patients from the intervention group, of which seven letters (78%) were considered helpful and 8/22 (36%) anticholinergic drugs were discontinued, reducing anticholinergic load in seven patients. In contrast to patients without drug change, memory assessment in patients with reduced anticholinergic load improved significantly after 2 weeks (6 ± 3 vs. -1 ± 6 points).
CONCLUSIONS: The approach was well received by the participating physicians and might support standardized anticholinergic deprescribing.
METHODS: Based on published evidence and expert opinion, a list of 85 anticholinergic drugs and 21 algorithms for reducing anticholinergic load, e.g., by recommending alternative drugs with lower risk, were developed. An accompanying test battery was assembled by focusing on instruments that sensitively reflect anticholinergic load and may be sensitive to depict changes (Neuropsychological Assessment Battery to measure memory and attention, validated assessments for constipation, urinary symptoms, and xerostomia, as well as blood biomarkers). The approach was pilot-tested in a geriatric rehabilitation unit, with clinician feedback as the primary outcome and characterization of anticholinergic symptoms as the secondary outcome. The intervention was delivered by a pharmacist and a clinical pharmacologist who used the algorithms to generate personalized recommendation letters.
RESULTS: We included a total of 20 patients, 13 with anticholinergic drugs and 7 without. Recommendations were made for 22 drugs in nine patients from the intervention group, of which seven letters (78%) were considered helpful and 8/22 (36%) anticholinergic drugs were discontinued, reducing anticholinergic load in seven patients. In contrast to patients without drug change, memory assessment in patients with reduced anticholinergic load improved significantly after 2 weeks (6 ± 3 vs. -1 ± 6 points).
CONCLUSIONS: The approach was well received by the participating physicians and might support standardized anticholinergic deprescribing.
摘要：
背景：抗胆碱能药物不良反应很常见，然而，关于如何减少抗胆碱能活性的暴露并可靠地衡量成功的开处方的证据仍然很少。这项研究提出了一种基于算法的方法来评估和减少抗胆碱能负荷，并报告其试点测试的结果。
方法：根据已发表的证据和专家意见，85种抗胆碱能药物和21种减少抗胆碱能负荷的算法，例如，通过推荐风险较低的替代药物，是开发的。通过专注于敏感地反映抗胆碱能负荷并可能对描绘变化敏感的仪器来组装随附的测试电池（用于测量记忆和注意力的神经心理学评估电池，经验证的便秘评估，泌尿症状,口干症,以及血液生物标志物)。该方法在老年康复部门进行了试点测试，以临床医生的反馈为主要结局，以抗胆碱能症状为次要结局。干预由药剂师和临床药理学家提供，他们使用算法生成个性化推荐信。
结果：我们共纳入20名患者，13与抗胆碱能药物和7没有。对干预组9名患者的22种药物提出了建议，其中7个字母（78％）被认为是有帮助的，8/22（36％）的抗胆碱能药物被停用，减少7例患者的抗胆碱能负荷。与没有药物改变的患者相比，抗胆碱能负荷降低的患者的记忆力评估在2周后显着改善（6±3vs.-1±6分)。
结论：该方法受到参与医师的好评，可能支持标准化的抗胆碱能处方。
方法：根据已发表的证据和专家意见，85种抗胆碱能药物和21种减少抗胆碱能负荷的算法，例如，通过推荐风险较低的替代药物，是开发的。通过专注于敏感地反映抗胆碱能负荷并可能对描绘变化敏感的仪器来组装随附的测试电池（用于测量记忆和注意力的神经心理学评估电池，经验证的便秘评估，泌尿症状,口干症,以及血液生物标志物)。该方法在老年康复部门进行了试点测试，以临床医生的反馈为主要结局，以抗胆碱能症状为次要结局。干预由药剂师和临床药理学家提供，他们使用算法生成个性化推荐信。
结果：我们共纳入20名患者，13与抗胆碱能药物和7没有。对干预组9名患者的22种药物提出了建议，其中7个字母（78％）被认为是有帮助的，8/22（36％）的抗胆碱能药物被停用，减少7例患者的抗胆碱能负荷。与没有药物改变的患者相比，抗胆碱能负荷降低的患者的记忆力评估在2周后显着改善（6±3vs.-1±6分)。
结论：该方法受到参与医师的好评，可能支持标准化的抗胆碱能处方。
