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抗抑郁药的减药:使用 RAND/UCLA 适宜性方法制定高风险和过度处方的指标。

Deprescribing of antidepressants: development of indicators of high-risk and overprescribing using the RAND/UCLA Appropriateness Method.

机构信息

Institute of General Practice and Family Medicine, LMU University Hospital, LMU Munich, Munich, Germany.

Graduate Program "POKAL - Predictors and Outcomes in Primary Care Depression Care", (DFG - GrK 2621), Munich, Germany.

出版信息

BMC Med. 2024 May 13;22(1):193. doi: 10.1186/s12916-024-03397-w.

DOI:10.1186/s12916-024-03397-w
PMID:38735930
原文链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC11089726/
Abstract

BACKGROUND

Antidepressants are first-line medications for many psychiatric disorders. However, their widespread long-term use in some indications (e.g., mild depression and insomnia) is concerning. Particularly in older adults with comorbidities and polypharmacy, who are more susceptible to adverse drug reactions, the risks and benefits of treatment should be regularly reviewed. The aim of this consensus process was to identify explicit criteria of potentially inappropriate antidepressant use (indicators) in order to support primary care clinicians in identifying situations, where deprescribing of antidepressants should be considered.

METHODS

We used the RAND/UCLA Appropriateness Method to identify the indicators of high-risk and overprescribing of antidepressants. We combined a structured literature review with a 3-round expert panel, with results discussed in moderated meetings in between rounds. Each of the 282 candidate indicators was scored on a 9-point Likert scale representing the necessity of a critical review of antidepressant continuation (1-3 = not necessary; 4-6 = uncertain; 7-9 = clearly necessary). Experts rated the indicators for the necessity of review, since decisions to deprescribe require considerations of patient risk/benefit balance and preferences. Indicators with a median necessity rating of ≥ 7 without disagreement after 3 rating rounds were accepted.

RESULTS

The expert panel comprised 2 general practitioners, 2 clinical pharmacologists, 1 gerontopsychiatrist, 2 psychiatrists, and 3 internists/geriatricians (total N = 10). After 3 assessment rounds, there was consensus for 37 indicators of high-risk and 25 indicators of overprescribing, where critical reviews were felt to be necessary. High-risk prescribing indicators included settings posing risks of drug-drug, drug-disease, and drug-age interactions or the occurrence of adverse drug reactions. Indicators with the highest ratings included those suggesting the possibility of cardiovascular risks (QTc prolongation), delirium, gastrointestinal bleeding, and liver injury in specific patient subgroups with additional risk factors. Overprescribing indicators target patients with long treatment durations for depression, anxiety, and insomnia as well as high doses for pain and insomnia.

CONCLUSIONS

Explicit indicators of antidepressant high-risk and overprescribing may be used directly by patients and health care providers, and integrated within clinical decision support tools, in order to improve the overall risk/benefit balance of this commonly prescribed class of prescription drugs.

摘要

背景

抗抑郁药是许多精神疾病的一线药物。然而,它们在某些适应症(如轻度抑郁和失眠)中的广泛长期使用令人担忧。特别是在患有合并症和多种药物治疗的老年患者中,他们更容易出现药物不良反应,因此应定期审查治疗的风险和益处。本共识过程的目的是确定潜在不适当使用抗抑郁药的明确标准(指标),以支持初级保健临床医生识别应考虑停用抗抑郁药的情况。

方法

我们使用 RAND/UCLA 适宜性方法来确定高风险和过度处方抗抑郁药的指标。我们结合了结构化文献综述和 3 轮专家小组,在每轮之间的会议上讨论结果。282 个候选指标中的每一个都在 9 分李克特量表上进行评分,代表对抗抑郁药继续使用进行批判性审查的必要性(1-3=不必要;4-6=不确定;7-9=明确必要)。专家对抗抑郁药继续使用进行批判性审查的必要性进行了评估,因为决定是否停用抗抑郁药需要考虑患者的风险/获益平衡和偏好。在 3 轮评估后,接受了中位数评分为≥7 且无分歧的指标。

结果

专家小组由 2 名全科医生、2 名临床药理学家、1 名老年精神病学家、2 名精神科医生和 3 名内科医生/老年病学家(共 10 人)组成。经过 3 轮评估,有 37 个高风险指标和 25 个过度处方指标达成共识,认为有必要进行批判性审查。高风险处方指标包括存在药物-药物、药物-疾病和药物-年龄相互作用风险或发生药物不良反应的情况。评分最高的指标包括那些表明特定具有附加危险因素的患者亚组存在心血管风险(QTc 延长)、谵妄、胃肠道出血和肝损伤可能性的指标。过度处方指标针对的是抑郁、焦虑和失眠治疗时间长的患者,以及疼痛和失眠高剂量的患者。

结论

抗抑郁药高风险和过度处方的明确指标可由患者和医疗保健提供者直接使用,并整合到临床决策支持工具中,以改善这类常用处方药的总体风险/获益平衡。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/688a/11089726/495dc15138a7/12916_2024_3397_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/688a/11089726/495dc15138a7/12916_2024_3397_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/688a/11089726/495dc15138a7/12916_2024_3397_Fig1_HTML.jpg

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