预测慢性疼痛患者处方阿片类药物后致死和非致死性药物过量的因素：观察性研究的系统评价和荟萃分析。

Predictors of fatal and nonfatal overdose after prescription of opioids for chronic pain: a systematic review and meta-analysis of observational studies.

机构信息

Department of Anesthesia (L. Wang, Busse); The Michael G. DeGroote Institute for Pain Research and Care (L. Wang, Rehman, Couban, Busse); Department of Health Research Methods, Evidence & Impact (L. Wang, Rehman, Busse), McMaster University, Hamilton, Ont.; Department of Anesthesiology and Pain Medicine (P.J. Hong), University of Toronto, Toronto, Ont.; Faculty of Health Science (Jiang), McMaster University, Hamilton, Ont.; Division of Plastic Surgery, Department of Surgery (B.Y. Hong), University of Toronto, Toronto, Ont.; Guangdong Science and Technology Library (C. Wang), Institute of Information, Guangdong Academy of Sciences, Guangzhou, China; Department of Biomedical Informatics (Hayes), College of Medicine, University of Arkansas for Medical Sciences, Little Rock, Ark.; Center for Mental Healthcare and Outcomes Research (Hayes), Central Arkansas Veterans Healthcare System, North Little Rock, Ark.; Sunnybrook Health Sciences Centre (Juurlink); Institute for Clinical Evaluative Sciences (Juurlink); Institute of Health Policy, Management, and Evaluation (Juurlink), University of Toronto, Toronto, Ont.

出版信息

CMAJ. 2023 Oct 23;195(41):E1399-E1411. doi: 10.1503/cmaj.230459.

BACKGROUND

Higher doses of opioids, mental health comorbidities, co-prescription of sedatives, lower socioeconomic status and a history of opioid overdose have been reported as risk factors for opioid overdose; however, the magnitude of these associations and their credibility are unclear. We sought to identify predictors of fatal and nonfatal overdose from prescription opioids.

METHODS

We systematically searched MEDLINE, Embase, CINAHL, PsycINFO and Web of Science up to Oct. 30, 2022, for observational studies that explored predictors of opioid overdose after their prescription for chronic pain. We performed random-effects meta-analyses for all predictors reported by 2 or more studies using odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Twenty-eight studies (23 963 716 patients) reported the association of 103 predictors with fatal or nonfatal opioid overdose. Moderate- to high-certainty evidence supported large relative associations with history of overdose (OR 5.85, 95% CI 3.78-9.04), higher opioid dose (OR 2.57, 95% CI 2.08-3.18 per 90-mg increment), 3 or more prescribers (OR 4.68, 95% CI 3.57-6.12), 4 or more dispensing pharmacies (OR 4.92, 95% CI 4.35-5.57), prescription of fentanyl (OR 2.80, 95% CI 2.30-3.41), current substance use disorder (OR 2.62, 95% CI 2.09-3.27), any mental health diagnosis (OR 2.12, 95% CI 1.73-2.61), depression (OR 2.22, 95% CI 1.57-3.14), bipolar disorder (OR 2.07, 95% CI 1.77-2.41) or pancreatitis (OR 2.00, 95% CI 1.52-2.64), with absolute risks among patients with the predictor ranging from 2-6 per 1000 for fatal overdose and 4-12 per 1000 for nonfatal overdose.

INTERPRETATION

We identified 10 predictors that were strongly associated with opioid overdose. Awareness of these predictors may facilitate shared decision-making regarding prescribing opioids for chronic pain and inform harm-reduction strategies SYSTEMATIC REVIEW REGISTRATION: Open Science Framework (https://osf.io/vznxj/).

背景

有研究报道，阿片类药物的高剂量、精神健康合并症、镇静剂的联合处方、较低的社会经济地位和阿片类药物过量史是阿片类药物过量的风险因素；然而，这些关联的程度及其可信度尚不清楚。我们试图确定处方类阿片类药物致致命和非致命性药物过量的预测因素。

方法

我们系统地检索了 MEDLINE、Embase、CINAHL、PsycINFO 和 Web of Science，检索时间截至 2022 年 10 月 30 日，以寻找探索慢性疼痛患者处方类阿片类药物后发生阿片类药物过量预测因素的观察性研究。我们使用比值比（ORs）和 95%置信区间（CIs），对 2 项或以上研究报告的所有预测因素进行了随机效应荟萃分析。

结果

28 项研究（23963716 名患者）报告了 103 个预测因素与致命或非致命性阿片类药物过量的关系。有中度到高度确定性证据支持以下预测因素与阿片类药物过量史（OR 5.85，95%CI 3.78-9.04）、较高的阿片类药物剂量（OR 2.57，95%CI 90 毫克增量 2.08-3.18）、3 名或以上开处方的医生（OR 4.68，95%CI 3.57-6.12）、4 家或以上配药的药店（OR 4.92，95%CI 4.35-5.57）、芬太尼处方（OR 2.80，95%CI 2.30-3.41）、当前物质使用障碍（OR 2.62，95%CI 2.09-3.27）、任何精神健康诊断（OR 2.12，95%CI 1.73-2.61）、抑郁症（OR 2.22，95%CI 1.57-3.14）、双相情感障碍（OR 2.07，95%CI 1.77-2.41）或胰腺炎（OR 2.00，95%CI 1.52-2.64）之间存在强关联，有预测因素的患者发生致命性药物过量的绝对风险在每 1000 人中为 2-6 例，发生非致命性药物过量的绝对风险为每 1000 人中 4-12 例。