Long-Term Opioid Prescriptions After Spine Surgery: A Meta-Analysis of Prevalence and Risk Factors.


Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
09 2020
Historique:
received: 24 04 2020
revised: 08 06 2020
accepted: 09 06 2020
pubmed: 23 6 2020
medline: 7 1 2021
entrez: 23 6 2020
Statut: ppublish

Résumé

Opioids are frequently prescribed for back pain, but the prevalence of and risk factors for long-term opioid use after spine surgery were not clearly reported. We conducted a systematic review and meta-analysis to summarize the evidence for long-term opioid use (>90 days) among adults who underwent spine surgery. PubMed, EMBASE, and Cochrane indexing databases were searched until November 9, 2018 for studies reporting the prevalence of and risk factors for long-term opioid use after spine surgery. Separate meta-analyses were conducted for commercial claims databases or registries (claims/registries) and nonclaims observational studies using the random-effects model to estimate the pooled odds ratio (OR). Prevalence meta-analysis was performed in a clinically homogeneous subset of these patients who underwent lumbar spine surgery. Eight claims and 5 nonclaims were meta-analyzed to avoid double-counting participants. The meta-analysis showed that preoperative opioid users (OR, 5.59; 95% confidence interval [CI], 3.37-9.27 vs. OR 4.21; 95% CI, 2.72-6.51) and participants with preexisting depression and/or anxiety (OR, 1.86, 95% CI, 1.43-2.42 and OR, 1.20; 95% CI, 0.83-1.74, respectively) had a statistically significantly higher odds of long-term postoperative opioids, compared with their peers. Males showed lower odds of long-term postoperative opioid use in the claims group (OR, 0.85; 95% CI, 0.79-0.92), but not in the nonclaims group (OR, 0.99; 95% CI, 0.71-1.39). The pooled prevalence of post-lumbar spine surgery long-term opioid use was 63% (95% CI, 50%-74%) in claims and 47% (95% CI, 38%-56%) in nonclaims. Patients undergoing spine surgery represent a high-risk surgical population requiring special attention and targeted interventions, with the strongest evidence for those treated with opioids before surgery and those with psychiatric comorbidities.

Sections du résumé

BACKGROUND
Opioids are frequently prescribed for back pain, but the prevalence of and risk factors for long-term opioid use after spine surgery were not clearly reported. We conducted a systematic review and meta-analysis to summarize the evidence for long-term opioid use (>90 days) among adults who underwent spine surgery.
METHODS
PubMed, EMBASE, and Cochrane indexing databases were searched until November 9, 2018 for studies reporting the prevalence of and risk factors for long-term opioid use after spine surgery. Separate meta-analyses were conducted for commercial claims databases or registries (claims/registries) and nonclaims observational studies using the random-effects model to estimate the pooled odds ratio (OR). Prevalence meta-analysis was performed in a clinically homogeneous subset of these patients who underwent lumbar spine surgery.
RESULTS
Eight claims and 5 nonclaims were meta-analyzed to avoid double-counting participants. The meta-analysis showed that preoperative opioid users (OR, 5.59; 95% confidence interval [CI], 3.37-9.27 vs. OR 4.21; 95% CI, 2.72-6.51) and participants with preexisting depression and/or anxiety (OR, 1.86, 95% CI, 1.43-2.42 and OR, 1.20; 95% CI, 0.83-1.74, respectively) had a statistically significantly higher odds of long-term postoperative opioids, compared with their peers. Males showed lower odds of long-term postoperative opioid use in the claims group (OR, 0.85; 95% CI, 0.79-0.92), but not in the nonclaims group (OR, 0.99; 95% CI, 0.71-1.39). The pooled prevalence of post-lumbar spine surgery long-term opioid use was 63% (95% CI, 50%-74%) in claims and 47% (95% CI, 38%-56%) in nonclaims.
CONCLUSIONS
Patients undergoing spine surgery represent a high-risk surgical population requiring special attention and targeted interventions, with the strongest evidence for those treated with opioids before surgery and those with psychiatric comorbidities.

Identifiants

pubmed: 32569762
pii: S1878-8750(20)31339-5
doi: 10.1016/j.wneu.2020.06.081
pii:
doi:

Substances chimiques

Analgesics, Opioid 0

Types de publication

Journal Article Meta-Analysis Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

e894-e920

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Yu Tung Lo (YT)

Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; Department of Neurosurgery, National Neuroscience Institute, Singapore.

Michelle Lim-Watson (M)

School of Pharmacy, MCPHS University, Boston, Massachusetts, USA.

Yookyung Seo (Y)

School of Pharmacy, MCPHS University, Boston, Massachusetts, USA.

Noemi Fluetsch (N)

School of Pharmacy, MCPHS University, Boston, Massachusetts, USA.

Moudi M Alasmari (MM)

College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.

Mona Y Alsheikh (MY)

Clinical Pharmacy Department, School of Pharmacy, Taif University, Taif, Saudi Arabia.

Nayan Lamba (N)

Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; Harvard Radiation Oncology Program, Boston, Massachusetts, USA.

Timothy R Smith (TR)

Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA.

Linda S Aglio (LS)

Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; Department of Anesthesiology, Perioperative, and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.

Rania A Mekary (RA)

Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; School of Pharmacy, MCPHS University, Boston, Massachusetts, USA. Electronic address: rania.mekary@channing.harvard.edu.

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Classifications MeSH