Effectiveness and Safety of Pharmacologic Therapies for Migraine in the Emergency Department: A Systematic Review and Bayesian Network Meta-analysis - 14/12/24

Doi : 10.1016/j.annemergmed.2024.11.004

Ian S. deSouza, MD ^a,^⁎ , Nicole Anthony, MD ^b, Henry Thode, PhD ^c, Robert Allen, MD ^d, Jane Belyavskaya, MD ^e, Jessica Koos, MLS, MSEd ^f, Adam Singer, MD ^g
^a Department of Emergency Medicine, SUNY Downstate Health Sciences University and Kings County Hospital Center, Brooklyn, NY
^b Department of Emergency Medicine, New York-Presbyterian Brooklyn Methodist Hospital, Brooklyn, NY
^c Emergency Medicine Research Center, Stony Brook University, Stony Brook, NY
^d Department of Emergency Medicine, LA General Medical Center, Los Angeles, CA
^e Department of Emergency Medicine, SUNY Downstate Health Sciences University and Kings County Hospital Center, Brooklyn, NY
^f Health Sciences Library, Stony Brook University, Stony Brook, NY
^g Department of Emergency Medicine, Stony Brook University, Stony Brook, NY

^∗Corresponding author.

Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le Saturday 14 December 2024

Abstract

Study objective

We performed a systematic review and Bayesian network meta-analysis to determine which pharmacologic therapies are relatively more effective and safer for migraine in adult patients who present to the emergency department (ED).

Methods

We searched MEDLINE, Embase, and Web of Science from inception to February 9, 2024. Eligible studies were randomized controlled trials that enrolled adult participants presenting to ED with migraine and compared one pharmacologic therapy to another or placebo. Outcomes were as follows: 1) adequate pain relief at 2 hours, 2) change in pain intensity at 1 hour, 3) need for rescue drug at 2 hours, and 4) significant adverse reaction. We extracted data according to PRISMA-network meta-analysis and appraised trials using Cochrane RoB 2. For dichotomous outcomes, we performed Bayesian network meta-analysis to calculate odds ratios with 95% credible intervals; for continuous outcomes, we performed frequentist network meta-analysis to calculate mean differences with 95% confidence intervals. We assessed confidence using Confidence in Network Meta-analysis. We used Surface under the cumulative ranking curve (SUCRA) to rank agents.

Results

Chlorpromazine intravenous (IV)/intramuscular (IM) (SUCRA=87.3%) was most likely to be superior for “adequate pain relief at 2 hours” (24 trials; n=2,361); metoclopramide IV-ibuprofen IV (SUCRA=94.6%) was most likely to be superior for “need for rescue drug” (not needing rescue drug) at 2 hours (27 trials; n=2,942); dexamethasone IV (SUCRA=79.5%) was most likely to be superior for “significant adverse reaction” (not causing adverse reaction) (22 trials; n=2,450). The network for change in pain intensity demonstrated statistically significant incoherence at the overall level. Confidence in network meta-analysis estimates (certainty of evidence) varied and was mostly “low” or “very low,” limiting the validity of the probabilistic analyses.

Conclusions

According to Bayesian network meta-analysis, ibuprofen IV is definitely among the least effective for adequate pain relief; chlorpromazine IV/IM is definitely among the most effective; valproate IV is definitely among the least effective, and ketorolac IV/IM is possibly among the least effective as single agents. The relative safety of the pharmacologic therapies cannot be determined with sufficient certainty.

Le texte complet de cet article est disponible en PDF.

Keywords : Migraine, Migraine therapies, Pain relief

Plan

	Please see page XX for the Editor’s Capsule Summary of this article.
	Supervising editor: Clifton Callaway, MD. Specific detailed information about possible conflicts of interest for individual editors is available at editors.
	Author contributions: All authors contributed to the study conception and design. JK prepared the systematic review. AS and Id performed the study selection. NA, JB, RA, and Id performed the data collection. RA and NA performed the study quality assessment. HT Jr. and Id performed the analysis. Id wrote the first draft of the manuscript, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Id takes responsibility for the paper as a whole.
	Data sharing statement: All data for the network meta-analyses are included in the supplementary material. Analytic code for this investigation is available upon request from the date of article publication by contacting Ian deSouza, MD, at ian.desouza@downstate.edu.
	All authors attest to meeting the four ICMJE.org authorship criteria: (1) Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND (2) Drafting the work or revising it critically for important intellectual content; AND (3) Final approval of the version to be published; AND (4) Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
	Funding and support: By Annals’ policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article as per ICMJE conflict of interest guidelines (see www.icmje.org). AS is on the speakers bureau and a consultant for AstraZeneca. Id, HT Jr, NA, RA, JB, and JK declare that they have no financial interests. The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
	Presentation information: Presented at ACEP22 Research Forum in San Francisco, CA, October 1, 2022