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Record W4403137544 · doi:10.1111/head.14841

The effectiveness of parenteral agents to mitigate relapses after severe acute migraine headache presentations: A systematic review and network analysis

2024· review· en· W4403137544 on OpenAlexafffund
Scott W. Kirkland, Jillian Meyer, Lloyd Visser, Sandy Campbell, Cristina Villa‐Roel, Benjamin W. Friedman, Nana Owusu Mensah Essel, Brian H Rowe

Bibliographic record

VenueHeadache The Journal of Head and Face Pain · 2024
Typereview
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsMedicineRelative riskMigrainePlaceboConfidence intervalRandomized controlled trialInternal medicineEmergency departmentMeta-analysisAnesthesia

Abstract

fetched live from OpenAlex

OBJECTIVES: To compare the effectiveness of parenteral agents to reduce relapse in patients with acute migraine and identify factors that predict relapse. BACKGROUND: Following discharge from emergency settings, many patients with acute migraine will experience a relapse in pain; severe relapses may result in re-visits to emergency settings. METHODS: A comprehensive literature search, updated to 2023, was conducted to identify randomized controlled trials assessing the effectiveness of parenteral agents on relapse outcomes in patients with acute migraine discharged from emergency settings. Two independent reviewers completed study selection, quality assessment, and data extraction. A traditional meta-analysis compared parenteral corticosteroids to placebo; a frequentist network analysis assessed direct and indirect comparisons. Results are reported as risk ratios (RRs) and 95% confidence intervals (CIs). The review protocol was registered with the International Prospective Register of Systematic Reviews (identifier: CRD42018099493). RESULTS: = 0%). Patients receiving lidocaine (RR 0.10, 95% CI 0.01-0.82), sedatives/hypnotics (RR 0.33, 95% CI 0.14-0.75), ergot agents (RR 0.44, 95% CI 0.25-0.75), neuroleptics (RR 0.47, 95% CI 0.31-0.71), opioids (RR 0.58; 95% CI 0.35-0.94), or corticosteroids (RR 0.64, 95% CI 0.47-0.86) were significantly less likely to relapse. Lidocaine (RR 0.09, 95% CI 0.01-0.71), combination therapy (RR 0.12, 95% CI 0.02-0.74), or adding corticosteroids (RR 0.61, 95% CI 0.44-0.84) were more likely to reduce severe relapses. Longer duration of headache and residual pain at discharge were significantly associated with higher relapses. DISCUSSION: Corticosteroids remain the recommended first-line option to reduce relapse outcomes. Some parenteral agents typically provided for pain relief including ergot agents, neuroleptics, or combination therapy may effectively reduce relapse; however, opioids are not recommended due to safety concerns. Additional research is needed for some lesser studied, albeit promising, agents including lidocaine and propofol. Effective pain control in emergency settings prior to discharge and duration of headache may play a role in the success of such treatments and further investigations could provide further insight regarding how and why some parenteral agents are effective in mitigating relapse events.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.059
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.020
Bibliometrics0.0120.011
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.367
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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