The Effect of Butyrophenones for the Management of Primary Headache in the Emergency Department: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The use of butyrophenones for headaches became plausible when the association was established between dopamine and headache. However, despite their positive effect on acute headaches, their use remains controversial. AIM: The goal of this study is to ascertain whether the addition of haloperidol or droperidol to the treatment regimen for acute primary headache lowers the pain score of adult patients in the emergency department. METHODS: A systematic review and meta-analysis was conducted. We searched the following databases for randomised controlled trials (RCTs): PubMed, Cochrane databases, and grey literature, from 1963 to October 2022. Included were RCTs conducted on the use of butyrophenones (IV haloperidol or IV/IM droperidol) in the acute management of primary headaches (diagnosed or undiagnosed), designated prospective, double-blind or open, using only the Visual Analogue Scale (VAS) with a specific measurement time. We excluded non-English studies that lacked translation, studies conducted on paediatric age groups, and studies conducted on animals. RESULTS: Out of 49 articles we included seven, three of which investigated haloperidol. The mean difference in VAS score favoured haloperidol; -2.46 (95% CI: [-4.11 to -0.81]), indicating a drop in VAS score of 2.5/10 units. The mean difference in VAS score for the use of droperidol was -0.35 (95% CI: [-1.24 to 0.54]). CONCLUSION: Haloperidol can induce an acute 25% reduction in VAS score when added to the regimen for acute headache management. It also reduces the need for rescue medications and improves patient satisfaction. Nonetheless, considerable side effects cannot be overlooked.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".