Practice advisory for intravenous management of headache disorders in hospitalized patients: a review of the evidence and consensus recommendations
Bibliographic record
Abstract
INTRODUCTION: Patients hospitalized for headache treatment pose unique challenges to the healthcare system. Currently, there is a lack of evidence-based guidance on management. This practice advisory aims to fill this critical gap by systematically reviewing the existing literature and providing comprehensive, evidence-based recommendations for managing headache patients during hospitalization. METHODS: In February 2023, the American Society of Regional Anesthesia and Pain Medicine approved this practice advisory proposal. The steering committee selected committee members based on clinical and research expertise in the field of headache medicine. Nine questions were formulated by the committee, and each question was assigned to a group composed of 3-4 members. A systematic literature search for each question was performed in Medline, Embase, Cochrane Database of Systematic Reviews and Web of Science on June 21, 2023. The results from each search were imported into separate Covidence projects for screening, data extraction, and risk of bias assessment. Additionally, relevant systematic reviews (SR) were screened. Each group submitted a structured narrative review along with statements and recommendations based on the US Preventive Services Task Force (USPSTF) format for grading of evidence. While the USPSTF framework was used, including the language in the recommendations, the formal USPSTF methodology, including the SR with meta-analysis and summary tables with forest plots, was not followed because of low overall evidence quality. The interim draft was shared electronically with each collaborator, who was requested to vote anonymously using two rounds of the modified Delphi approach. A consensus recommendation required >75% agreement. RESULTS: The panel generated 12 statements and 17 recommendations, along with their strength and certainty of evidence. Following two rounds of Delphi voting, a high consensus was achieved for all statements and recommendations. Most statements received a low-to-moderate level of certainty, and all but one recommendation received grade B or C, which was consistent with the lack of randomized controlled trials supporting most of the drugs in this document. CONCLUSIONS: This evidence-based practice advisory provides a foundational step toward standardizing inpatient headache care and highlights existing gaps in the literature that should be addressed through rigorous prospective randomized studies.
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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 | 0.125 | 0.259 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.010 | 0.009 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".