Intranasal Lidocaine for Acute Management of Primary Headaches: A Systematic Review
Bibliographic record
Abstract
Intranasal lidocaine has been studied and recommended as an alternative in the management of acute headache. The objective of this systematic review was to evaluate the efficacy and safety of intranasal lidocaine in the acute management of primary headaches. The MEDLINE (1946 to May 2018), EMBASE (1974 to May 2018), Cochrane Central Register of Controlled Trials (2008 to May 2018), Cumulative Index to Nursing and Allied Health Literature (CINAHL) (1982 to May 2018), and ClincialTrials.gov online databases were searched. Studies conducted in patients with acute primary headache were included if lidocaine was compared with placebo or alternative treatments, lidocaine dosing was specified, and patients' pain before and after treatment were clearly reported. Six studies met the inclusion criteria. Intranasal lidocaine demonstrated potential benefit over placebo in acute pain reduction and need for rescue medication only in the four studies deemed to be of poor quality, not in the two fair-quality studies. No study reported benefit in preventing headache recurrence or repeat visits to the emergency department. Lidocaine was associated with significantly higher rates of adverse events compared with placebo and may result in lower rates of patient satisfaction. There is insufficient evidence to support the use of intranasal lidocaine in acute management of primary headaches. Further research is warranted to better elucidate whether intranasal lidocaine has a role in the management of specific primary headache subtypes and whether there is an optimal regimen.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".