What is the Evidence for Using Intranasal Medicine in the Prehospital Setting? A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: Intranasal (IN) medications offer a safe non-invasive way to rapidly deliver drugs in situations where intravenous (IV) access and intramuscular (IM) administration is challenging or not feasible. In the prehospital setting, this can be an essential alternative in time critical situations including trauma management, seizures, and agitated patients. However, there is a paucity of evidence summarizing its efficacy in this environment. This systematic review aims to assess the current evidence supporting the use of IN medicine (midazolam, ketamine, fentanyl, morphine, glucagon, and naloxone) in the prehospital setting alone. METHODS: A systematic literature search (PROSPERO CRD42023440713) of PubMed, Web of Science, OVID Medline, "Cochrane Central Register of Controlled Trials," Cochrane reviews and Embase was performed from inception to June 2023 to identify studies where IN medications were administered to patients in the prehospital setting. All randomized controlled trials, observational cohort studies, case series, and case reports were included. Papers not written in English, review articles, abstracts, and non-published data (including letters to the editor) were excluded. The methodological quality of the included studies was interpreted using the Cochrane risk of bias tool and rated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. No funding was received. RESULTS: From 4818 studies, 39 were included (seven for midazolam, five for ketamine, twelve for fentanyl, one for diamorphine, two for glucagon, and twelve for naloxone). A total of 24,097 patients were treated with IN medications across all the studies. There were five moderate quality, four low quality, and thirty very low quality studies. The potential efficacy of IN fentanyl and ketamine was demonstrated consistently throughout the studies with less clear evidence for midazolam, morphine, glucagon, and naloxone. This review was severely limited by the study quality, with most studies demonstrating "high concerns" for bias. CONCLUSIONS: Prehospital IN medication administration has wide-ranging potential, particularly for administering analgesia. There are likely to be certain populations, for example, pediatrics, that will benefit the most, although conclusions are limited by the quality of evidence currently available. We encourage additional research in this area, particularly with robust prospective double-blind RCTs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".