The use of expired resuscitation medications for life-threatening first aid conditions: a systematic search and narrative review
Bibliographic record
Abstract
Introduction: First aid providers may encounter life-threatening conditions requiring treatment with medications. Given that resuscitation medications in first aid kits may be administered infrequently, first aid providers may face situations where only expired medications are available. Objective: This systematic search with a narrative review aims to evaluate the efficacy and safety of expired life-saving medications commonly used in first aid. Methods: We conducted a search of PubMed, EMBASE, Web of Science, CINAHL, and Cochrane Library (inception-April 2025) for studies regarding expired albuterol, epinephrine, aspirin, or naloxone. Two reviewers independently screened titles and abstracts, followed by full-text reviews to determine eligibility. We included randomized controlled trials (RCTs), clinical trials, systematic reviews, meta-analyses, and observational studies evaluating expired medications' potency and safety. Data extraction focused on study design, population, interventions, comparators, outcomes, and key findings. Results: = 3). Albuterol (salbutamol) retained 98 % active drug 20-30 years past expiration. Aspirin (acetylsalicylic acid) could retain active drug for up to 40 years after expiration. Epinephrine autoinjectors could retain epinephrine for at least 36 months after expiration. Naloxone retained active drug for at least 19 months after expiration. There was minimal evidence of harmful degradation products. Conclusions: Under individual study conditions, the evaluated expired first aid medications maintained active drug and were largely free of harmful byproducts beyond their labeled expiration dates. Scientific and ethical principles may suggest possible benefits from expired medications in emergency settings when alternatives are unavailable.
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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 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".