Lidocaine Allergy: Do Positive Patch Results Restrict Future Use?
Bibliographic record
Abstract
BACKGROUND: Adverse reactions from lidocaine are commonly reported. When allergy is suspected, patients may be referred for specific skin testing to confirm the association of their clinical findings. OBJECTIVE: We aimed to investigate 13 cases of suspected lidocaine allergy to analyze if positive patch results restricted future use as an injectable local anesthetic. METHODS: A prospective study was conducted from March 2013 to September 2014 at 2 academic hospital-based patch test clinics in Toronto. Patients were tested to the North American Contact Dermatitis Group standard series (Smart Practice, Phoenix, AZ) and, if suspicion for lidocaine allergy was high, a local anesthetic series (Chemotechnique Diagnostics, Malmö, Sweden) was added. Intradermal skin testing to local anesthetics below irritant concentrations was subsequently conducted in lidocaine-positive patients. If negative, a subcutaneous challenge with 1% lidocaine was done. RESULTS: Thirteen of 756 patients patch tested were positive to lidocaine. Seven patients had relevant reactions to over-the-counter products containing lidocaine, 2 reacted to subcutaneous lidocaine, and 4 had incidental findings. There were no patients with positive results to intradermal testing. Three patients had delayed reactions to the subcutaneous challenge. CONCLUSIONS: Patients with positive patch tests to lidocaine and negative results to intradermal testing and subcutaneous challenge may be safe to use lidocaine as an injectable local anesthetic in the future.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".