Immediate‐ and delayed‐type allergic reactions to amide local anesthetics: clinical features and skin testing
Bibliographic record
Abstract
PURPOSE: Amide type local anesthetic agents are among the most commonly used drugs in medicine. Several adverse drug reactions (ADRs) have been previously described with their use. Among them, allergic reactions are considered rare. The aim of this study was to describe the main characteristics of ADRs induced by amide type local anesthetic drugs. METHODS: We studied reports recorded in the French Pharmacovigilance database and the GERAP database over a 12-year period (1995-2006). For each report, we detailed the clinical features and skin tests used. Delayed or immediate-type allergic reactions and cross-reactivity between amide type local anesthetics were also analyzed. RESULTS: We identified 16 reports (seven from the Pharmacovigilance database and nine from the GERAP database). Local anesthetic allergic reactions occurred mostly in young females (F/M sex ratio = 14:2). An immediate-type allergic reaction was encountered in 11/16 cases. Lidocaine was the local anesthetic most often involved (11/16). Prick test, intradermal reaction, and challenge tests were used to confirm the diagnosis. A cross-reactivity between the different amide type local anesthetics was found in six cases (lidocaine-mepivacaine in all cases). CONCLUSIONS: This is the largest series of immediate-type local anesthetic allergic reactions reported in the literature. Cutaneous symptoms are the main features even though more serious symptoms may occur. Intradermal reaction and challenge tests are very helpful. Because cross-reactivity is not scarce, skin tests should involve several local anesthetics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".