Severe bullous hypersensitivity reactions after exposure to carbamazepine in a Han-Chinese child with a positive HLA-B*1502 and negative in vitro toxicity assays: evidence for different pathophysiological mechanisms.
Bibliographic record
Abstract
BACKGROUND: Drug hypersensitivity syndrome (DHS) can present in several clinical forms ranging from simple maculopapular skin rash to severe bullous reactions and multi-system dysfunction. Genetic analysis of DHS patients has revealed a striking association between carbamazepine (CBZ)-induced severe bullous reactions, such as Steven-Johnson Syndrome, and toxic epidermal necrolysis in individuals from Southeast Asia who carry a specific HLA allele (HLA-B*1502). This ethnic-specific relationship with a disease phenotype has raised the question of the commonality of the pathogenesis mechanisms of these diseases. The aim of this study was to investigate the genetic and metabolic bases of DHS development to help predict patient susceptibility. METHOD: A case of carbamazepine-induced Steven-Johnson Syndrome reaction in a HLA-B*1502 positive child of Han Chinese origin, a carbamazepine-induced DHS case in a Caucasian patient and 3 healthy controls were investigated. We performed two types of in vitro toxicity assay, the lymphocyte toxicity assay (LTA) and the novel in vitro platelet toxicity assay (iPTA) on cells taken from the Chinese child 3 and 9 months after recovery from the reaction and from two healthy volunteers. We also tested the Caucasian patient, who developed CBZ-induced DHS, 3 months after the reaction. RESULTS: Both LTA and iPTA tests were negative 3 and 9 months after the reaction on samples from the Chinese child whereas the tests were positive in the Caucasian patient. CONCLUSION: These results strongly suggest more than one mechanistic pathway for different CBZ-induced hypersensitivity reactions in patients with different ethnic backgrounds.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".