Anticonvulsant hypersensitivity syndrome: an update
Bibliographic record
Abstract
INTRODUCTION: Anticonvulsant hypersensitivity syndrome (AHS) is a rare but potentially life-threatening adverse drug reaction, primarily associated with phenytoin, phenobarbital and carbamazepine. It is characterized by a triad of fever, skin eruption and internal organ involvement (usually liver), which occur two to eight weeks after the initiation of therapy. Anticonvulsant hypersensitivity syndrome has been estimated to occur between 1 and 1000 and 1 in 10,000 exposures; however, its true incidence is unknown because of the variable presentation and inaccurate reporting. AREAS COVERED: This paper presents the incidence, epidemiology and pathogenesis of AHS, along with recommendations for its diagnosis and management. EXPERT OPINION: Avoidance of all aromatic anticonvulsants is recommended in patients who develop AHS with one of these agents, as there is a high degree of crossreactivity among all these agents. There are no universally recognized tests for the prediction of AHS due to aromatic anticonvulsants or lamotrigine. Yet genetic testing in a predictive sense would help guide the choice of an appropriate anticonvulsant medication. Other tests, using cellular surrogates, such as lymphocytes or platelets, have been used primarily for diagnostic testing and do not have the universal practicality afforded to genetic tests.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".