Predicting possible zonisamide hypersensitivity syndrome
Bibliographic record
Abstract
UNLABELLED: Zonisamide (ZNS) is an anticonvulsant (AC) that contains a sulpha moiety potentially triggering hypersensitivity syndrome reactions (HSR). The lymphocyte toxicity assay (LTA) is an in vitro drug rechallenge test, which is believed to reflect a decreased capacity of the individual to detoxify reactive metabolites. The study examined whether cross-reactivity is present between ZNS and other AC and/or sulphonamides and if this HSR may be predicted using the LTA. The second aim was to determine age-related differences in ZNS-induced HSR. LTA was previously validated in patients who received sulphamethoxazole (SMX) or AC. METHODS: Forty adult patients who displayed clinical HSR to SMX (20) or AC (20) participated in the study. Each group was represented with an equal number of individuals above and below the age of 60. LTA-SMX, LTA-AC and LTA-ZNS from 20 patients who previously presented a clinical reaction to one of the drugs and who had a positive LTA result to the specific drug were compared with 20 individuals who received the same drugs but did not present reactions. Binary logistic regression was used to evaluate the statistical significance. RESULTS: In vitro results correlated with the clinical diagnosis. LTA presented a significant difference (P < 0.0001) between control and hypersensitive patients. In each age group, only a single patient had a severe clinical manifestation of SMX-HSR. These individuals tested positive to both SMX and ZNS. CONCLUSIONS: Sulphamethoxazole-HSR but not AC-HSR patients may present a cross-reactivity to ZNS-HSR. The use of LTA to predict a possible ZNS reaction is recommended for SMX-sensitive individuals who prescribed ZNS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".