Nimesulide induced Stevens Johnson Syndrome: a case report
Bibliographic record
Abstract
Adverse drug reactions to the prescribed medicines are the major obstacles in continuation of drug treatment. Stevens- Johnson Syndrome (SJS) is a severe, episodic, acute mucocutaneous reaction which is most commonly elicited by drugs and occasionally by infections. Common drugs associated with SJS are sulphonamide antibiotics, anticonvulsants, non- steroidal anti-inflammatory drugs (NSAIDS) and allopurinol. Nimesulide is an NSAID with analgesic and antipyretic properties. Here, we report a case of 21 years old male patient who developed Stevens Johnson Syndrome following ingestion of tablet Nimesulide. The patient was managed with parenteral corticosteroids, antibiotics, emollients, and supportive care. This case highlights the importance of Nimesulide and other NSAIDs as possible cause of SJS. Nimesulide has never been approved in countries like USA, Canada, Australia. But in India it is available as over the counter drug and is used for various indications like fever, myalgia, arthralgia. Therefore, the drugs which are banned outside India should be used with caution and practitioners should report all the adverse drug reactions to such drugs.
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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) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".