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Nimesulide induced toxic epidermal necrolysis: a rare case report

2017· article· en· W2770939440 on OpenAlexaboutno aff
Vineet Kumar, Manju Gari, Kishor Chakraborty, Ravi Ranjan, Anshuman Chandra, Kavita Kumari

Bibliographic record

VenueInternational Journal of Basic & Clinical Pharmacology · 2017
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsnot available
FundersMinistry of Health and Family Welfare
KeywordsNimesulideMedicineToxic epidermal necrolysisDermatologyAntipyreticAdverse effectDrugAdverse drug reactionPharmacologyAnalgesic

Abstract

fetched live from OpenAlex

Adverse drug reactions to the prescribed medicines are the major obstacles in continuation of drug treatment. Nimesulide, a selective cyclo-oxygenase (COX-2) inhibitor was first launched in Italy in 1985 and subsequently marketed in more than 50 countries including India. Due to its better and faster antipyretic action, it has gained popularity among physicians and paediatricians. Here, we report a case of 60 years old male patient who developed toxic epidermal necrolysis (TEN) following ingestion of tablet nimesulide. The patient was managed with parenteral corticosteroids, antibiotics, emollients, anti-fungal and supportive care. This case highlights the importance of nimesulide and other NSAIDs as possible cause of TEN. Nimesulide has never been approved in countries like USA, Canada, Britain, New Zealand, 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 medical practitioners should report all the adverse drug reactions to such drugs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.003
Science and technology studies0.0040.003
Scholarly communication0.0030.005
Open science0.0020.003
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.116
GPT teacher head0.493
Teacher spread0.377 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Basic & Clinical PharmacologySame topicDrug-Induced Adverse ReactionsFrench-language works237,207