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Record W2051451279 · doi:10.1155/2014/513108

Clozapine-Induced Myocarditis: Is Mandatory Monitoring Warranted for Its Early Recognition?

2014· article· en· W2051451279 on OpenAlexaff
Tariq Munshi, D. Volochniouk, Tariq Hassan, Nadia Mazhar

Bibliographic record

VenueCase Reports in Psychiatry · 2014
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsClozapineMedicineMyocarditisSchizophrenia (object-oriented programming)AntipsychoticAtypical antipsychoticPsychosisPsychiatryIntensive care medicinePediatricsInternal medicine

Abstract

fetched live from OpenAlex

Clozapine is an atypical antipsychotic used for treatment resistant schizophrenia. Its potential to induce agranulocytosis is well known but it can also cause myocarditis. Clozapine is the only antipsychotic known to induce this side effect, typically early in the treatment, and literature is scarce on this condition. We are presenting a case report of a 21-year-old schizophrenic male who developed myocarditis within 3 weeks of starting on clozapine for his treatment resistant psychosis. We then aim to review some of the available literature and raise awareness among physicians as this condition can potentially be fatal if not detected early.

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)0.005
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 score0.005
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.048
GPT teacher head0.353
Teacher spread0.305 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

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