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Record W2118098636 · doi:10.1139/jpn.0332

A review of olanzapine-associated toxicity and fatality in overdose

2003· review· en· W2118098636 on OpenAlexaffvenueabout
Pierre Chue, Peter P. Singer

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2003
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsOffice of the Chief Medical ExaminerUniversity of Alberta Hospital
Fundersnot available
KeywordsOlanzapineMedicineToxicityCase fatality rateDrug overdoseIntensive care medicineEmergency medicinePsychiatryInternal medicinePoison controlSchizophrenia (object-oriented programming)Epidemiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Given the increasing use of atypical antipsychotics in psychiatric populations and the very limited data concerning the safety of such drugs, we examined the available data on olanzapine in untreated overdose situations. METHODS: Available toxicity data concerning olanzapine were obtained from the Offices of the Medical Examiners of Canada, the Canadian Adverse Drug Reaction Monitoring Program and a review of the literature. RESULTS: Despite the complexities and limitations of postmortem data analysis, 29 deaths were identified where an overdose of olanzapine was either the principal cause of toxicity or a significant contributor in combined toxicity. CONCLUSIONS: Olanzapine is associated with toxicity in certain overdose situations, but evidence of any relation is limited and likely influenced by the higher rates of cardiovascular disease and sudden death in subjects with schizophrenia. RECOMMENDATIONS: Similar toxicity data reviews should be conducted for all commonly prescribed psychotropics. Early signal detection and effective notification processes are crucial in the event that serious adverse effects do occur.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.066
GPT teacher head0.393
Teacher spread0.327 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations53
Published2003
Admission routes3
Has abstractyes

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