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Record W27936072 · doi:10.1177/120347540000400310

Treatment of Self-Mutilation with Olanzapine

2000· article· en· W27936072 on OpenAlexaff
Sylvia Garnis-Jones, Stephen M. Collins, Donald Rosenthal

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2000
Typearticle
Languageen
FieldMedicine
TopicRestraint-Related Deaths
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineOlanzapineDermatologyClinical trialSide effect (computer science)ModalitiesPsychiatrySchizophrenia (object-oriented programming)Internal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Self-mutilation or dermatitis artefacta is a facet of a much broader spectrum of factitial disease. Three nonpsychotic patients with self-mutilation are presented in this article who were successfully treated with low dose olanzapine when all other modalities of therapy had failed, including trials with numerous antidepressants and antipsychotics. OBJECTIVE: The patients were simultaneously evaluated and treated by a dermatologist and a psychiatrist who run the psychodermatology or consultation-liaison clinic based at McMaster University. After dermatologic conditions had been excluded as a cause of the clinical findings, olanzapine was prescribed on a trial basis due to its low risk of parkinsonian side-effects and its antihistaminic properties. CONCLUSIONS: The excellent clinical response of the patients can be attributed to the low side-effect profile of the drug but also to the anti-impulsive effect which stems not only from antihistaminic properties but also from its antidopamine and serotonin-blocking action.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.260
Teacher spread0.242 · 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

Citations40
Published2000
Admission routes1
Has abstractyes

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