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Record W2031897931 · doi:10.1097/yco.0b013e328017f6b1

Tardive dyskinesia: eliminated, forgotten, or overshadowed?

2007· review· en· W2031897931 on OpenAlexaff
Gary Remington

Bibliographic record

VenueCurrent Opinion in Psychiatry · 2007
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsTardive dyskinesiaClozapineAntipsychoticMedicineDyskinesiaPsychiatryAtypical antipsychoticSchizophrenia (object-oriented programming)Internal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The present review focuses on atypical antipsychotics and tardive dyskinesia. RECENT FINDINGS: We have known for many years that clozapine has a diminished risk of tardive dyskinesia compared with typical antipsychotics. The last decade has seen the introduction of a number of other atypical antipsychotics, allowing us to begin evaluating whether they too share this attribute. In addition, the opportunity to use these drugs as first-line treatment permits a more precise means of establishing risk. While longer-term data are required, the limited evidence available clearly indicates that the atypical antipsychotics have a decreased liability of tardive dyskinesia, approximately 1% compared with 5% for typical agents annually. Like clozapine, the other atypical antipsychotics also demonstrate antidyskinetic properties in individuals with preexisting tardive dyskinesia. The underlying mechanisms remain unclear, and without such information it is not possible to say what clinical conditions, if any, might diminish or even eliminate these advantages. SUMMARY: An update is provided regarding the atypical antipsychotics and tardive dyskinesia. This information is critical in our decision-making regarding choice of antipsychotic and optimal use in the clinical setting.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.896
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.182
GPT teacher head0.482
Teacher spread0.300 · 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 teacher head, not a consensus.

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

Citations66
Published2007
Admission routes1
Has abstractyes

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