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Comorbidity of obsessive‐compulsive disorder in recovered inpatients with bipolar disorder

2000· article· en· W2164323344 on OpenAlexaff
Stephanie Krüger, Peter Bräunig, R.G. Cooke

Bibliographic record

VenueBipolar Disorders · 2000
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsBipolar disorderManiaComorbidityPsychiatryObsessive compulsiveDepression (economics)PsychologyBipolar I disorderClinical psychologyMedicineMood

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the frequency of obsessive-compulsive disorder (OCD) in inpatient subjects with bipolar disorder (BD) and to examine the clinical characteristics of BD subjects with OCD. METHOD: The sample consisted of 143 inpatient subjects with DSM-III-R BD-I and BD-NOS (BD-II), recovered from a current episode of either depression or mania. Demographic and clinical variables were obtained on the day of admission. Current comorbid conditions including OCD were determined by the Structured Clinical Interview for DSM-III-R Ifollowing recovery from the acute affective episode. RESULTS: The frequency of current OCD was 7% (N = 10). All BD subjects with OCD were BD-II, were male, and had a diagnosis of current dysthymia. They had fewer episodes and a higher incidence of prior suicide attempts than bipolar subjects without OCD. None of the bipolar subjects with OCD fulfilled criteria for cyclothymia. CONCLUSIONS: Our findings suggest that BD-II, OCD, dysthymia, and suicidality cluster together in some subjects with BD. We discuss the clinical implications of our findings.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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 designObservational
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

Citations89
Published2000
Admission routes1
Has abstractyes

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