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Record W2141113959 · doi:10.1192/bjp.bp.105.020321

Influence of sub-syndromal symptoms after remission from manic or mixed episodes

2006· article· en· W2141113959 on OpenAlexaff
Mauricio Tohen, Charles L. Bowden, Joseph R. Calabrese, Daniel Lin, Tammy Forrester, Athanasios Koukopoulos, Lakshmi N. Yatham, Heinz Grunze

Bibliographic record

VenueThe British Journal of Psychiatry · 2006
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDepressive symptomsOlanzapineMedicineLogistic regressionStepwise regressionBipolar disorderQuality of life (healthcare)Internal medicinePsychiatryLithium (medication)Schizophrenia (object-oriented programming)Cognition

Abstract

fetched live from OpenAlex

BACKGROUND: Sub-syndromal symptoms in bipolar disorder impair functioning and diminish quality of life. AIMS: To examine factors associated with time spent with sub-syndromal symptoms and to characterise how these symptoms influence outcomes. METHOD: In a double-blind randomised maintenance trial, patients received either olanzapine or lithium monotherapy for 1 year. Stepwise logistic regression models were used to identify factors that were significant predictors of percentage time spent with sub-syndromal symptoms. The presence of sub-syndromal symptoms during the first 8 weeks was examined as a predictor of subsequent relapse. RESULTS: Presence of sub-syndromal depressive symptoms during the first 8 weeks significantly increased the likelihood of depressive relapse (relative risk 4.67, P<0.001). Patients with psychotic features and those with a greater number of previous depressive episodes were more likely to experience sub-syndromal depressive symptoms (RR=2.51, P<0.001 and RR=2.35, P=0.03 respectively). CONCLUSIONS: These findings help to identify patients at increased risk of affective relapse and suggest that appropriate therapeutic interventions should be considered even when syndromal-level symptoms are absent.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.223
Teacher spread0.219 · 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.

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

Citations78
Published2006
Admission routes1
Has abstractyes

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