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Birth‐cohort and dual diagnosis effects on age‐at‐onset in Brazilian patients with bipolar I disorder

2009· article· en· W1981516012 on OpenAlexaff
Pedro Vieira da Silva Magalhães, Fabiano A. Gomes, Maurício Kunz, Flávio Kapczinski

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2009
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British Columbia
FundersUniversidade Federal de Santa MariaNational Alliance for Research on Schizophrenia and DepressionStanley Medical Research Institute
KeywordsAge of onsetBipolar disorderComorbidityCohortSubstance abusePsychiatryDual diagnosisMedicineAlcohol dependencePsychologyYoung adultCohort studyPediatricsAlcohol use disorderInternal medicineAlcoholMoodDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: Substance use disorders and birth-cohort have been associated with an earlier onset in bipolar disorder (BD). This study aimed at evaluating the inter-relations of these factors in age-at-onset in bipolar illness. METHOD: Two-hundred and thirty patients with bipolar I disorder were cross-sectionally evaluated. Patients were categorized into four age groups for analysis. Lifetime comorbidity and age-at-onset were derived from the Structured Clinical Interview for DSM-IV. RESULTS: There was a strong linear association between age group and age-at-onset. Lifetime alcohol and drug use disorders were also associated with age-at-onset. Illicit drug and alcohol use disorders and age group remained significant in the multivariate model. No interactions appeared. CONCLUSION: Both age group and dual diagnoses had strong and independent impacts on age-at-onset in out-patients with BD. Substance abuse may be partly accountable for earlier symptom onset, but other features of BD in younger generations are still in need to be accounted for.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.003
GPT teacher head0.231
Teacher spread0.227 · 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 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

Citations18
Published2009
Admission routes1
Has abstractyes

Explore more

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