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Record W2192846808 · doi:10.4088/jcp.14m09395

Inflammatory Markers Among Adolescents and Young Adults With Bipolar Spectrum Disorders

2015· article· en· W2192846808 on OpenAlexafffund
Benjamin I. Goldstein, Francis E. Lotrich, David Axelson, Mary Kay Gill, Heather Hower, Tina R. Goldstein, Jieyu Fan, Shirley Yen, Rasim Somer Diler, Daniel P. Dickstein, Michael Strober, Satish Iyengar, Neal D. Ryan, Martin B. Keller, Boris Birmaher

Bibliographic record

VenueThe Journal of Clinical Psychiatry · 2015
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Institute of Mental HealthCanadian Institutes of Health Research
KeywordsSpectrum (functional analysis)MedicinePsychologyClinical psychologyPhysics

Abstract

fetched live from OpenAlex

OBJECTIVE: Despite burgeoning literature in middle-aged adults, little is known regarding proinflammatory markers (PIMs) among adolescents and young adults with bipolar disorder. Similarly, few prior studies have considered potential confounds when examining the association between PIMs and bipolar disorder characteristics. We therefore retrospectively examined these topics in the Course and Outcome of Bipolar Youth (COBY) study. METHOD: Subjects were 123 adolescents and young adults (mean [SD] = 20.4 ± 3.8 years; range, 13.4-28.3 years) in COBY, enrolled between October 2000 and July 2006. DSM-IV diagnoses were determined using the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS). Clinical characteristics during the preceding 6 months, including mood, comorbidity, and treatment, were evaluated using the Longitudinal Interval Follow-Up Evaluation (LIFE). Serum levels of interleukin (IL)-6, tumor necrosis factor (TNF)-α, and high-sensitivity C-reactive protein (hsCRP) were assayed. Primary analyses examined the association of PIMs with bipolar disorder characteristics during the preceding 6 months. RESULTS: Several lifetime clinical characteristics were significantly associated with PIMs in multivariable analyses, including longer illness duration (P = .005 for IL-6; P = .0004 for hsCRP), suicide attempts (P = .01 for TNF-α), family history of suicide attempts or completion (P = .01 for hsCRP), self-injurious behavior (P =.005 for TNF-α), substance use disorder (SUD) (P < .0001 for hsCRP), and family history of SUD (P = .02 for TNF-α; P = .01 for IL-6). The following bipolar disorder characteristics during the preceding 6 months remained significantly associated with PIMs in multivariable analyses that controlled for differences in comorbidity and treatment: for TNF-α, percentage of weeks with psychosis (χ(2) = 5.7, P =.02); for IL-6, percentage of weeks with subthreshold mood symptoms (χ(2)= 8.3, P = .004) and any suicide attempt (χ(2) = 6.1, P = .01); for hsCRP, maximum severity of depressive symptoms (χ(2) = 8.3, P =.004). CONCLUSION: Proinflammatory markers may be relevant to bipolar disorder characteristics as well as other clinical characteristics among adolescents and young adults with bipolar disorder. Traction toward validating PIMs as clinically relevant biomarkers in bipolar disorder will require repeated measures of PIMs and incorporation of relevant covariates.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.293
Teacher spread0.271 · 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

Citations75
Published2015
Admission routes2
Has abstractyes

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