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Record W3124628347 · doi:10.5206/uwomj.v89i1.8588

The case for and against selective serotonin reuptake inhibitors in rapid cycling bipolar disorder

2021· article· en· W3124628347 on OpenAlexaffvenue
D.I. Semenov, Jason Quinn

Bibliographic record

VenueUniversity of Western Ontario Medical Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsBipolar disorderPolypharmacyRapid cyclingPsychiatryDepression (economics)PsychologyMoodMajor depressive disorderMedicinePharmacology

Abstract

fetched live from OpenAlex

Patients affected by the rapid cycling variant of bipolar disorder often experience significant functional difficulties. Physicians caring for affected patients face many challenges managing the turbulent course of this disorder, complicated at times by psychiatric comorbidities (including substance use disorders), polypharmacy, risk management (of suicidality and aggression), and difficulties with community functioning. There is some controversy about the use of selective serotonin receptor inhibitors (SSRIs) in managing bipolar depression, particularly in the rapid cycling variant. The potential benefit of SSRIs in reducing depressive symptoms must be balanced against the risks of mood phase switching and overall worsening of the rapid cycling course. This case report highlights challenges inherent in the application of SSRIs in a case of treatment-refractory rapid cycling bipolar disorder, and discusses the controversy of their use.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.232
Teacher spread0.222 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2021
Admission routes2
Has abstractyes

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