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Bipolar II Postpartum Depression: Detection, Diagnosis, and Treatment

2009· article· en· W2104823766 on OpenAlexaff
Verinder Sharma, Vivien K. Burt, Hendrica L. Ritchie

Bibliographic record

VenueAmerican Journal of Psychiatry · 2009
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsHypomaniaBipolar disorderPsychiatryDepression (economics)Postpartum depressionPostpartum periodBipolar II disorderMoodPsychotic depressionMood disordersPostpartum psychosisPsychologyMedicinePsychosisClinical psychologyManiaPregnancyAnxiety

Abstract

fetched live from OpenAlex

Research on postpartum mood disorders has focused primarily on major depressive disorder, bipolar I disorder, and puerperal psychosis and has largely ignored or neglected bipolar II disorder. Hypomanic symptoms are common after delivery but frequently unrecognized. DSM-IV does not consider early postpartum hypomania as a significant diagnostic feature. Although postpartum hypomania may not cause marked impairment in social or occupational functioning, it is often associated with subsequent, often disabling depression. Preliminary evidence suggests that bipolar II depression arising in the postpartum period is often misdiagnosed as unipolar major depressive disorder. The consequences of the misdiagnosis can be particularly serious because of delayed initiation of appropriate treatment and the inappropriate prescription of antidepressants. Moreover, no pharmacological or psychotherapeutic studies of bipolar postpartum depression are available to guide clinical decision making. Also lacking are screening instruments designed specifically for use before or after delivery in women with suspected bipolar depression. It is recommended that the treatment of postpartum bipolar depression follow the same guidelines as the treatment of nonpuerperal bipolar II depression, using medications that are compatible with lactation.

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 score0.413
Threshold uncertainty score0.417

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 head0.007
GPT teacher head0.262
Teacher spread0.255 · 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

Citations90
Published2009
Admission routes1
Has abstractyes

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