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Role of Estrogen in the Treatment of Depression

2002· review· en· W2049329725 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Therapeutics · 2002
Typereview
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsEstrogenMedicineAntidepressantMoodDepression (economics)Mood disordersPsychiatryPlaceboMajor depressive disorderInternal medicineAlternative medicineAnxiety

Abstract

fetched live from OpenAlex

The role of estrogen in the treatment of depression is reviewed. The relation is examined in studies of perimenopausal and postmenopausal women with depressed mood, in studies of depressive disorders, and in studies of estrogen as an adjunct to antidepressant medication. The literature has many methodologic shortcomings, including combining women of various ages, failure to confirm life stage, the use of different types of estrogens, the inclusion of women with a range of mood disturbances, and the enrollment of women with concurrent psychiatric illness. There are few controlled evaluations of the use of estrogen to supplement ongoing antidepressant treatment. Estrogen alone seems to be beneficial for improving mood in perimenopausal and postmenopausal women. Estrogen is superior to placebo for reproductive-related mood disorders, including postpartum depression and mild depressive disorders during perimenopause. Replication is necessary, especially in moderate to severe levels of major depression. Estrogen may augment antidepressant treatment. Assessment and treatment implications are discussed.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.100
GPT teacher head0.412
Teacher spread0.312 · 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