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A Comparison of Antidepressant Response in Younger and Older Women

2003· article· en· W2031214296 on OpenAlexafffund
Sophie Grigoriadis, Sidney H. Kennedy, R. Michael Bagby

Bibliographic record

VenueJournal of Clinical Psychopharmacology · 2003
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
FundersUniversity of Toronto
KeywordsTolerabilityNefazodoneAntidepressantVenlafaxineDepression (economics)Major depressive episodePsychologyInternal medicineMedicineMajor depressive disorderRating scaleHamilton Rating Scale for DepressionSerotonin reuptake inhibitorPsychiatryMoodFluoxetineAnxietyAdverse effectSerotonin

Abstract

fetched live from OpenAlex

The objective of this report is to compare antidepressant response rates and tolerability in younger and older women. One hundred fifteen female outpatients who met DSM-IV criteria for major depressive disorder were evaluated before and after 8 weeks of treatment with a selective serotonin reuptake inhibitor, nefazodone, or venlafaxine. The sample was divided into younger and older groups based on age to approximate premenopausal and postmenopausal status. Eighty-six age-matched male outpatients formed the comparison group. Younger women compared with older women had significantly lower Hamilton Rating Scale for Depression scores after 8 weeks of antidepressant treatment and achieved significant higher rates of remission. There were no differences in overall drug tolerability. This pattern was not replicated in the male patients. Younger women with depression are more responsive to serotonergic antidepressants. This may relate to changes in menstrual status. Limitations of the study and implications for the role of female sex hormones are discussed. Future investigations should include measurement of reproductive hormone levels.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.078
GPT teacher head0.518
Teacher spread0.439 · 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 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

Citations67
Published2003
Admission routes2
Has abstractyes

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