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Record W3092577559 · doi:10.1002/oby.22969

Antidepressant Medications and Weight Change: A Narrative Review

2020· review· en· W3092577559 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

VenueObesity · 2020
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of TorontoBrain and Cognition Discovery FoundationUniversity Health Network
Fundersnot available
KeywordsMirtazapineWeight gainAntidepressantMedicineAdverse effectWeight lossBupropionWeight changeAppetiteEscitalopramPsychiatryBody weightInternal medicineObesityAnxietySmoking cessation

Abstract

fetched live from OpenAlex

Antidepressant medications are the first-line treatment option for moderate to severe major depressive disorder. However, most antidepressants have numerous documented adverse events, including cardiometabolic effects and weight gain, which are major public health concerns. Antidepressant agents provide varying risk of associated weight gain, including significant within-class differences. Some agents, such as mirtazapine, show significant levels of weight gain, while others, such as bupropion, demonstrate weight-loss effects. Current findings suggest the role of histamine and serotonin off-target appetite-promoting pathways in adverse weight-gain effects. Therefore, controlling for undesired weight effects is an important consideration for the selection of antidepressants.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.892
Threshold uncertainty score1.000

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 head0.068
GPT teacher head0.381
Teacher spread0.313 · 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