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Record W7116960291 · doi:10.1002/alz70860_106470

How Sex, Frailty, and Neuropathology Modify the Relationship Between Antidepressant Exposure and Alzheimer's Disease: A Retrospective Study

2025· article· en· W7116960291 on OpenAlexaff
Lucy Y Eum, Pilar Robinson Gonzalez, Sanja Stanojevic, Melissa K. Andrew, Shanna Trenaman

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsAntidepressantOddsNeuropathologyOdds ratioRetrospective cohort studyAssociation (psychology)Depression (economics)

Abstract

fetched live from OpenAlex

BACKGROUND: Depression is a modifiable dementia risk factor often treated with antidepressants, but the long-term association between antidepressant use and Alzheimer's Disease (AD) remains unclear. This study examines the association between antidepressant exposure and AD and, whether binary sex, frailty, or neuropathology modifies this relationship. METHODS: This was a retrospective study using secondary data from a multi-site cohort study. We analyzed data from 930 participants aged ≥55 with normal cognition. Frailty was measured using a 30-item frailty index (FI) and frailty phenotype. The primary outcome was the association between antidepressant exposure and clinical diagnosis of AD. Secondary outcomes included potential modification of the association between antidepressant exposure and AD by sex, frailty, or neuropathology index (NPI) scores. The 10-item NPI was constructed using postmortem AD-related brain autopsy findings. Logistic regression was used for statistical analysis. RESULTS: Antidepressant exposure was significantly associated with increased odds of AD (OR 2.51, 95%CI: 1.89-3.34), and this remained significant when adjusted by the age at baseline, sex, FI, and NPI (OR 3.11, 95%CI: 2.23-4.37). When stratified by binary sex, antidepressant use was significantly associated with increased AD odds in females only (OR for females 2.87, 95%CI: 2.05-4.03; OR for males 1.59, 95%CI: 0.91-2.76), and, after adjusting for the age at baseline, FI, and NPI, the association remained significant for females (OR: 3.93, 95%CI: 2.63-5.95) and non-significant for males (OR: 1.86, 95%CI: 1.00-3.47). For secondary outcomes, the association between antidepressant use and AD was not significantly modified by sex, FI, frailty phenotype, or NPI (p >0.05). A scatterplot of FI vs. frailty phenotype showed a positive association between the FI and the frailty phenotype among the subjects not missing frailty phenotype data (Figure 1). CONCLUSION: Antidepressant use was significantly associated with increased odds of AD. When stratified by binary sex, antidepressant use was significantly associated with increased AD odds in females, but not in males. Antidepressant-AD association was not modified by sex, frailty, or NPI. There was a positive association between the FI and the frailty phenotype among those not missing frailty phenotype data. These findings highlight key insights for identifying more modifiable risk factors for dementia.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.052
GPT teacher head0.334
Teacher spread0.283 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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