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Record W2113230922 · doi:10.1002/gps.636

Gender, aggression and serotonergic function are associated with response to sertraline for behavioral disturbances in Alzheimer's disease

2002· article· en· W2113230922 on OpenAlexafffund
Krista L. Lanctôt, Nathan Herrmann, Robert van Reekum, Goran Eryavec, Claudio A. Naranjo

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2002
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsBaycrest HospitalHealth Sciences CentreWomen's College HospitalUniversity of TorontoNorth York General HospitalSunnybrook Health Science Centre
FundersPhysicians' Services Incorporated Foundation
KeywordsSerotonergicSertralineAggressionIrritabilityPsychologyPlaceboFenfluraminePsychiatryInternal medicineMedicineClinical psychologySerotoninAntidepressantAnxiety

Abstract

fetched live from OpenAlex

BACKGROUND: Indications for serotonergic medications in the treatment of behavioral disorders associated with Alzheimer's disease (AD) remain to be established. METHOD: Sertraline (100 mg OD) was evaluated in a double-blind, randomized, placebo-controlled cross-over study in 22 nondepressed patients with severe probable AD and significant behavioral disturbance. Each subject was given a fenfluramine challenge to evaluate central serotonergic tone. RESULTS: Eight of 21 (38%) completers responded to sertraline. Drug responsive behaviors included aggression/agitation, irritability and aberrant motor behavior. Low aggression, female gender and large prolactin increase were associated with a better response. There was a trend for decreased aggression during sertraline versus placebo (p = 0.08). CONCLUSION: Aggression, gender and serotonergic function were associated with sertraline response. Larger randomized controlled trials are needed to clarify the profile of responders.

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)0.001
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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.035
GPT teacher head0.339
Teacher spread0.304 · 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

Citations66
Published2002
Admission routes2
Has abstractyes

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Same venueInternational Journal of Geriatric PsychiatrySame topicDementia and Cognitive Impairment ResearchFrench-language works237,207