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Record W1996411509 · doi:10.1080/09540260802094480

Depression in Alzheimer's disease: Phenomenology, clinical correlates and treatment

2008· review· en· W1996411509 on OpenAlexaff
Sergio Starkstein, Romina Mizrahi, Brian Power

Bibliographic record

VenueInternational Review of Psychiatry · 2008
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
FundersNational Institute of Mental HealthNational Medical Research CouncilNational Health and Medical Research CouncilNational Institutes of Health
KeywordsApathyDepression (economics)DementiaDiseaseSubclinical infectionPsychiatryAlzheimer's diseaseMedicinePsychologySertralineMoclobemideClinical psychologyCognitionAnxietyInternal medicineAntidepressant

Abstract

fetched live from OpenAlex

Depression is one of the most frequent comorbid psychiatric disorders in Alzheimer's disease and other dementias, and is associated with worse quality of life, greater disability in activities of daily living, a faster cognitive decline, a high rate of nursing home placement, relatively higher mortality, and a higher frequency of depression and burden in caregivers. Depression in Alzheimer's disease is markedly under-diagnosed, and most patients with depression are either not treated or are on subclinical doses of antidepressants. This is related to the lack of validated diagnostic criteria and specific instruments to assess depression in dementia. Apathy and pathological affect-crying are the main differential diagnoses of depression in Alzheimer's disease. Left untreated, major depression in Alzheimer's disease may last for about 12 months. Recent randomized controlled trials demonstrated the efficacy of sertraline and moclobemide to treat depression in Alzheimer's disease. Other psychoactive compounds may be useful as well, but careful consideration must be given to potentially serious side-effects.

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 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 score0.845
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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 head0.071
GPT teacher head0.462
Teacher spread0.392 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations104
Published2008
Admission routes1
Has abstractyes

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