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Prevalence of Depression in Patients With Mild Cognitive Impairment

2016· review· en· W2552864116 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

VenueJAMA Psychiatry · 2016
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of ManitobaHotchkiss Brain InstituteSt. Michael's HospitalUniversity of Calgary
Fundersnot available
KeywordsDepression (economics)PsycINFOMedicineMEDLINEDementiaPopulationPsychiatryMeta-analysisClinical psychologyInternal medicineDisease

Abstract

fetched live from OpenAlex

IMPORTANCE: Depression is common in individuals with mild cognitive impairment (MCI) and may confer a higher likelihood of progression to dementia. Prevalence estimates of depression in those with MCI are required to guide both clinical decisions and public health policy, but published results are variable and lack precision. OBJECTIVE: To provide a precise estimate of the prevalence of depression in individuals with MCI and identify reasons for heterogeneity in the reported results. DATA SOURCES: A search of literature from database inception to March 2016 was performed using Medline, Embase, and PsycINFO. Hand searching of all included articles was performed, including a Google Scholar search of citations of included articles. STUDY SELECTION: Articles were included if they (1) were published in English, (2) reported patients with MCI as a primary study group, (3) reported depression or depressive symptoms using a validated instrument, and (4) reported the prevalence of depression in patients with MCI. DATA EXTRACTION AND SYNTHESIS: All abstracts, full-text articles, and other sources were reviewed, with data extracted in duplicate. The overall prevalence of depression in patients with MCI was pooled using a random-effects model. Heterogeneity was explored using stratification and random-effects meta-regression. MAIN OUTCOMES AND MEASURES: The prevalence of depression in patients with MCI, reported as a percentage with 95% CIs. Estimates were also stratified by population source (community-based or clinic-based sample), method of depression diagnosis (clinician-administered, informant-based, or self-report), and method of MCI diagnosis (cognitive vs global measure and amnestic vs nonamnestic). RESULTS: Of 5687 unique abstracts, 255 were selected for full-text review, and 57 studies, representing 20 892 patients, met all inclusion criteria. The overall pooled prevalence of depression in patients with MCI was 32% (95% CI, 27-37), with significant heterogeneity between estimates (I2 = 90.7%). When stratified by source, the prevalence of depression in patients with MCI in community-based samples was 25% (95% CI, 19-30) and was 40% (95% CI, 32-48) in clinic-based samples, which was significantly different (P < .001). The method used to diagnose depression did not significantly influence the prevalence estimate, nor did the criteria used for MCI diagnosis or MCI subtype. CONCLUSIONS AND RELEVANCE: The prevalence of depression in patients with MCI is high. A contributor to heterogeneity in the reported literature is the source of the sample, with greater depression burden prevalent in clinic-based samples.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.422
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.337
Teacher spread0.321 · 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