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Record W2115493608 · doi:10.1177/2325957414557270

The Montreal Cognitive Assessment

2014· article· en· W2115493608 on OpenAlexaboutno aff
Maggie Chartier, Pierre-Cédric Crouch, Van Tullis, Stephanie Catella, Erin Frawley, Charles Filanosky, Timothy P. Carmody, John R. McQuaid, Harry Lampiris, Joseph K. Wong

Bibliographic record

VenueJournal of the International Association of Providers of AIDS Care (JIAPAC) · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeU.S. Department of Veterans Affairs
KeywordsMontreal Cognitive AssessmentNeurocognitiveMedicineDementiaAnxietyConfidence intervalDepression (economics)CognitionCognitive impairmentClinical psychologyPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

HIV-associated neurocognitive disorders (HANDs) are common, often go undetected, and can impact treatment outcomes. There is limited evidence on how to perform routine cognitive screening in HIV clinical settings. To address this, 44 HIV-positive males were recruited from a Veteran Affairs Infectious Disease clinic and completed the Montreal Cognitive Assessment (MoCA), International HIV Dementia Scale (IHDS), and Depression Anxiety and Stress Scale-21. In all, 50% scored below the MoCA cutoff and 36% scored below the IHDS cutoff. Current CD4 was the strongest predictor of an abnormal MoCA score (P = .007, 95% confidence interval [CI]: 0.987-0.998) and elevated depression was the second strongest predictor (P = .008, CI: 1.043-1.326). Combination antiviral therapy use and age were not significant predictors in this model. The MoCA appeared to be a reasonable screening tool to detect cognitive impairment in HIV-positive patients, and although it is not sufficient to diagnose HAND, it has the potential to provide meaningful clinical data.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.005

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 head0.007
GPT teacher head0.270
Teacher spread0.264 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations16
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the International Association of Providers of AIDS Care (JIAPAC)Same topicHIV Research and TreatmentFrench-language works237,207