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Comparison of Montreal cognitive assessment scale and minimental state examination scale in screening HIV-associated neurocognitive disorders in Shenzhen, China

2015· article· en· W3032648571 on OpenAlexaboutno aff
Fang Zhao, Yong Deng, Liqin Sun, Liumei Xu, Shaxi Li, Hui Wang

Bibliographic record

VenueChinese Journal of Clinical Hepatology · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentNeurocognitiveMini–Mental State ExaminationMedicineCognitionCognitive impairmentInternal medicinePsychiatryPhysical therapyPsychology

Abstract

fetched live from OpenAlex

Objective To compare the performance of Montreal cognitive assessment scale (MoCA) and minimental state examination scale (MMSE) in screening HIV-associated neurocognitive disorders (HAND). Methods A case-control study of 127 HIV+ and 60 HIV- individuals. All the subjects' cognitive functions were assessed using MoCA and MMSE separately. Results Mean MoCA score in cases was 26.28±2.43 compared to 27.33±1.30 in controls (P<0.01). Mean MMSE score in cases was 27.45±1.31 compared to 27.70±0.89 in controls (P=0.139). Using the MoCA screening revealed 43(33.9%) cases had HAND compared with 6 (6.7%) controls(χ2=16.01, P<0.001). Using MMSE, 6 (4.7%) cases and 1(1.7%) control had HAND (P=0.124). Conclusion The MoCA scale is more sensitive in deteting HAND than MMSE and is suited for the early cognitive screening of HIV patients in clinic. Key words: Mental statas schedule; Cogniotive dissonance

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 score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.045
GPT teacher head0.418
Teacher spread0.373 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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