MétaCan
Menu
Back to cohort
Record W3089841855 · doi:10.1111/hiv.12963

Neurocognitive evaluation using the International HIV Dementia Scale (IHDS) and Montreal Cognitive Assessment Test (MoCA) in an HIV‐2 population

2020· article· en· W3089841855 on OpenAlexaboutno aff
FABIANA RODRIGUES DE ALMEIDA, Ana Macedo, D Trigo, Miguel Araújo Abreu, Maria Eduarda Adornes Guimarães, Nuno Luís, Raquel Pinho, Raquel Tavares

Bibliographic record

VenueHIV Medicine · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentNeurocognitiveMedicineDementiaPopulationGerontologyNeuropsychologyCognitionOdds ratioClinical psychologyPsychiatryInternal medicineEnvironmental healthDisease

Abstract

fetched live from OpenAlex

OBJECTIVES: We aimed to characterize neurocognitive impairment (NI) in an HIV-2 population using an observational cross-sectional study in four Portuguese hospitals. METHODS: Adult HIV-2-infected patients were included. Montreal Cognitive Assessment Test (MoCA) and International HIV Dementia Scale (IHDS) scales were applied for screening of NI. Patient Health Questionnaire-9 (PHQ-9) and Instrumental Activities of Daily Living (IADL) scales were used for assessment of depression and functionality. A multivariate analysis was performed to assess for risk factors for NI. RESULTS: Eighty-one patients were included, 50.6% of African origin (n = 41) and 49.4% of Portuguese origin (n = 40). The MoCA scale showed alterations in 81.5% of patients (100% of migrants vs. 62.5% of non-migrants, P < 0.001) and the IHDS scale showed alterations in 42%. Both scales were altered simultaneously in 35.8%. Variables independently associated with NI were age [odds ratio (OR) = 0.885] and migrant status (OR = 9.150). CONCLUSIONS: Neurocognitive impairment (both scales altered) was present in 35.8%, which is comparable to what is described for HIV-1. The MoCA performed worse in the migrant population and might not be applicable in this setting.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.053
GPT teacher head0.358
Teacher spread0.305 · 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 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

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueHIV MedicineSame topicHIV Research and TreatmentFrench-language works237,207