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Record W3045487155 · doi:10.1177/0898264320943330

Gait Speed Is Associated with Cognitive Function among Older Adults with HIV

2020· article· en· W3045487155 on OpenAlexaboutno aff
Heather M. Derry, Carrie D. Johnston, Chelsie O. Burchett, Eugenia L. Siegler, Marshall J. Glesby

Bibliographic record

VenueJournal of Aging and Health · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Allergy and Infectious DiseasesNational Institute on AgingNational Cancer InstituteGilead Sciences
KeywordsCognitionGrip strengthGaitPhysical medicine and rehabilitationPreferred walking speedMontreal Cognitive AssessmentPhysical therapyMedicineGerontologyEffects of sleep deprivation on cognitive performancePsychologyCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

Objectives: To determine links between objectively and subjectively measured physical function and cognitive function among HIV-positive older adults, a growing yet understudied group with elevated risk for multimorbidity. Methods: At a biomedical research visit, 162 participants completed objective tests of gait speed (4-m walk), grip strength (dynamometer), and cognitive function (Montreal Cognitive Assessment, MoCA) and reported their well-being (Medical Outcomes Study-HIV survey). Results: Those with faster gait speed had better overall cognitive function than those with slower gait speed ( b = 3.98, SE = 1.30, p = .003) in an adjusted regression model controlling for age, sex, race, height, preferred language, and assistive device use. Grip strength was not significantly associated with overall cognitive function. Self-rated cognitive function was weakly related to MoCA scores ( r = .26) and gait speed ( r = .14) but was strongly associated with emotional well-being ( r = .53). Discussion: These observed, expected connections between physical and cognitive function could inform intervention strategies to mitigate age-related declines for older adults with HIV.

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 score0.030
Threshold uncertainty score0.251

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)0.0000.000

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 head0.024
GPT teacher head0.303
Teacher spread0.278 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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