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Association Between Perceived Physical Fatigability And Cognitive Performance: Study Of Muscle, Mobility, And Aging (SOMMA)

2023· article· en· W4387061905 on OpenAlexaboutno aff
Benjamin T. Schumacher, Caterina Rosano, Yujia Qiao, Andrea Rosso, Peggy M. Cawthon, Stephen B. Kritchevsky, Nancy W. Glynn

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsDigit symbol substitution testMontreal Cognitive AssessmentCalifornia Verbal Learning TestCognitionMedicineTrail Making TestVerbal memoryEffects of sleep deprivation on cognitive performanceAudiologyPsychologyPhysical therapyPsychiatryCognitive impairmentPlacebo

Abstract

fetched live from OpenAlex

Higher perceived fatigability—the quantification of vulnerability to fatigue in relation to specific intensity and duration of activities—is associated with poorer central nervous system health, including lower volumes of the thalamus and hippocampus. Understanding whether perceived fatigability is related to cognitive function may inform interventions to prolong independence and improve cognitive outcomes. PURPOSE: Examine the association between perceived physical fatigability and four cognitive function assessments in older adults. METHODS: At baseline, SOMMA participants completed the Pittsburgh Fatigability Scale (PFS) Physical subscale (range 0 - 50; higher scores = greater fatigability) and four cognitive function assessments [Digit Symbol Substitution Test (DSST), Montreal Cognitive Assessment (MoCA), Trails Making Test Part B (TMT-B), and California Verbal Learning Test (CVLT)]. Analysis of variance was used to compare characteristics across PFS severity strata (0 - 4, 5 - 9, 10 - 14, 15 - 19, 20 - 24, and ≥ 25). Linear regression quantified associations between PFS and cognitive assessment scores adjusting for site, age, sex, race, education, marital status, and history of stroke, cancer, heart failure, and lung disease. RESULTS: In the 814 participants (59.2% women; age 76.2 ± 4.9 years; 86% White), mean PFS score was 15.7 ± 8.6. Prevalence of cognitive impairment was 52% mild (MoCA 18 - 25), 7% moderate (10 - 17), and 0% severe (< 10). Across PFS severity strata, number of correct DSST items was fewer (59 in 0 - 4 and 52 in ≥25) and number of seconds to complete TMT-B was slower (107 in 0 - 4 and 133 in ≥25), both p ≤ 0.01; MoCA and CVLT did not vary. After adjustments, for each 5-point higher PFS (greater fatigability), participants had 1.65 fewer correct DSST items [β coefficient and 95% confidence interval: -1.65 (-2.20, -1.05)] and 4.30 seconds slower TMT-B time [4.30 (2.30, 6.30)]. PFS was not associated with MoCA and CVLT. CONCLUSION: We demonstrate for the first time that greater perceived physical fatigability may be indicative of subtle cognitive changes, particularly in executive function. Future longitudinal work should incorporate PFS Mental to better characterize the nature of this relation. SOMMA funded by NIA R01AG059416. BTS funded by 2T32AG000181-31.

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)0.002
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.042
GPT teacher head0.363
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

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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