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Record W4390191718 · doi:10.1002/alz.083184

Cognitive and muscle health, and related amino acid kinetics in older adults with Mild Cognitive Impairment, and the effect of comorbidities

2023· article· en· W4390191718 on OpenAlexaboutno aff
Sofie M De Wandel, Nicolaas E.P. Deutz, M.P. Engelen

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentDepression (economics)Internal medicineMedicineCognitionComorbidityTrail Making TestStroop effectMoodSarcopeniaBody mass indexLean body massPsychologyGerontologyPhysical therapyCognitive impairmentDiseasePsychiatryBody weight

Abstract

fetched live from OpenAlex

Abstract Background Recent studies suggest cognitive decline and reduced muscle health is associated with the presence of comorbidities. Our objective is to identify whether the presence of comorbidities in older adults affects muscle health (mass and function) and related protein and amino acid (AA) kinetics differently when Mild Cognitive Impairment is present. Method We selected older adults (127 with comorbidities (Charlson comorbidity index (CCIS>0)) and120 without comorbidities (CCIS = 0) from the MEDIT database. These were stratified into MCI and non‐MCI based on their Montreal Cognitive Assessment (MoCA) score. Health history obtained by interview, body composition by DEXA, and habitual dietary intake by 3‐day food record, . Mood (depression) assessed by questionnaire, and cognitive function by MoCA and battery. Muscle function measured by handgrip dynamometry. Postabsorptive protein and AA kinetics analyzed by pulse administration of 18 stable isotopes of AAs and tracer enrichments/concentrations by LC‐MS/MS to calculate whole‐body production (WBP) of these AAs. Statistics by ANCOVA to examine effects of MCI, CCIS, and MCI*CCIS interaction, with covariates Sex, BMI, and Age. Significance was set as p<0.05. Result Presence of MCI was associated with lower cognitive and muscle function and lean mass (all p<0.05). There were no differences in lean mass between CCIS and healthy counterparts (all p>0.05). CCIS subjects had higher depression score (p<0.05), performed worse on Stroop test (p = 0.0124) and had lower muscle function (p<0.05). Furthermore, CCIS subjects had higher plasma concentrations of glutamate (p = 0.0115), and isoleucine (p = 0.0071) compared to healthy counterparts. CCIS subjects had higher WBP of phenylalanine (p = 0.032), tryptophan (p = 0.0143), and isoleucine (p = 0.035), and higher net protein breakdown (PHE>>TYR) (p = 0.0758). There was no MCI*CCI interaction for lean mass, dietary intake, or mood. MCI with comorbidities had higher moca scores (p = 0.0037), stroop test performance (p = 0.0592) and muscle function compared to healthy counterparts (all P<0.05). MCI*CCI interactions showed MCI with CCIS had lower BCAA concentrations. Conclusion Presence of comorbidities affects mood, cognitive function, muscle health, and metabolism in older adults independent of MCI. The presence of comorbidities in MCI should be considered when designing nutritional based intervention trials.

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)0.001
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.021
GPT teacher head0.306
Teacher spread0.284 · 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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