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Record W4400839093 · doi:10.2196/58316

Graded Intensity Aerobic Exercise to Improve Cerebrovascular Function and Performance in Older Veterans: Protocol for a Randomized Controlled Trial

2024· article· en· W4400839093 on OpenAlexvenueno aff
Medina Bello, Kevin Mammino, Mark Vernon, Daniel G. Wakeman, Chanse Denmon, Lisa C. Krishnamurthy, Venkatagiri Krishnamurthy, Keith McGregor, Thomas Novak, Joe R. Nocera

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersU.S. Department of Veterans Affairs
KeywordsPhysical medicine and rehabilitationAerobic exercisePopulationFunctional magnetic resonance imagingCognitionCognitive declineMedicinePhysical therapyCardiovascular fitnessQuality of life (healthcare)Cognitive trainingRandomized controlled trialPsychological interventionPsychologyPhysical fitnessDementiaNeurosciencePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Growing health care challenges resulting from a rapidly expanding aging population necessitate examining effective rehabilitation techniques that mitigate age-related comorbidity and improve quality of life. To date, exercise is one of a few proven interventions known to attenuate age-related declines in cognitive and sensorimotor functions critical to sustained independence. OBJECTIVE: This work aims to implement a multimodal imaging approach to better understand the mechanistic underpinnings of the beneficial exercise-induced adaptations to sedentary older adults' brains and behaviors. Due to the complex cerebral and vascular dynamics that encompass neuroplastic change with aging and exercise, we propose an imaging protocol that will model exercise-induced changes to cerebral perfusion, cerebral vascular reactivity (CVR), and cognitive and sensorimotor task-dependent functional magnetic resonance imaging (fMRI) after prescribed exercise. METHODS: test, basal cerebral perfusion using arterial spin labeling (ASL), CVR using hypercapnic fMRI, and cortical activation using fMRI during verbal fluency and motor tapping tasks. A battery of cognitive-executive and motor function tasks outside the scanning environment will be performed before and after the interventions. RESULTS: Our studies and others show that improved cardiovascular fitness in older adults results in improved outcomes related to physical and cognitive health as well as quality of life. A consistent but unexplained finding in many of these studies is a change in cortical activation patterns during task-based fMRI, which corresponds with improved task performance (cognitive-executive and motor). We hypothesize that the 12-week aerobic exercise intervention will increase basal perfusion and improve CVR through a greater magnitude of reactivity in brain areas susceptible to neural and vascular decline (inferior frontal and motor cortices) in previously sedentary older adults. To differentiate between neural and vascular adaptations in these regions, we will map changes in basal perfusion and CVR over the inferior frontal and the motor cortices-regions we have previously shown to be beneficially altered during fMRI BOLD (blood oxygen level dependent), such as verbal fluency and motor tapping, through improved cardiovascular fitness. CONCLUSIONS: Exercise is one of the most impactful interventions for improving physical and cognitive health in aging. This study aims to better understand the mechanistic underpinnings of improved health and function of the cerebrovascular system. If our hypothesis of improved perfusion and cerebrovascular reactivity following a 12-week aerobic exercise intervention is supported, it would add critically important insights into the potential of exercise to improve brain health in aging and could inform exercise prescription for older adults at risk for neurodegenerative disease brought on by cerebrovascular dysfunction. TRIAL REGISTRATION: ClinicalTrials.gov NCT05932069; https://clinicaltrials.gov/study/NCT05932069. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58316.

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)0.020
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.051
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.019
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0150.006
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0510.008

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 head0.077
GPT teacher head0.475
Teacher spread0.399 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations3
Published2024
Admission routes1
Has abstractyes

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