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Record W4390201511 · doi:10.1002/alz.077495

Reshaping the path of vascular cognitive impairment with progressive resistance training: A 12‐Month Randomized Trial

2023· article· en· W4390201511 on OpenAlexaffabout
Ryan S. Falck, Roger Tam, Elizabeth Dao, Cindy K. Barha, Ging‐Yuek Robin Hsiung, Rachel A. Crockett, Walid Ahmed Alkeridy, John R. Best, Sofia Grant, Thalia S. Field, Nárlon Cássio Boa Sorte Silva, Lisanne F. ten Brinke, Teresa Liu‐Ambrose

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsSimon Fraser UniversityCenter for Diagnosis and Research on Alzheimer's DiseaseLibin Cardiovascular Institute of AlbertaUniversity of British ColumbiaUniversity of CalgaryVancouver Coastal Health Research InstituteVancouver Coastal Health
Fundersnot available
KeywordsRandomized controlled trialHyperintensityDementiaMedicineCognitive declinePhysical therapyCognitionMontreal Cognitive AssessmentCognitive trainingVascular dementiaPhysical medicine and rehabilitationPsychologyInternal medicineDiseasePsychiatryMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Abstract Background Subcortical ischaemic vascular cognitive impairment (SIVCI) is the most common form of vascular cognitive impairment. Importantly, SIVCI is considered the most treatable form of cognitive impairment, due to its modifiable risk factors such as hypertension and diabetes mellitus. Exercise training is a promising intervention to delay the progression of SIVCI, as it actively targets these cardiometabolic risk factors. Despite the demonstrated benefits of resistance training on cognitive function and emerging evidence suggesting resistance training may reduce the progression of white matter hyperintensities, research on SIVCI has predominantly focused on the use of aerobic exercise. Thus, we examined the efficacy of a 12‐month, twice‐weekly progressive resistance training (RT) program on cognitive function in older adults with SIVCI. Method We conducted a 12‐month single‐blinded, randomized controlled trial with 91 adults with SIVCI who were randomly allocated to: 1) progressive RT; or 2) balance and tone exercises (BAT; control). Study eligibility included: 1) age 55 years and older; 2) neuroimaging evidence of cerebral small vessel disease at study entry; 3) mild cognitive impairment, as indicated by Montreal Cognitive Assessment scores < 26/30; and 4) the absence of dementia. Measurements occurred at baseline, 6 months, and 12 months. The primary outcome for cognitive function was the Alzheimer’s Disease Assessment Scale‐Cognitive‐Plus (ADAS‐Cog 13 with additional cognitive tests). Gait speed over 4 meters was also assessed as impaired mobility is common among those with SIVCI. Result Forty‐five participants were randomized to the RT group and 46 to the BAT group. Mean baseline age was 74.6 years (SD = 5.7 years), 66% of participants were female, and the median Fazekas score was 1. After adjusting for baseline, participants in the RT group had significantly better ADAS‐Cog Plus performance at 12 months vs. BAT (estimated mean difference [RT – BAT]:‐0.20; 95% CI:[‐0.39, ‐0.01]; p = 0.039). In addition, participants in RT had significantly faster gait speed at 12 months vs. BAT (estimated mean difference: ‐0.08 m/s; 95% CI: [‐0.16, 0.00]; p = 0.047). Conclusion The prevalence and burden of SIVCI will only increase due to the world’s aging population. Our results suggest progressive resistance training should be considered in the management and treatment of individuals with SIVCI.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.027
GPT teacher head0.273
Teacher spread0.247 · 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
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 routes2
Has abstractyes

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