RESISTANCE TRAINING AND COGNITIVE FUNCTION IN VASCULAR COGNITIVE IMPAIRMENT: A 12-MONTH RANDOMIZED TRIAL
Bibliographic record
Abstract
Abstract Background Subcortical ischaemic vascular cognitive impairment (SIVCI) is considered the most treatable form of cognitive impairment, due to its modifiable risk factors such as hypertension and diabetes mellitus. Despite the benefits of resistance training (RT) on cognitive function and cardiometabolic health, no study has examined the effect of RT on cognitive outcomes in SIVCI. Methods A 12-month single-blinded, randomized controlled trial with 91 older adults with SIVCI who were randomized to: 1) 2x/week progressive RT; or 2) 2x/week balance and tone exercises (BAT; control). Study eligibility included: 1) age 55 years and older; 2) neuroimaging evidence of cerebral small vessel disease; 3) mild cognitive impairment; and 4) the absence of dementia. Measurements occurred at baseline, 6, and 12 months. The primary outcome was the Alzheimer’s Disease Assessment Scale-Cognitive-Plus (ADAS-Cog 13 with additional cognitive tests). Sex differences in RT efficacy was explored. Results 45 were allocated to the RT group and 46 to the BAT group. COVD-19 impacted the training of 16 participants (9 RT, 7 BAT). After adjusting for covariates and baseline value, participants in the RT group had significantly better ADAS-Cog Plus performance at 12 months (estimated mean difference [RT – BAT]:-0.18; 95% CI:[-0.35, -0.01]; p=0.047). In the sex-stratified analysis, there was a significant effect of the RT on ADAS-Cog Plus performance (estimated mean difference: -0.25; 95% CI:[-0.47, -0.03]; p= 0.028) for females, but not for males. Conclusion Our results suggest progressive RT should be considered in the management and treatment of individuals with SIVCI, particularly for females.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".