Lower Thalamic Blood Flow Is Associated With Slower Stride Velocity in Older Adults
Bibliographic record
Abstract
Background: Gait deficits are associated with brain atrophy and white matter hyperintensities (WMH) – both markers of underlying cerebral small vessel disease (SVD). Given reduced subcortical cerebral blood flow (CBF) is prevalent in SVD, we tested the hypothesis that regional CBF is positively associated with gait performance among older adults. Methods: Thirty-two older adults (55-80 years) with at least one vascular risk factor were recruited. We assessed gait during 2 consecutive walking sequences using a GAITRite system: 1) at a self-selected pace, and 2) while performing a serial subtraction dual-task challenge. We quantified CBF using pseudo-continuous arterial spin labeling MRI within 4 regions of interest: putamen, pallidum, thalamus, and hippocampus. We investigated associations between gait characteristics and overall CBF adjusting for age, sex, and height in an omnibus approach using multivariate analysis of variance, followed by regression analysis with each individual region. We also conducted further regression analyses to investigate associations between gait characteristics and frontal lobe CBF. Sensitivity analyses examined how the observed associations were modified by WMH, executive function, and depressive symptoms. A change of 10% in the model’s adjusted r2 and effect size was considered as a threshold for confounding. Results: Overall subcortical CBF was not associated with self-paced gait. When examining individual ROI, gait velocity was directly related to thalamic CBF (p = .026), and across all gait variables the largest effect sizes were observed in relation to thalamic CBF. In the dual-task condition, gait variables were not related to CBF in either the omnibus approach or individual multiple regressions. Furthermore, no significant associations were observed between frontal CBF and gait variables in either the self-paced or dual-task condition. Sensitivity analyses which were restricted to examine the association of velocity and thalamic CBF identified a cofounding effect of depressive symptoms which increased the effect size of the CBF-gait association by 12%. Conclusions: Subcortical hypoperfusion, particularly in regions that comprise central input/output tracts to the cortical tissue, may underlie the association between gait deficits and brain aging.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".