Disrupted Rest-Activity Rhythms and Cerebral Small Vessel Disease Pathology in Older Adults
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The pathogenesis of cerebral small vessel disease remains incompletely understood. The relationship between circadian rhythm disturbances and histopathologic measures of cerebral small vessel disease has not been studied. We hypothesized that disrupted circadian rest-activity rhythms would be associated with a higher burden of cerebral small vessel disease pathology. METHODS: We studied 561 community-dwelling older adults (mean age at death, 91.2, 27.4% male) from the Rush Memory and Aging Project. We used actigraphy to quantify several measures of 24-hour rest-activity rhythmicity, including interdaily stability, intradaily variability, and amplitude, and used ordinal logistic regression models to relate these measures to the severity of cerebral arteriolosclerosis, atherosclerosis, macroinfarcts, and microinfarcts, assessed at autopsy. RESULTS: Lower interdaily stability was associated with a higher burden of arteriolosclerosis, higher intradaily variability was associated with a higher burden of atherosclerosis and subcortical infarcts, and lower amplitude was associated with a higher burden of arteriosclerosis, atherosclerosis and subcortical macroinfarcts. Moreover, the associations between interdaily stability and arteriolosclerosis and intradaily variability and subcortical infarcts were independent of cardiovascular risk factors, sleep fragmentation, and medical comorbidities. CONCLUSIONS: Disrupted rest-activity rhythms are associated with a greater burden of cerebral small vessel disease in older adults.
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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 | 0.001 |
| 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) | 0.001 | 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".