0305 Degraded Fractal Activity Regulation and Incident Parkinsonism in Community-Based Older Adults
Bibliographic record
Abstract
Healthy physiological systems exhibit fractal regulation, generating similar fluctuation patterns in physiological outputs across different time scales from seconds to hours. Evidence indicates a mechanistic link between fractal regulation and sleep/circadian control, and both degraded with aging and in diseases. It is accepted that sleep and circadian disturbances are common non-motor symptoms of Parkinson’s disease (PD). We tested whether degraded fractal regulation is associated with incident Parkinsonism. We examined 810 older adults (620 females; age: 80.4±7.2 [SD], range 59.4-98.9) in the Rush Memory and Aging Project who were free from any parkinsonian signs at baseline and had undergone annual motor tests for assessment of 4 parkinsonian signs (i.e., bradykinesia, gait, rigidity, and tremor) for up to 13 years. Parkinsonism was rendered if ≥2 parkinsonian signs presented. Motor activity was monitored on the wrist continuously for up to 10 days at baseline. Detrended fluctuation analysis was performed to obtain a metric α that quantifies fractal temporal correlations of motor activity at time scales ~0.1-1.5h. A Cox proportional hazards model was performed to examine the association of α with incident Parkinsonism. Parkinsonism was observed in 332 subjects (~41%) after 3.9±2.8 [SD] years on average from baseline. Older age (hazard ratio [HR]=1.07, p<0.0001) and less education (HR=1.07, p=0.002) but not sex (p=0.6) were associated with a higher risk of Parkinsonism. After controlled for age, sex, and education, 1-SD decrease in α (0.06) was also associated with increased risk for Parkinsonism with an HR of 1.22 (95% CI: 1.09-1.37, p=0.001). The effect is equivalent to that of being ~2.9 years older. The association remained after further adjusting for actigraphy-derived sleep and/or circadian metrics (i.e., sleep fragmentation and interdaily stability). Degraded fractal regulation was associated with increased PD risk. Even though previous studies have well documented the mechanistic link between fractal regulation and sleep/circadian control, the effect of fractal degradation on PD risk appears to be independent from sleep/circadian control. This work was supported by NIH grants R01AG048108, RF1AG059867, R01AG017917, and R01NS078009.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".