Nocturnal Limb Movements Are Correlated with Cerebral White Matter Hyperintensities (P05.001)
Bibliographic record
Abstract
Objective: To explore the association of nocturnal limb movements (LMs) and sleep quality with cerebral white matter hyperintensities (WMH). Background Nocturnal LMs are associated with transient but significant increases in night-time blood pressure and autonomic hyperactivity; emerging evidence suggests a link with vascular disease. While obstructive sleep apnea is linked with WMH, the relationship between nocturnal LMs and WMH remains to be clarified. Design/Methods: Patients evaluated in a tertiary care behavioral neurology clinic were assessed with polysomnography for various sleep problems. Polysomnography was scored according to criteria from the American Academy of Sleep Medicine. WMH were rated using the Age Related White Matter Changes Score (ARWMC) from FLAIR MRI. Polysomnographic (transformed where necessary) and ARWMC data were compared using Pearson correlations. Results: Forty-five participants were assessed (69% male, mean age 64 years) and vascular risk factors were as follows: hypertension (27%), hyperlipidemia (18%) and diabetes (9%). Prior cerebrovascular disease (7%), obstructive sleep apnea (49%) and restless legs syndrome (33%) were also present. The mean ARWMC score was 3.84 (range 0-25, standard deviation 4.73). When controlling for hypertension, the total ARWMC score was correlated with total LMs per hour of sleep (r=0.66, p=0.01). There were no differences in the ARWMC score between hemispheres, but more LMs were noted on the left side (66.3 vs. 24.1, p Conclusions: LM counts strongly correlated with the presence of WMH. In addition, sleep efficiency was negatively correlated with WMH. In keeping with developing evidence, our findings suggest that nocturnal LMs associated with poor quality sleep may contribute to episodes of nocturnal hypertension, which have been implicated in the development of WMH, even after controlling for the presence of daytime hypertension. Supported by: Dr. Mark Boulos is supported by a Focus on Stroke Research Fellowship, which is funded by the Canadian Institutes of Health Research, the Heart and Stroke Foundation of Canada, and the Canadian Stroke Network. Disclosure: Dr. Boulos has nothing to disclose. Dr. Pettersen has nothing to disclose. Dr. Jewell has nothing to disclose. Dr. Black has received personal compensation for activities with Novartis Pharmaceuticals, Pfizer, GlaxoSmithKline, Roche Pharmaceuticals, and Bristol-Myers Squibb. Dr. Black has received research support from Novartis Pharmaceuticals, Pfizer, Roche, and GlaxoSmithKline. Dr. Murray has received personal compensation for activities with Pfizer and Valeant as a consultant.
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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) | 0.006 | 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".