Periodic Leg Movements Predict Total Sleep Time in Persons with Cognitive Impairment and Sleep Disturbance
Bibliographic record
Abstract
STUDY OBJECTIVE: To determine if periodic leg movements predict total sleep time at night in elders with cognitive impairment and sleep disturbance. DESIGN: Descriptive cross-sectional secondary analysis using data from an observational study and baseline data from a randomized, controlled clinical trial. SETTINGS: Private homes, nursing homes, and assisted living facilities. PARTICIPANTS: One hundred and two persons with a mean age of 81.8 years, cognitive impairment, and sleep disturbance. INTERVENTION: N/A. MEASUREMENTS AND RESULTS: We measured sleep variables using 1 night of attended polysomnography in each participant's usual sleep setting. We assessed 10 characteristics associated with sleep disturbance (periodic leg movement index, time in bed, apnea-hypopnea index, oxygen saturation nadir, age, sex, living arrangement, cognitive status, painful conditions, and depression) with multiple linear regression analyses to determine the predictors of total sleep time. Of the 102 participants, 56.9% were men, and 64.7% lived in nursing homes or assisted living facilities. Their mean Mini-Mental State Examination score was 17.3. In addition, 21.6% had 1 or more painful conditions, and 45.1% were diagnosed with depression. Participants' mean periodic leg movement index was 17.3 with 34 (33.3%) having a periodic leg movement index greater than 15. Time in bed at night exceeded 8 hours, yet participants averaged only 5.5 hours of sleep. They had a mean apnea-hypopnea index of 18.3, with a mean oxygen saturation nadir of 86.4%. Periodic leg movement index, time in bed, and age explained 43.6% of the variance in total sleep time. CONCLUSIONS: Frequent periodic leg movements, less time in bed, and older age are associated with less sleep at night in this population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".