Greater Sleep Fragmentation Is Associated With Less Physical Activity in Adults With Cystic Fibrosis
Bibliographic record
Abstract
BACKGROUND: Sleep quality in people with cystic fibrosis (CF) is known to be poor, whereas participating in regular physical activity is associated with less decline in lung function (forced expiratory volume in 1 sec [FEV1]). The relationship between sleep quality and physical activity in people with CF is unknown. METHODS: Secondary analysis of sleep and activity data collected via actigraphy. Adults with CF in stable health, participating in a study of physical activity (including assessment of exercise capacity), completed 7 d of activity and sleep assessment (SenseWear Armband [SWA]; BodyMedia). Sleep characteristics were derived from accelerometer positional data and registration of sleep state by the SWA, determined by energy expenditure. RESULTS: Sleep and activity data were available for 47 participants [n = 28 male; mean ± standard deviation age = 29 ± 8 yr; median (IQR) FEV1 = 60 (50, 82) % predicted]. More fragmented sleep was associated with poorer exercise capacity (rs = -0.303, P = .04), less time spent in moderate-vigorous physical activity (rs = -0.337, P = .020), and poorer FEV1 (rs = -0.344, P = .018). Regression analysis showed that less fragmented sleep was an independent predictor of more total daily activity time (β = -1.0, standard error [SE] of β = .4, P = .02) and trended toward significance for more moderate-vigorous physical activity (β = -.3, SE of β = -.26, P = .08). Greater total sleep time and sleep efficiency were related to better exercise capacity and lung function (P < .05). CONCLUSION: This secondary analysis demonstrated a modest relationship between sleep parameters and physical activity and exercise capacity in adults with CF. Future studies of interventions to promote physical activity participation in this group should consider the relationship between sleep and activity performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".