Correlation between physical functioning and sleep disturbances in hemodialysis patients
Bibliographic record
Abstract
The study set out to investigate the relationship between physical functioning, inflammatory status, and sleep disturbance in a chronic hemodialysis (HD) population. Forty-six maintenance HD patients from the McGill University Health Centre were enrolled in this study between October 2005 and 2006. The well-validated Human Activity Profile (HAP) questionnaire and the RAND 36-item survey were used to assess physical functioning. Subjects were given the Pittsburgh Sleep Quality Index (PSQI) survey to evaluate the degree of sleep disturbance. Inflammatory status was assessed with the average value of serial C-reactive protein (CRP) levels for each patient, over a period of 12 months before their enrollment in the study. A multivariate logistic regression model was created for these analyses to control for potential confounders, including dialysis adequacy, inflammation, and hemoglobin. Seventy-six percent of the study population had poor sleep as per the Pittsburgh Sleep Quality Index (PSQI score > or = 5). In addition, 65% of subjects had high CRP values (>5 mg/L). On univariate analysis, both a CRP >5 mg/L and a lower adjusted activity score (AAS) on the HAP were significantly associated with poor sleep (PSQI score > or = 5). Multivariate logistic analysis demonstrated that the AAS remained significantly associated with poor sleep, with a 6% decrease in the odds of poor sleep for each score increase in the AAS of the HAP. Poor physical functioning in chronic HD patients, as measured by the HAP, is associated with sleep disturbance, after controlling for inflammation and dialysis adequacy.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".