Sleep disorders and illness intrusiveness in patients on chronic dialysis
Bibliographic record
Abstract
BACKGROUND: The prevalence of sleep problems (insomnia, restless legs syndrome, periodic limb movements in sleep and sleep apnoea) has been shown to be high in patients with end-stage renal disease (ESRD) and might contribute to impaired quality of life in this population. METHODS: In a cross-sectional study using self-administered questionnaires, we examined the prevalence of sleep disorders and assessed their effect on different aspects of health-related quality of life in a sample of Hungarian patients on maintenance dialysis. RESULTS: Our data confirm that sleep problems are frequent in patients with ESRD; 65% of the patients reported symptoms of at least one specific sleep disorder; insomnia was the most common sleep complaint with 49%, the prevalence of sleep apnoea was 32% and the prevalence of restless legs syndrome was 15%. Co-morbidity, assessed by the End-Stage Renal Disease Severity Index, was shown to be an independent predictor of sleep disorders. Patients with sleep disorders reported higher illness intrusiveness and worse self-perceived health than those without sleep problems. The presence of sleep disorders was an independent predictor of illness intrusiveness, an important determinant of health-related quality of life. CONCLUSION: Sleep disorders are important determinants of illness intrusiveness and health-related quality of life in patients with ESRD. Sleep problems may be treated successfully; therefore, more attention should be paid to assessing these problems in this patient 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".