Sleep quality in people with chronic pain undergoing hemodialysis
Bibliographic record
Abstract
Objective: to evaluate sleep quality in people with chronic pain undergoing hemodialysis. Methods: observational, prospective, and cross-sectional study carried out in two hemodialysis clinics. The sample was formed by 76 people with chronic kidney disease and chronic pain who were undergoing hemodialysis. We used a sociodemopgrahic and clinical form, the visual analogue scale for pain, the McGill questionnaire, and the Pittsburgh Sleep Quality Index. Results were analyzed using descriptive and inferential statistics and correlation tests. Results: most participants had very poor sleep quality. There was a correlation between sleep quality and the visual analogue scale for pain (p=0.027). There was a negative correlation between McGill pain scale descriptors and sleep quality (p=0.033). Conclusion: the sleep quality levels of most participants suffered alterations and were classified as poor or very poor. Contributions to practice: this study provides data on correlations associated with the sleep quality of patients with chronic pain undergoing hemodialysis. It also gives support for nursing teams to develop interventions to improve the sleep quality of these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 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".