Association Between Work Status and Quality of Life in End‐Stage Renal Disease Patients During the First Year of Hemodialysis
Bibliographic record
Abstract
INTRODUCTION: End-stage renal disease patients have impaired health-related quality of life as compared to the general population due to the combined effects of the disease and hemodialysis (HD) therapy. As a result, poor quality of life increases their risk of mortality and hospitalization and affects their general well-being. While existing rehabilitation programs aim to improve physical activity in HD patients, the link between work status, particularly within the first year of treatment, and their quality of life remains unclear. OBJECTIVES: This study aimed to compare the quality of life of working and nonworking end-stage renal disease patients during their first year of HD. MATERIALS AND METHODS: The comparative cross-sectional study involved 120 patients (60 working, 60 non- working) with end-stage renal disease at the hemodialysis (HD) centers during their first year of HD. Patients were administered the SF-36 survey to determine their physical and mental health levels. Statistical analyses, including Mann-Whitney U tests, Spearman's correlation, and multiple regression, were performed using SPSS 22. RESULTS: Employed patients demonstrated significantly higher physical functioning (MR = 82.37, Me = 41.27) and mental health (MR = 74.33, Me = 47.22) scores compared to non-employed (MR = 38,63, Me = 29.07 and MR = 46.67, Me = 38,14, respectively) (p < 0.001). Employment is a significant predictor of high quality of life (B = 11.6 for PF, B = 6.5 for MH). Despite older age and increased prevalence of comorbidities, employed patients demonstrate better quality of life results. CONCLUSION: Employment has a positive effect on the quality of life of patients with chronic renal failure receiving HD, indicating that their regimen may be improved by incorporating work into the treatment program. Employment opportunities for patients with chronic renal failure receiving dialysis should be explored in the future.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".