In-center nocturnal hemodialysis improves health-related quality of life for patients with end-stage renal disease
Bibliographic record
Abstract
BACKGROUND: Conventional in-center hemodialysis (HD) is associated with significant symptom burden and reduced health-related quality of life (HRQOL). The HRQOL effects of conversion to in-center nocturnal hemodialysis (INHD) remain unclear, especially amongst those with poor HRQOL. METHODS: Prospective cohort study of HD patients converting to INHD. Linear regression models summarized the mean score at baseline and at 12 months for the cohort. To assess whether patients with low baseline HRQOL derive greater benefit, we compared values before and after by levels of baseline score for each domain (below vs equal to or above the median) using a formal interaction test (t test). RESULTS: 36 patients started INHD, 7 withdrew (5 transplanted, 1 death, 1 moved) and 5 declined follow-up. After 12 months the mental component score (MCS) increased by 7.1 points to a value of 51.0 (95% CI + 1.5 to 10.9, p = 0.01). Amongst patients with baseline scores below the median, improvements were seen in: Symptoms/Problems of Kidney Disease (+ 15.2, 95% CI + 5.5 to + 24.9, p = 0.003), Effects of Kidney Disease (+ 16.9, 95% CI + 2.2 to + 31.7, p = 0.026), Physical Component Score (+ 9.4, 95% CI + 1.69 to + 17.2, p = 0.018), MCS (+ 10.7, 95% CI + 2.4 to + 19.1, p = 0.013). Burden of Kidney Disease domain change was not significant (+ 15.1, 95% CI - 2.1 to + 32.3, p = 0.083). DISCUSSION: INHD is a potential intervention for HD patients who struggle with reduced HRQOL, especially for those who struggle with poor mental health. Medical benefits of reduced pill burden and improved phosphate control occur with transition to INHD.
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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 | 0.000 |
| 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) | 0.001 | 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".