In-center Nocturnal Hemodialysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Some patients are not optimally treated by conventional in-center hemodialysis (HD) and are unable to perform home HD. We examined the effect of in-center thrice-weekly nocturnal HD (INHD) on patient outcomes. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Patients who were not optimally treated on conventional HD were offered INHD. Thirty-nine patients' laboratory data and medication use were analyzed for the 12 mo before and after conversion to INHD until September 1, 2007. Quality of life on conventional HD and INHD was compared. RESULTS: After conversion to INHD, median values for phosphorus decreased from 5.9 to 3.7 mg/dl (P < 0.01), alkaline phosphatase level increased from 84 to 161 U/L (P < 0.01), and percentage reduction in urea increased from 74 to 89% (P < 0.01). The mean number of antihypertensive drugs prescribed declined from 2.0 to 1.5 (P < 0.05) during the course of INHD, and the mean daily dosage of phosphate binders declined from 6.2 to 4.9 at study end (P < 0.05). There was a significant reduction in erythropoietin-stimulating agent use of 1992 U/wk (P < 0.01). There was no significant change in median hemoglobin, iron saturation, corrected calcium, or parathyroid hormone levels. Overall, quality of life, sleep, intradialytic cramps, appetite, and energy level all improved significantly on INHD. CONCLUSIONS: INHD offers an effective form of HD for long-term dialysis patients who are unable to perform home HD.
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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 | 0.000 | 0.000 |
| 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) | 0.008 | 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".