Effect of Long Nocturnal Dialysis on Nutritional Status and Blood Pressure Control
Bibliographic record
Abstract
Objective: Nutritional status is an important predictor of outcome in dialysis patients. Long nocturnal dialysis (LND) improves clearances, and potentially can have a beneficial impact on nutritional status and on blood pressure control. Methods: Retrospective analysis of a prospectively collected database of 12 patients in a LND program. Patients were dialysed 3*/week during 8 hours, at a Qb of 175–200 ml/min and a Qd of 500 ml/min. Pre-dialysis serum albumin (nephelometric), ideal body weight, systolic blood pressure and residual GFR were measured just before start of LND, and after 1 year. Results: Mean Kt/v for urea over the 1 year period was 1.9 ± 0.29/session. Serum albumin increased from 3.83 ± 0.18 to 4.12 ± 0.28 mg/dl (paired T-test : p = 0.007). Ideal body weight increased nonsignificantly from 75.08 ± 15.35 to 78.07 ± 13.49 kg (paired T-test, p = 0.39). Systolic blood pressure decreased from 146.3 ± 21.7 to 132.8 ± 17.3mmHg (paired T-test, p = 0.06) Discussion: Malnutrition is an important predictor of outcome in dialysis patients. Several studies have pointed that an intensification of dialysis adequacy can lead to an enhanced nutritional status. The use of daily dialysis or of nocturnal dialysis can substantially improve delivered Kt/V, as is shown in our patient group. There was a concommitant rise in pre-dialysis serum albumin concentration in all patients. There was also tendency for an increase in total body weight, although this did not reach statistical significance, and was also not present in all patients. This might just be a false impression as the improvement of the pre-dialysis blood pressure might indicate that excess fluid was gradually removed, with an increase in lean body mass and a resulting stable total body weight. In conclusion, LND is well-tolerated, and results in an improvement of serum albumin and pre-dialysis systolic blood pressure.
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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 | 0.004 |
| 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".