Nutritional education for management of osteodystrophy: Impact on serum phosphorus, quality of life, and malnutrition
Bibliographic record
Abstract
Introduction Osteodystrophy management includes dietary phosphorus restriction, which may limit protein intake, exacerbate malnutrition-inflammation syndrome and mortality among hemodialysis patients. Methods A multicenter randomized controlled trial was conducted in Lebanon, to test the hypothesis that intensive nutrition education focused on phosphorus-to-protein balance will improve patient outcomes. Six hemodialysis units were randomly assigned to the trained hospital dietitian (THD) protocol (210 patients). Six others (184 patients) were divided equally according to the patients' dialysis shifts and assigned to Dedicated Dietitian (DD) and Control protocols. Patients in the THD group received nutrition education from hospital dietitians who were trained by the study team on renal dietetics, but had limited time for hemodialysis patients. Patients in the DD group received individualized nutritional education on dietary phosphorus and protein management for 6 months (2-hour/patient/month) from study renal dietitians. Patients in the control group continued receiving routine care from hospital dietitians who had limited time for these patients and were blinded to the study. Serum phosphorus (mmol/L), malnutrition-inflammation score (MIS), health-related quality of life (HRQOL) index and length of hospital stay (LOS) were assessed at T0 (baseline), T1 (postintervention) and T2 (post6 month follow up). Findings Only the DD protocol significantly improved serum phosphorus (T0:1.78 ± 0.5, T1:1.63 ± 0.46, T2:1.69 ± 0.53), 3 domains of the HRQOL and maintained MIS at T1, but this protective effect resolved at T2. The LOS significantly dropped for all groups. Discussion The presence of competent renal dietitians fully dedicated to hemodialysis units was superior over the other protocols in temporarily improving patient outcomes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".