The impact of education and cooking methods on serum phosphate levels in patients on hemodialysis: 1‐year study
Bibliographic record
Abstract
INTRODUCTION: Control of serum phosphate is important for patients on hemodialysis. The aim of the study was to determine if education based on phosphorus-reducing techniques in food preparation and thermal processing, and accordingly prepared and applied diets, will lead to better outcomes than a standard education program to improve phosphate control in patients on hemodialysis. METHODS: Forty-seven patients on hemodialysis were divided between an intervention and a control group. All subjects received training about nutrition for hemodialysis patients by trained dietitian. In addition, subjects in the intervention group received additional training in phosphorus-reducing techniques in food preparation and received two hospital meals prepared using suggested cooking methods to reduce the phosphate content of food during dialysis treatment. Serum phosphate, serum albumin, and anthropometric parameters were measured, while nPCR was calculated, at the baseline and during the 1-year study. FINDINGS: No differences in serum phosphate levels were observed between intervention (1.68 mmol/L [1.48-2.03]) and control group (1.88 mmol/L [1.57-2.2]) at baseline (P = 0.130). Although not statistically significant between groups the mean reduction was more apparent in the intervention group (-0.3 mmol/L (-0.4 to 0.1) vs. -0.2 (-0.5 to 0.1)), and lead to significantly reduction of phosphate binder therapy. During the study, the nPCR and anthropometric status of the patients did not change significantly. DISCUSSION: Providing additional education to hemodialysis patients on the specific cooking methods and accordingly prepared meals may decrease serum phosphate levels without significantly affecting nutritional status which may be useful in helping to prevent and treat hyperphosphatemia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".