Evolución de la función renal en pacientes con enfermedad renal crónica con dieta restringida en proteínas suplementada con una mezcla de aminoácidos y cetoanálogos
Bibliographic record
Abstract
INTRODUCTION: chronic kidney disease (CKD) is a public health problem. Low-protein diets supplemented with ketoacids and essential aminoacids have proved effective at different CKD stages. AIM: to assess the progression of renal failure in adult patients with CKD stages 3b and 4 receiving a protein-controlled diet supplemented with aminoacids and ketoanalogues. METHODS: retrospective, descriptive intervention study. The nutritional intervention consisted of a protein/calorie intake of 0.4-0.6 g/kg/day and 30-35 kcal/kg/day plus a tablet of ketoanalogues (Ketosteril®)/5 kg weight. We assessed nutritional condition, glomerular filtration (GF) and creatinine, urea and albumin levels at 0, 3, 6, 9 and 12 months. SPSS version 18 was used for data statistical analysis. RESULTS: thirty-three patients were studied (67% male; mean age 59.7 years, r: 24-87). Protein/calorie intake was 0.55 ± 0.20 g/kg/day and 34 ± 4.51 kcal/kg/day. Ketosteril® intake was 11.87 tablets/day (r: 9-14). Initial GF was 24.97 ± 6.64 ml/min/1.73 m2, showing a significant increase between three and 12 months (25.51 ± 8.57 and 29.26 ± 10.33 ml/min/1.73 m2; p = 0.006). Urea nitrogen decreased significantly at six months compared with the initial level (p < 0.005). Body mass index did not change significantly (initial, 26. 63 ± 4.08 kg/m2; after a year, 26.78 ± 3.98 kg/m2). Initial and final albumin levels were 3.53 ± 0.64 g/l and 4.00 ± 0.53 g/l, respectively (p = 0.79). CONCLUSION: a low-protein diet supplemented with ketoanalogues administered to patients with CKD stages 3b and 4 preserved nutritional condition and mineral balance, improved GF significantly and decreased urea levels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".