Stability of nutritional parameters during a 5‐year follow‐up in patients treated with sequential long‐hour hemodialysis
Bibliographic record
Abstract
Progressive nutritional impairment has been recently reported during conventional hemodialysis (HD) treatment. We studied the nutritional parameters during a 5-year follow-up in HD patients. Thirty-three patients (15F/18M; 65 years old at the study start) filled out a 3-day food questionnaire once a year between 1995 and 1999 (study group). Twenty patients, who did not fill out the food records during this period served as a control group (control group). The food record was run by the renal dietician using a dedicated software, providing daily energy and protein intakes (DEI and DPI). Serum albumin, normalized protein equivalent of nitrogen appearance (nPNA), and postdialysis body weight (BW) at the time of food record were collected in the study group and from the patient chart in the control group. The energy intake in the study group and the protein intake in both groups were close to the recommended intakes in ESRD patients. Protein intake assessed from food questionnaire or from urea kinetics were not statistically different. Using ANOVA for repeated measures, no difference along the 5 years was found for daily energy intake, daily protein intake, nPNA, and BW in the study group. The BW and nPNA remained stable in the control group. Hence, this study does not confirm the progressive nutritional impairment reported in the HEMO study, whereas the patients' age and vintage are largely higher in the present study. The role of a large dialysis dose in maintaining nutritional status in HD patients is discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".