Effect of nutritional support on nutritional status and inflammation in malnourished patients undergoing maintenance hemodialysis
Bibliographic record
Abstract
INTRODUCTION: Protein energy wasting/malnutrition is a strong predictor of morbidity and mortality in patients on maintenance hemodialysis (MHD). We aimed to compare the effects of oral and/or intradialytic parenteral nutrition (IDPN) support on nutritional and inflammatory parameters in malnourished patients with MHD. METHODS: This is an observational study of 56 malnourished patients on MHD. We offered combined oral nutritional support (ONS) and IDPN for 12 months to all patients. Depending on patient choices for treatment, they were classified into four groups: group 1 (ONS only), group 2 (IDPN only), group 3 (both ONS and IDPN), and group 4 (patients who refused artificial nutrition support and only followed dietary advice). Normalized protein catabolic rate (nPCR), malnutrition inflammation score (MIS), and body composition (fat mass [FM], muscle mass [MM]) were assessed monthly. FINDINGS: The mean serum albumin levels of groups 2 and 3 significantly increased with the intervention, whereas that of group 4 significantly decreased. The mean nPCR levels of groups 2 and 3 significantly increased. Group 3 had the most significant positive change in serum albumin and nPCR levels. Mean serum C-reactive protein (CRP) levels of groups 1, 2, and 3 decreased, whereas those of group 4 increased. A ∆ in CRP was only identified in group 3. The MIS of groups 1, 2, and 3 significantly decreased whereas that of group 4 significantly increased. The ∆% in FM was 1.1, 1.9, 9.1, and -2.9 for groups 1, 2, 3, and 4, respectively, and that in MM was -0.6, 4.4, 6.9, and -7.9 for groups 1, 2, 3, and 4, respectively. DISCUSSION: Compared to monotherapy or nutritional counseling, the choice of ONS plus IDPN is associated with improved nutritional status and decreased inflammation in malnourished patients on MHD. Nonetheless, interventional studies must be conducted to confirm these observations.
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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) | 0.000 | 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".