Dietary intake, clinical-nutritional status, and homocysteine in hemodialysis subjects: the mediating role of inflammation (NUGE-HD study)
Bibliographic record
Abstract
The aim of the present study was to test the hypothesis that inflammation mediates the associations among food intake, clinical-nutritional status, and plasma homocysteine (Hcys) in hemodialysis (HD) subjects. This was a cross-sectional analysis of data on 129 subjects undergoing HD (58.9% male, 61.8 ± 15.5 years of age) from the cohort Nutrition and Genetics on HD outcomes (NUGE-HD study). Sociodemographic, anthropometric, and metabolic data were collected, and food intake was assessed using a quantitative food frequency questionnaire. Plasma C-reactive protein (CRP) was used as an inflammatory marker. Data were analyzed by structural equation modeling. Regarding the direct effects, complex B vitamin intake was negatively associated with body mass index, and diabetes mellitus was positively associated with CRP. Plasma CRP also showed a negative association with Hcys, and the ratio of saturated and polyunsaturated fatty acids intake showed a positive association with Hcys. Regarding indirect effects, the results showed that the relationship between the presence of diabetes mellitus and Hcys is mediated by plasma CRP. In conclusion, the ratio of saturated and polyunsaturated fatty acids had a direct effect on plasma Hcys, whereas inflammation had a direct and mediating effect on the relationship between Hcys and diabetes mellitus in HD subjects. Novelty In end-stage renal disease, CRP influences plasma Hcys directly and also indirectly through its mediating effect. The quantity and quality of dietary fatty acids influence plasma Hcys concentrations in HD subjects.
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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 | 0.000 | 0.001 |
| 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".