Relative validity and reproducibility of food frequency questionnaire for individuals on hemodialysis (NUGE‐HD study)
Bibliographic record
Abstract
INTRODUCTION: Adequate assessment of food intake is essential to establish the magnitude and direction of the relationship of food, nutrients, and bioactive compounds with clinical outcomes of individuals in hemodialysis. We evaluated the relative validity and reproducibility of a specific food frequency questionnaire for individuals on hemodialysis (FFQ-HD). METHODS: Eighty-two participants (57.3% male, 57.5 ± 14.4 years) from the open cohort Nutrition and Genetics in Hemodialysis Outcomes participated in this study. The relative validity of the FFQ-HD was assessed using the mean of two 24-h food recall (24hR) adjusted for within-subject variability as a reference method. We also performed Pearson correlations, and agreement between tertile, kappa statistics, and Bland-Altman scatter plots were validated. Reproducibility was assessed after 1 year using intraclass correlation coefficient (ICC). FINDINGS: Daily energy intake was not different between FFQ-HD and 24hR (mean difference of 50.1 kcal). Intake of protein, linolenic acid, fiber, phosphorus, potassium, sodium, calcium, and sugar showed a moderate correlation (r between 0.4 and 0.5) among instruments, while mean correlation coefficient was r = 0.38 to food group intake. Bland-Altman plots showed good agreement for micronutrients, phosphorus, sodium, and potassium and for the groups "flour, bread, and pasta" and "processed, canned meat, salts, and seasonings". The reproducibility of FFQ-HD for nutrients and food groups was satisfactory, reaching a maximum ICC of 0.72 and 0.59, respectively. DISCUSSION: The FFQ-HD showed moderate validity and reproducibility for calories, nutrients, and food groups of clinical and nutritional interest for HD subjects so that it can be a useful tool in epidemiological studies in this population.
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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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".