FC061DIETARY PATTERNS AND MORTALITY IN ADULTS ON HEMODIALYSIS
Bibliographic record
Abstract
INTRODUCTION: Clinical practice guidelines on dietary intake in patients treated with haemodialysis focus on restricting individual nutrients to avoid electrolyte complications. Evidence for whole dietary patterns and their association with clinical outcomes is of very low certainty due to sparse existing data. We aimed to evaluate the association of data driven dietary patterns with cardiovascular and all-cause mortality among adults treated with hemodialysis. METHODS: In the DIET-HD multinational cohort study, dietary composition of over 200 foods was ascertained using the GA2LEN food frequency questionnaire in 8110 adults treated with haemodialysis. In this analysis, dietary patterns were identified using principal components analysis. Participants received a score for each identified pattern with higher scores indicating closer resemblance of their diet to the identified pattern. The association of dietary pattern scores (as quartiles) with all-cause and cardiovascular mortality was estimated using Cox regression analyses, clustered by country and adjusted for comorbidity, demographic and life style characteristics. Estimates are presented as adjusted hazard ratios (aHR) with 95% confidence intervals (CI), using the lowest quartile score as the reference category. RESULTS: During a median follow up of 2.7 years (18,666 person-years), there were 2087 deaths (958 cardiovascular). Two dietary patterns, “fruit and vegetables-based” and “Western”, were identified by principal components analysis. The main food components of each dietary patient is shown in Figure 1. There was no evidence of an association of increasing concordance with the fruit and vegetable dietary pattern and cardiovascular mortality (aHR 0.94 (CI, 0.76-1.15), 0.83 (0.66-1.06) and 0.91 (0.69-1.21) for ascending score quartiles) or all-cause mortality (0.95 (0.83-1.09), 0.84 (0.71-0.99) and 0.87 (0.72-1.05)). Similarly there was no evidence of an association between a Western dietary pattern in ascending quartiles of dietary concordance and cardiovascular mortality (aHR 1.01 1.10 (0.90-1.35), 1.11 (0.87-1.41) and 1.09 (0.80-1.49) or all-cause mortality (1.01 (0.88-1.16), 1.00 (0.85-1.18) and 1.14 (0.93-1.41)). CONCLUSIONS: There appears to be little or no association between consumption of a fruit and vegetable-based or a Western diet with cardiovascular and all-cause mortality in patients on hemodialysis.
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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 | 0.000 | 0.002 |
| 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) | 0.003 | 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".