Improving nutrition in pediatric heart failure
Bibliographic record
Abstract
Heart failure occurs in 0.9 to 3 per 100,000 children, and can be the result of either structural heart disease, genetic, or acquired cardiomyopathies. Malnutrition remains a major concern in this population, and results from the complex interplay between decreased dietary intake, decreased absorption, and an altered metabolic state. Assessing nutritional status remains a challenge, with conventional anthropometric measures often being unsuitable. To this end, the Subjective Global Nutrition Assessment has been developed and this, in combination with indirect calorimetry, can be used to give a better estimate of a child's nutritional status and caloric needs. Determining the best way to meet these needs requires a multidisciplinary team approach, determining both the most appropriate feeding route and most appropriate type of feed. This is particularly important with the trend toward blended feeds, as these feeds must not only meet protein-energy requirements but must also not exceed daily sodium requirements or fluid restrictions. To further optimize heart failure through nutrition, the use of micronutrient supplementation has evolved. In particular, optimizing vitamin D, selenium, and iron has been shown to be beneficial from a heart failure management perspective. As nutrition plays such a vital role in the medical optimization of pediatric patients with heart failure, it is important to acknowledge the impact this can have on the child and the family unit.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".