Disease associated malnutrition in pediatrics – what is new?
Bibliographic record
Abstract
PURPOSE OF REVIEW: Disease associated malnutrition (DAM) remains an important concern in the care of hospitalized children and children with a chronic disease. This review focused on pediatric literature published since 2023 on the prevalence, assessment and treatment of DAM in different settings. RECENT FINDINGS: The prevalence of DAM depends on a variety of factors. Studies focused on the relationship between different assessment methods of DAM and sarcopenia in hospitalized children and children with an underlying disease and clinical outcomes. Several papers focused on exploring the interplay between nutritional management and the evolving metabolic phases of critically ill children. Some studies explored feeding intolerance and barriers to administering enteral nutrition, micronutrient assessment and whether continuous versus intermittent feeding was superior in pediatric intensive care. SUMMARY: In hospitalized children and chronically ill children, nutritional assessment and assessment of frailty and/or sarcopenia is best done using a comprehensive approach integrating anthropometrics, nutrition focused history and physical examination. Adequate nutritional support for critically ill children is challenging and needs to be tailored to the specific phases of critical illness. Intermittent feeding may offer potential advantages in inducing ketosis and circadian rhythm alignment but requires careful management to prevent nutritional deficits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".