Prospective evaluation and follow-up of nutritional status of children hospitalized in secondary-care level hospitals: a multicentre study
Bibliographic record
Abstract
Although disease-associated undernutrition is still an important problem in hospitalized children that is often underrecognized, follow-up studies evaluating post-discharge nutritional status of children with undernutrition are lacking. The aim of this multicentre prospective observational cohort study was to assess the rate of acute undernutrition (AU) and/or having a high nutritional risk (HR) in children on admission to seven secondary-care level Dutch hospitals and to evaluate the nutritional course of AU/HR group during admission and post-discharge. STRONG kids was used to indicate HR, and AU was based on anthropometric data ( z-score < −2 for weight-for-age (WFA; <1 year) or weight-for-height (WFH; ≥1 year)). In total, 1985 patients were screened for AU/HR over a 12-month period. On admission, AU was present in 9.9% of screened children and 6.2% were classified as HR; 266 (13.4%) children comprised the AU/HR group (median age 2.4 years, median length of stay 3 days). In this group, further nutritional assessment by a dietitian during hospitalization occurred in 44% of children, whereas 38% received nutritional support. At follow-up 4–8 weeks post-discharge, 101 out of orginal 266 children in the AU/HR group (38%) had available paired anthropometric measurements to re-assess nutrition status. Significant improvement of WFA/WFH compared to admission (−2.48 vs. −1.51 SD; p < 0.001) and significant decline in AU rate from admission to outpatient follow-up (69.3% vs. 35.6%; p < 0.001) were shown. In conclusion, post-discharge nutritional status of children with undernutrition and/or high nutritional risk on admission to secondary-care level pediatric wards showed significant improvement, but about one-third remained undernourished. Findings warrant the need for a tailored post-discharge nutritional follow-up.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".