Prevalence of malnutrition at the time of admission among patients admitted to a Canadian tertiary-care paediatric hospital
Bibliographic record
Abstract
BACKGROUND: Malnutrition among hospitalized children is known to negatively influence their response to therapy and to prolong their admission. It also has short- and long-term consequences for growth, development and well-being. It is commonly regarded as a condition affecting children in low-income countries; however, malnutrition has been found to be variably prevalent among hospitalized children in higher-income countries. At the time the present study was conducted, it had been >30 years since the nutritional status of Canadian hospitalized children was last published. OBJECTIVES: To determine and communicate the prevalence of malnutrition among children in a Canadian tertiary-care paediatric hospital at the time of their admission. METHODS: In the present cross-sectional study, anthropometric measures were obtained from 322 children admitted to The Hospital for Sick Children in Toronto, Ontario. Nutritional indexes (BMI for age, weight for age, weight for length/height and length/height for age) were generated from anthropometric measures using the WHO igrowup software, and summarized according to WHO definitions. RESULTS: The overall prevalence of malnutrition using BMI for age was 39.6% (95% CI 33% to 46%), of which 8.8% and 30.8% of participants were under- and overnourished, respectively. Furthermore, 6.9% (95% CI 3% to 13%) were determined to be acutely malnourished (weight for length/height <-2 SD) and 13.4% (95% CI 10% to 18%) chronically malnourished (length/height for age <-2 SD). CONCLUSION: The high prevalence of overall malnutrition observed among study participants suggests that initial screening using simple anthropometric measures should be conducted on hospital admission so that patients can receive appropriate nutrition-specific care.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".