Epidemiology of Interruptions to Nutrition Support in Critically Ill Children in the Pediatric Intensive Care Unit
Bibliographic record
Abstract
BACKGROUND: Nutrition support is often delayed or interrupted. The aim of this study is to identify reasons for and quantify time spent without nutrition in a mixed medical-surgical-cardiac pediatric intensive care unit (PICU). METHODS: Data were prospectively collected to describe the patient cohort (anthropometrics and diagnostic category) and nutrition practices (time to nutrition initiation; frequency, duration, and causes of interruptions; and overall caloric intake). Descriptive statistics were used; comparisons of groups were performed using an independent t test and P < .05 as significance. RESULTS: The mean (standard deviation) time to nutrition initiation was 22.8 (16.6) hours following admission; 35% of patients were initiated after >24 hours. Nutrition was interrupted 1.2 (2.0) times per patient. Time spent without nutrition due to interruptions was 11.6 (23.0) hours, up to 102 hours. Patients spent 42.4% (28.2%) of their median (range) PICU admission of 2.9 days (0.25-39 days) without any form of nutrition. Patients aged 0-6 months had a significantly higher mean number and duration of interruptions (P = .001 and P < .001, respectively) compared with children >6 months. Interruptions due to surgery and planned extubation lasted significantly longer than all other interruptions (P < .001 and P = .001, respectively). Pediatric Risk of Mortality (PRISM) III scores were not correlated with percentage of length of stay spent without nutrition (r = 0.137). CONCLUSIONS: Prolonged time to nutrition initiation and interruptions in delivery caused pediatric patients to spend a high proportion of admission without nutrition support, preventing most from meeting energy requirements. Further research addressing specific patient outcomes is required to define optimal initiation times and appropriate procedural-specific fasting times.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".