Post-discharge complications and hospital readmissions are associated with nutritional risk and malnutrition status in a cohort of Canadian pediatric patients
Bibliographic record
Abstract
BACKGROUND: This study constitutes a secondary analysis of a prospective cohort aiming to evaluate the potential correlation between nutritional risk and status at admission with the occurrence of post-discharge complications and hospital readmissions in children receiving care at high resource Centres. METHODS: Data was collected from 5 Canadian tertiary pediatric Centers between 2012 and 2016. Nutritional risk and status were evaluated at hospital admission with validated tools (STRONGkids and Subjective Global Nutrition Assessment [SGNA]) and anthropometric measurements. Thirty days after discharge, occurrence of post-discharge complications and hospital readmission were documented. RESULTS: A total of 360 participants were included in the study (median age, 6.1 years; median length of stay, 5 days). Following discharge, 24.1% experienced complications and 19.5% were readmitted to the hospital. The odds of experiencing complications were nearly tripled for participants with a high nutritional risk compared to a low risk (OR = 2.85; 95% CI [1.08-7.54]; P = 0.035) and those whose caregivers reported having a poor compared to a good appetite (OR = 2.96; 95% CI [1.59-5.50]; P < 0.001). According to SGNA, patients identified as malnourished had significantly higher odds of complications (OR, 1.92; 95% CI, 1.15-3.20; P = 0.013) and hospital readmission (OR, 1.95; 95% CI, 1.12-3.39; P = 0.017) than to those well-nourished. CONCLUSIONS: This study showed that complications and readmission post-discharge are common, and these are more likely to occur in malnourished children compared to their well-nourished counterparts. Enhancing nutritional care during admission, at discharge and in the community may be an area for future outcome optimization.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".