Systemic Inflammation Increases Energy Expenditure Following Pediatric Cardiopulmonary Bypass
Bibliographic record
Abstract
OBJECTIVES: To examine the association between cardiopulmonary bypass-related systemic inflammation and resting energy expenditure in pediatric subjects following cardiac surgery. DESIGN: Single-center, prospective cohort study. SETTING: Pediatric cardiac critical care unit in Toronto, Canada. PATIENTS: Children with congenital heart disease undergoing cardiopulmonary bypass surgery. INTERVENTIONS: Resting energy expenditure was determined by indirect calorimetry and the modified Weir equation, using VO2 and VCO2 measured by in-line respiratory mass spectrometry. Measurements were taken at baseline and 6-hour intervals from separation from cardiopulmonary bypass for a maximum of 72 hours. Plasma interleukin-6, glucose delivery, feeding status, and cardiac output (calculated by Fick equation) were monitored at each resting energy expenditure measurement. MEASUREMENTS AND MAIN RESULTS: We studied 111 subjects at a median (interquartile range) age of 5.3 months (0.8-10.5 mo), weighing 5.7 kg (3.9-8.1 kg), of whom 88% underwent biventricular repair. Resting energy expenditure decreased from 51 kcal/kg/d to 45 kcal/kg/d during the study period. Resting energy expenditure was positively associated with increased plasma interleukin-6 (estimate variable, 1.76; p = 0.001) and inversely associated with preoperative methylprednisolone use (estimate variable, -6.7; p = 0.003) even after accounting for other predictors. Increase in cardiac output was also associated (estimate variable, 13.7; p < 0.0001) with higher resting energy expenditure. CONCLUSIONS: Resting energy expenditure ranges between 40 and 60 kcal/kg/d and decreases progressively in children following cardiopulmonary bypass surgery. It is directly associated with increased inflammation and higher cardiac output and inversely associated with anti-inflammatory strategies. Further studies are required to predict the appropriate caloric delivery in this cohort.
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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 | 0.001 | 0.005 |
| 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".