Hyperglycemia after pediatric cardiac surgery: Impact of age and residual lesions*
Bibliographic record
Abstract
OBJECTIVE: We evaluated the effect of patient age and significant residual cardiac lesions on the association between hyperglycemia and adverse outcomes in children after cardiac surgery. The incidence, severity, and duration of hyperglycemia in this patient population and perioperative factors predisposing to hyperglycemia were also delineated. DESIGN: Retrospective, observational cohort study. SETTING: Eighteen-bed pediatric cardiac critical care unit. PATIENTS: Seven hundred seventy-two children undergoing cardiac surgery with cardiopulmonary bypass during 2006 and 2007. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Postoperative glucose levels were reviewed in all children who underwent cardiac surgery with cardiopulmonary bypass at our institution during 2006 and 2007 who met all inclusion criteria and none of the exclusion criteria (n = 772). The composite morbidity-mortality outcome included hospital death, cardiac arrest, renal/hepatic failure, lactic acidosis, extracorporeal membrane oxygenation use, or infection. Hyperglycemia occurred in 90% of patients and resolved within 72 hrs in most without exogenous insulin. Preoperative factors, including prostaglandins, mechanical ventilation, and cyanosis, were significantly associated with increased odds of significant hyperglycemia (>180 mg/dL for >12 hrs or any level >270 mg/dL) as were increased surgical complexity and perioperative steroid administration. Thirty-one percent of the entire cohort reached the composite outcome and the odds were significantly increased after 54 hrs of mild (elevated, but <180 mg/dL), 12 hrs of moderate (180-270 mg/dL), or any period of severe hyperglycemia (>270 mg/dL). Neonates (<1 month of age) tolerated longer periods of hyperglycemia before showing increased odds of reaching the composite morbidity-mortality end point. In the setting of important residual cardiac lesions, mild or moderate hyperglycemia was not as strongly associated with adverse outcomes. CONCLUSIONS: Age and residual cardiac lesions are important modifiers of the association between hyperglycemia and suboptimal outcomes after pediatric cardiac surgery. Use of insulin therapy for glucose control in this patient population may need to be carefully targeted toward high-risk subsets of patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".