Perioperative Outcomes in Congenital Heart Disease: A Review of Clinical Factors Associated With Prolonged Ventilation and Length of Stay in Four Common CHD Operations
Bibliographic record
Abstract
OBJECTIVES: Perioperative management strategies and outcomes for low-risk congenital heart disease (CHD) surgery vary between institutions. To date, no consensus exists on standardized management for pediatric patients undergoing cardiac surgery. This study seeks to benchmark the perioperative management of 4 common CHD lesions and explore clinical factors affecting postoperative outcomes. DESIGN: A retrospective review of CHD procedures performed between 2015 and 2020. SETTING: The study was conducted at a single academic tertiary pediatric hospital. PARTICIPANTS: All patients presenting for repair of ventricular septal defects (VSDs), complete atrioventricular canal defects, tetralogy of Fallot (TOF), and transposition of the great arteries (TGA) were reviewed. INTERVENTIONS: Demographic and clinical data were collected; clinical outcomes were defined as postoperative length of ventilation (LOV) and hospital length of stay, divided into reference and prolonged course groups analyzed for variables associated with differences in outcomes. MEASUREMENTS AND MAIN RESULTS: We selected 931 patients for review. Prolonged length of ventilation and length of stay in all cohorts were associated with longer operative, cardiopulmonary bypass, and cross-clamp times; higher intraoperative requirements for inotropic support; more blood transfusions and higher opioid administration; lower pH preoperatively and higher lactic acid postoperatively. Worse outcomes were associated with younger age in VSD, older age in TGA, and lower weight in TOF and TGA. Worse outcomes were also associated with a higher preoperative hematocrit in VSD and TOF and elevated preoperative blood glucose in VSD and TGA. CONCLUSIONS: A better understanding of clinical factors affecting outcomes may facilitate streamlining perioperative management strategies for pediatric patients undergoing low-risk cardiac surgery.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".