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Author Spotlight: Simulating Pediatric Cardiac Surgery Using a Neonatal Piglet Model
Published on: May 26, 2023
Predicting and Surviving Prolonged Critical Illness After Congenital Heart Surgery
Aaron G DeWitt1, Joseph W Rossano2, David K Bailly3
1Division of Cardiac Critical Care Medicine, Departments of Pediatrics and Anesthesia & Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, Philadelphia, PA.
Insights
Prolonged critical illness after pediatric heart surgery is common, with many predictors being preventable. Identifying best practices at hospitals with lower rates can improve care and reduce mortality.
Area of Science:
- Pediatric critical care medicine
- Congenital heart surgery outcomes
- Healthcare quality improvement
Background:
- Prolonged critical illness (PCI) following congenital heart surgery (CHS) significantly impacts patients and healthcare resources.
- Understanding predictors and variations in PCI is crucial for improving outcomes.
Purpose of the Study:
- To define PCI, identify nonmodifiable and potentially preventable predictors of PCI and its mortality.
- To analyze interhospital variation in PCI rates after CHS.
Main Methods:
- Observational analysis of the Pediatric Cardiac Critical Care Consortium clinical registry.
- Stratified analysis of neonates (≤28 days) and nonneonates (29 days to 18 years).
- Multivariable logistic regression to identify predictors of PCI and mortality.
Main Results:
- PCI occurred in 24% of neonates and 8% of nonneonates, with higher mortality than non-PCI patients.
- Identified 10 neonatal and 19 nonneonatal PCI predictors; only 1 mortality predictor was nonmodifiable.
- Approximately 40% of PCI predictors were nonmodifiable, while most mortality predictors were potentially preventable.
Conclusions:
- While some PCI predictors are nonmodifiable, many are preventable, offering targets for intervention.
- Complications and critical care interventions significantly influence PCI mortality.
- Significant interhospital variation in PCI rates suggests opportunities for quality improvement by adopting practices from high-performing centers.
Objectives:
Prolonged critical illness after congenital heart surgery disproportionately harms patients and the healthcare system, yet much remains unknown. We aimed to define prolonged critical illness, delineate between nonmodifiable and potentially preventable predictors of prolonged critical illness and prolonged critical illness mortality, and understand the interhospital variation in prolonged critical illness.
Design:
Observational analysis.
Setting:
Pediatric Cardiac Critical Care Consortium clinical registry.
Patients:
All patients, stratified into neonates (≤28 d) and nonneonates (29 d to 18 yr), admitted to the pediatric cardiac ICU after congenital heart surgery at Pediatric Cardiac Critical Care Consortium hospitals.
Interventions:
None.
Measurements And Main Results:
There were 2,419 neonates and 10,687 nonneonates from 22 hospitals. The prolonged critical illness cutoff (90th percentile length of stay) was greater than or equal to 35 and greater than or equal to 10 days for neonates and nonneonates, respectively. Cardiac ICU prolonged critical illness mortality was 24% in neonates and 8% in nonneonates (vs 5% and 0.4%, respectively, in nonprolonged critical illness patients). Multivariable logistic regression identified 10 neonatal and 19 nonneonatal prolonged critical illness predictors within strata and eight predictors of mortality. Only mechanical ventilation days and acute renal failure requiring renal replacement therapy predicted prolonged critical illness and prolonged critical illness mortality in both strata. Approximately 40% of the prolonged critical illness predictors were nonmodifiable (preoperative/patient and operative factors), whereas only one of eight prolonged critical illness mortality predictors was nonmodifiable. The remainders were potentially preventable (postoperative critical care delivery variables and complications). Case-mix-adjusted prolonged critical illness rates were compared across hospitals; six hospitals each had lower- and higher-than-expected prolonged critical illness frequency.
Conclusions:
Although many prolonged critical illness predictors are nonmodifiable, we identified several predictors to target for improvement. Furthermore, we observed that complications and prolonged critical care therapy drive prolonged critical illness mortality. Wide variation of prolonged critical illness frequency suggests that identifying practices at hospitals with lower-than-expected prolonged critical illness could lead to broader quality improvement initiatives.
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