Predicting and Surviving Prolonged Critical Illness After Congenital Heart Surgery
| Autor: | Wenying Zhang, Joseph W. Rossano, Aaron G. DeWitt, Geoffrey L. Bird, Michael-Alice Moga, Gabe E. Owens, Priya N. Bhat, Mousumi Banerjee, David K. Bailly, Michael Gaies, Lauren Retzloff, Brandon Kirkland, Nikhil K. Chanani, Andrew T. Costarino |
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| Rok vydání: | 2020 |
| Předmět: |
Male
medicine.medical_specialty Heart Diseases Critical Illness medicine.medical_treatment Observational analysis Psychological intervention Intensive Care Units Pediatric Critical Care and Intensive Care Medicine Logistic regression Article 03 medical and health sciences 0302 clinical medicine Risk Factors medicine Humans Clinical registry cardiovascular diseases Registries Renal replacement therapy Cardiac Surgical Procedures Child Mechanical ventilation business.industry Infant Newborn Infant 030208 emergency & critical care medicine Length of Stay Surgery surgical procedures operative 030228 respiratory system Child Preschool Critical illness Female business therapeutics Healthcare system |
| Zdroj: | Crit Care Med |
| ISSN: | 0090-3493 |
| DOI: | 10.1097/ccm.0000000000004354 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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