Pediatr Crit Care Me
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Pediatr Crit Care Me · Jun 2016
Randomized Controlled Trial Multicenter StudyScore for Neonatal Acute Physiology-II Predicts Outcome in Congenital Diaphragmatic Hernia Patients.
Accurate and validated predictors of outcome for infants with congenital diaphragmatic hernia are needed. Score for Neonatal Acute Physiology-II has been validated to predict mortality in newborns. We investigated whether Score for Neonatal Acute Physiology-II scores in congenital diaphragmatic hernia could predict mortality, need for extracorporeal membrane oxygenation (in patients born in a center with extracorporeal membrane oxygenation availability), and development of bronchopulmonary dysplasia (oxygen dependency beyond 28 d after birth) in survivors. ⋯ The Score for Neonatal Acute Physiology-II predicts not only mortality but also need for extracorporeal membrane oxygenation in congenital diaphragmatic hernia patients. We, therefore, recommend to implement this simple and rapid scoring system in the evaluation of severity of illness in patients with congenital diaphragmatic hernia and thereby have insight into the prognosis within 1 day after birth.
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Pediatr Crit Care Me · Jun 2016
Development of a Prediction Model of Early Acute Kidney Injury in Critically Ill Children Using Electronic Health Record Data.
Acute kidney injury is independently associated with poor outcomes in critically ill children. However, the main biomarker of acute kidney injury, serum creatinine, is a late marker of injury and can cause a delay in diagnosis. Our goal was to develop and validate a data-driven multivariable clinical prediction model of acute kidney injury in a general PICU using electronic health record data. ⋯ We developed and validated the Pediatric Early AKI Risk Score, a data-driven acute kidney injury clinical prediction model that has good discrimination and calibration in a general PICU population using only electronic health record data that is objective, available in real time during the first 12 hours of ICU care and generalizable across PICUs. This prediction model was designed to be implemented in the form of an automated clinical decision support system and could be used to guide preventive, therapeutic, and research strategies.