Robert Baird1, Ying C MacNab, Erik D Skarsgard. 1. Division of Pediatric Surgery, British Columbia Children's Hospital, Vancouver, British Columbia, Canada V6H 3V4.
Abstract
BACKGROUND: A validated risk stratification tool for congenital diaphragmatic hernia (CDH) is required for accurate outcomes analyses. Existing mortality-predictive models include those of the CDH Study Group (CDHSG) based on birth weight and 5-minute Apgar score, the Canadian Neonatal Network (CNN) based on gestational age and admission score in Score for Neonatal Acute Physiology version II, and the Wilford Hall/Santa Rosa clinical prediction formula (WHSR(PF)) derived from blood gas measurements. The purpose of this study was to evaluate the calibration and discrimination of these predictive models using the Canadian Pediatric Surgical Network dataset. METHODS: Neonatal risk variables and birth hospital survivorship were collected prospectively in 11 perinatal centers, between May 2005 and October 2006. Actual vs predicted outcomes were analyzed for each equation to measure the calibration and discrimination of each model. RESULTS: Twenty (21.2%) of 94 infants with CDH died during birth hospitalization. The CDHSG model demonstrated superior discrimination (area under the receiver operator characteristic curve = 0.85; CNN = 0.79; WHSR(PF) = 0.63). Model calibration reflected by the Hosmer-Lemeshow P value was poorest with the WHSR(PF) = 0.37 and comparable between CDHSG and CNN (0.48 and 0.46, respectively). CONCLUSION: Predictive outcome models are essential for risk-adjusted outcome analysis of CDH. The ideal predictive equation should prove robust across CDH datasets.
BACKGROUND: A validated risk stratification tool for congenital diaphragmatic hernia (CDH) is required for accurate outcomes analyses. Existing mortality-predictive models include those of the CDH Study Group (CDHSG) based on birth weight and 5-minute Apgar score, the Canadian Neonatal Network (CNN) based on gestational age and admission score in Score for Neonatal Acute Physiology version II, and the Wilford Hall/Santa Rosa clinical prediction formula (WHSR(PF)) derived from blood gas measurements. The purpose of this study was to evaluate the calibration and discrimination of these predictive models using the Canadian Pediatric Surgical Network dataset. METHODS: Neonatal risk variables and birth hospital survivorship were collected prospectively in 11 perinatal centers, between May 2005 and October 2006. Actual vs predicted outcomes were analyzed for each equation to measure the calibration and discrimination of each model. RESULTS: Twenty (21.2%) of 94 infants with CDH died during birth hospitalization. The CDHSG model demonstrated superior discrimination (area under the receiver operator characteristic curve = 0.85; CNN = 0.79; WHSR(PF) = 0.63). Model calibration reflected by the Hosmer-Lemeshow P value was poorest with the WHSR(PF) = 0.37 and comparable between CDHSG and CNN (0.48 and 0.46, respectively). CONCLUSION: Predictive outcome models are essential for risk-adjusted outcome analysis of CDH. The ideal predictive equation should prove robust across CDH datasets.
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