• Maria Grazia Sacco Casamassima, Jose H Salazar, Dominic Papandria, James Fackler, Kristin Chrouser, Emily F Boss, and Fizan Abdullah.
• Center for Pediatric Surgical Clinical Trials and Outcomes Research, Division of Pediatric Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
• Eur. J. Pediatr. 2014 Jan 1;173(1):1-13.

UnlabelledThe complexity and high cost of neonatal and pediatric intensive care has generated increasing interest in developing measures to quantify the severity of patient illness. While these indices may help improve health care quality and benchmark mortality across hospitals, comprehensive understanding of the purpose and the factors that influenced the performance of risk stratification indices is important so that they can be compared fairly and used most appropriately. In this review, we examined 19 indices of risk stratification used to predict mortality in critically ill children and critically analyzed their design, limitations, and purposes. Some pediatric and neonatal models appear well-suited for institutional benchmarking purposes, with relatively brief data acquisition times, limited potential for treatment-related bias, and reliance on diagnostic variables that permit adjustment for case mix. Other models are more suitable for use in clinical trials, as they rely on physiologic variables collected over an extended period, to better capture the interaction between organ systems function and specific therapeutic interventions in acutely ill patients. Irrespective of their clinical or research applications, risk stratification indices must be periodically recalibrated to adjust for changes in clinical practice in order to remain valid outcome predictors in pediatric intensive care units. Longitudinal auditing, education, training, and guidelines development are also critical to ensure fidelity and reproducibility in data reporting.ConclusionRisk stratification indices are valid tools to describe intensive care unit population and explain differences in mortality.

13 keywords...

hide…