Abstract

Though commonly used for adjustment of risk, severity of illness and mortality risk prediction scores, based on the first 24 h of intensive care unit (ICU) admission, have not been validated in the pediatric extracorporeal membrane oxygenation (ECMO) population. We aimed to determine the association of Pediatric Index of Mortality 2 (PIM2), Pediatric Risk of Mortality Score III (PRISM III) and Pediatric Logistic Organ Dysfunction (PELOD) scores with mortality in pediatric patients on ECMO. This was a retrospective cohort study of children ≤18 years of age included in the Pediatric ECMO Outcomes Registry (PEDECOR) from 2014 to 2018. Logistic regression and Receiver Operating Characteristics (ROC) curves were used to calculate the area under the curve (AUC) to evaluate association of mortality with the scores. Of the 655 cases, 289 (44.1%) did not survive until hospital discharge. AUCs for PIM2, PRISM III, and PELOD predicting mortality were 0.52, 0.52, and 0.51 respectively. PIM2, PRISM III, and PELOD scores are not associated with odds of mortality for pediatric patients receiving ECMO. These scores for a general pediatric ICU population should not be used for prognostication or risk stratification of a select population such as ECMO patients.

Highlights

  • Tools to gauge severity of illness (SOI) and predict outcomes for children treated with extracorporeal membrane oxygenation (ECMO) can facilitate medical decision making, counseling of patients’ families, and prognostication

  • Logistic regression and Receiver Operating Characteristics (ROC) curves were used to calculate the area under the curve (AUC) for predicting mortality with Pediatric Index of Mortality 2 (PIM2), PRISM III, and Pediatric Logistic Organ Dysfunction (PELOD) to assess discrimination

  • Seven hundred fifty six ECMO runs were evaluated in pediatric patients ≤18years

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Summary

Introduction

Tools to gauge severity of illness (SOI) and predict outcomes for children treated with extracorporeal membrane oxygenation (ECMO) can facilitate medical decision making, counseling of patients’ families, and prognostication. ECMO is a cardio-pulmonary support modality for patients in severe cardiac and/or respiratory failure. It can be a life-saving therapy for patients who might otherwise not survive but is associated with significant morbidity and mortality. Patients requiring ECMO have increased severity of illness than the average pediatric intensive care unit (PICU) patient and have higher mortality [1]. It is not uncommon to include markers of SOI or predictors of mortality in multivariable analysis to adjust for illness severity in comparing patients

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