Early Changes in Near-Infrared Spectroscopy Are Associated With Cardiac Arrest in Children With Congenital Heart Disease

Frontiers in Pediatrics

article

Priscilla Yu¹  Ivie Esangbedo²  Xilong Li³  Joshua Wolovits¹  Ravi Thiagarajan⁴  Lakshmi Raman¹ 

[1] Division of Critical Care, Department of Pediatrics, University of Texas Southwestern Medical Center;Division of Cardiac Critical Care, Department of Pediatrics, University of Washington Seattle;Department of Population and Data Sciences, University of Texas Southwestern Medical Center;Division of Cardiovascular Critical Care, Department of Pediatrics, Harvard University

关键词: near-infrared (NIR) spectroscopy;    cardiac arrest;    prediction;    children;    congenital heart disease;   

DOI  :  10.3389/fped.2022.894125

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Background The association of near-infrared spectroscopy (NIRS) with various outcomes after pediatric cardiac surgery has been studied extensively. However, the role of NIRS in the prediction of cardiac arrest (CA) in children with heart disease has yet to be evaluated. We sought to determine if a model utilizing regional cerebral oximetry (rSO2c) and somatic oximetry (rSO2s) could predict CA in children admitted to a single-center pediatric cardiac intensive care unit (CICU). Methods We retrospectively reviewed 160 index CA events for patients admitted to our pediatric CICU between November 2010 and January 2019. We selected 711 control patients who did not have a cardiac arrest. Hourly data was collected from the electronic health record (EHR). We previously created a machine-learning algorithm to predict the risk of CA using EHR data. Univariable analysis was done on these variables, which we then used to create a multivariable logistic regression model. The outputs from the model were presented by odds ratio (OR) and 95% confidence interval (CI). Results We created a multivariable model to evaluate the association of CA using five variables: arterial saturation (SpO2)- rSO2c difference, SpO2-rSO2s difference, heart rate, diastolic blood pressure, and vasoactive inotrope score. While the SpO2-rSO2c difference was not a significant contributor to the multivariable model, the SpO2-rSO2s difference was. The average SpO2-rSO2s difference cutoff with the best prognostic accuracy for CA was 29% [CI 26–31%]. In the multivariable model, a 10% increase in the SpO2-rSO2s difference was independently associated with increased odds of CA [OR 1.40 (1.18, 1.67), P < 0.001] at 1 h before CA. Our model predicted CA with an AUROC of 0.83 at 1 h before CA. Conclusion In this single-center case-control study of children admitted to a pediatric CICU, we created a multivariable model utilizing hourly data from the EHR to predict CA. At 1 h before the event, for every 10% increase in the SpO2-rSO2s difference, the odds of cardiac arrest increased by 40%. These findings are important as the field explores ways to capitalize on the wealth of data at our disposal to improve patient care.

【 授权许可】

CC BY