A novel multimodal computational system using near-infrared spectroscopy to monitor cerebral oxygenation during assisted ventilation in CDH patients.

BACKGROUND/PURPOSE: The aim of this study was to create a computational simulator to serve as an early alert system for cerebral hypoxemia prior to the onset of clinical symptoms.

METHODS

Neonates with congenital diaphragmatic hernia (Jan 2010-Dec 2014) were recruited to collect continuous measurements of cerebral tissue oxygen saturation (cStO2) using a near-infrared spectroscopy (NIRS) device (FORE-SIGHT®, CASMED). Clinicians were blinded to NIRS data and treated infants based on pre-established clinical protocols. Charts were reviewed retrospectively to identify clinical events of hypoxemia (spontaneous, sustained decrease in preductal SpO2<85% leading to ventilator changes). We developed a computational algorithm that determined baseline values, variability and event data for each patient.

RESULTS

Twenty-three of 36 patients enrolled met data criteria. The algorithm anticipated an event at least 15 minutes prior to the event in 77% of cases, with an average pre-event detection of 47 minutes (range 16-122 minutes). Post-event StO2 (SpO2<85%) was determined to be 63.7% ± 11.7. In this computational model, the sensitivity to distinguish low states of cerebral perfusion was 94% with a specificity of 96%.

CONCLUSION

We have developed a computational algorithm with an early warning system that has the potential of being translated into a real-time clinical interface that may improve management of neonates.