Nocturnal Oximetry–based Evaluation of Habitually Snoring Children

Abstract

Neural network-based automated analyses of nSp_O₂ recordings provide accurate identification of OSA severity among habitually snoring children with a high pretest probability of OSA. Thus, nocturnal oximetry may enable a simple and effective diagnostic alternative to nocturnal polysomnography, leading to more timely interventions and potentially improved outcomes.