Heart rate variability analysis in pediatric obstructive sleep apneaautomated signal processing to identify biomarkers and help in the diagnosis

Resumen

Pediatric obstructive sleep apnea (OSA) is a respiratory disease defined by episodes of complete airflow cessation (apneas) or significant airflow reduction (hypopneas). This disorder is highly prevalent among children, affecting 5.7% of the pediatric population. If left untreated, it can lead to various adverse cardiovascular consequences, as well as cognitive and developmental impairments. Given the potential threat to the health of children, the early diagnosis and management of OSA are of the utmost importance, however being an underdiagnosed disease. Overnight polysomnography (PSG) is currently considered the gold standard diagnostic technique for pediatric OSA. This procedure involves children spending an entire night in a sleep laboratory, where numerous sensors are attached to their bodies to record up to 32 biomedical signals. Subsequently, medical experts visually analyze and score apneic events based on these recordings. The number of events of apneas and hypopneas per hour of sleep (e/h) is then calculated, resulting in the apnea-hypopnea index (AHI), which is used for diagnosing and determining the severity of OSA in children. Despite being the gold standard, PSG has certain drawbacks. It is time-consuming, complex, expensive, and highly uncomfortable for the pediatric population, leading to issues such as limited access and long waiting lists. As a result, there has been growing interest in exploring alternative techniques to simplify OSA diagnosis. The present Doctoral Thesis aims to comprehensively examine the behavior of HRV in children, seeking valuable insights into cardiac alterations associated with pediatric OSA that could aid in its diagnosis.