Introduction
Currently, the diagnosis and severity classification of Obstructive Sleep Apnea (OSA) heavily rely on traditional frequency indices such as the Apnea-Hypopnea Index (AHI) and Oxygen Desaturation Index (ODI), observed during sleep. However, these indices fall short in comprehensively considering the duration of ventilatory disturbances and the subsequent severity and duration of oxygen desaturation events. Consequently, they inadequately capture the pathophysiological abnormalities in OSA patients, limiting their efficacy in predicting the risk of associated adverse complications.
Polysomnography (PSG), the gold standard for OSA diagnosis, offers a wealth of physiological information and broad clinical feasibility, creating an avenue for new index development. In recent years, both domestic and international research teams have introduced a range of new PSG-derived indices to quantify OSA severity. Examples include mean respiratory event duration and hypoxic burden. However, consensus on the association between these new indices and OSA complications remains elusive, with varying outcomes in different studies.
The Sleep Breathing Impairment Index (SBII) calculation software addresses these issues by integrating the frequency and duration of respiratory events with associated oxygen saturation decline. This approach allows for a more nuanced quantification of OSA severity. The software facilitates automated batch processing of European Data Format (EDF) files and their annotation files (in XML format), making it suitable for large-scale OSA assessments. Simultaneously, it aids in exploring and managing target organ damage associated with the condition.
