Year: 2025
Type: article
Study design: Observational Study
Abstract: Obstructive sleep apnea (OSA) syndrome is a major health problem affecting 2 to 4% of the middle-aged population, so screening tests had to be established for the diagnosis of sleep-related breathing disorders. However, there isa great demand for polysomnography (PSGs), performing PSGs is a costly, labor-intensive uncomfortable techniqueand also not available in all areas. As oxygen saturation is often used as a main diagnostic criterion of these screening tests, so it is important to study the correlation between overnight oximetry and degree of obstructive sleep apnea. To investigate the relative usefulness of pulse oximetry in the diagnosis of OSA, and to determine sensitivityand specificity of average O2 saturation and minimum O2 saturation in predicting the degree of obstructive sleepapnea. This study was conducted during the period from December 2014 to November 2015 in Misurata, Libya. Itincluded 120 patients (52 women, 68 men) suspected to suffer from sleep apnea-syndrome. Participants underwentpulse oximetry recordings which was performed simultaneously during polysomnography for suspicion of OSA.Then oxygen saturation (pulse oximetry) was compared with respiratory disturbance index (RDI, polysomnography). An RDI ≥ 5/h and a minimal oxygen saturation < 90% and/or more than 5 oxygen desaturations/h ≥ 4% wereregarded as pathological. We found high statistically significant positive correlation between the severity of RDIwith average O2 saturation and O2 Saturation Minimum. Minimum O2 Saturation is better than average O2 Saturation in predicting the severity of RDI and better in predicting severe cases than mild cases (Sensitivity = 70.6 % ,Specificity = 80.8 % and Accuracy = 75.9 % at cutoff "Minimum O2 Saturation ≤ 79.5 %").We concluded thatpulse oximetry in combination with a positive case history is a sensitive method to recognize sleep apnea-patients.
Authors: Mohamed E. Eltwayeb, Abdelazeem A. M
Institutions: Misurata University, Zagazig University
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4414874966
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