Sleep Breathing Flow Characteristics as a Sign for the Detection of Wakefulness in Patients with Sleep Apnea

Background: To improve the performance of simplified sleep studies, it is essential to properly estimate the sleep time. Objectives: Our aim is to estimate sleep efficiency on the basis of flow breathing signal characteristics. Methods: Twenty subjects with sleep apnea-hypopnea syndrome diagnosed by polysomnography were studied. A characteristic pattern of flow signal defined our criteria for wakefulness and sleep. Sleep was analyzed in 2 different runs: (1) in the usual manner (neurological and respiratory variables), and (2) only the nasal cannula flow signal was displayed on the computer screen and the sleep and wakefulness periods were scored according to our criteria. At the end of the scoring process, all the signals were displayed on the screen to analyze the concordance. Results: Three thousand and sixty-nine screens were analyzed. The polysomnography sleep efficiency measured was 80.8%. The estimated sleep efficiency measured by nasal prongs was 78.9%. The detection and concordance of wakefulness had a sensitivity of 58.7%, a specificity of 96.4%, a positive predictive value of 81.3% and a negative predictive value of 89.6%. Conclusions: Our criteria for sleep and wakefulness based on airflow waveform morphology are a helpful parameter for estimating sleep efficiency in a simplified sleep study.