[Detecting of obstructive sleep apnea hypopnea syndrome using a multi-parameter pressure sensitive sleep monitor].

ABSTRACT

OBJECTIVE: To evaluate the efficacy of an electro-mechanical film-based(EMFi) multi-parameter pressure sensitive sleep monitor(MPSSM)on clinical diagnosis and research significance of obstructive sleep apnea hypopnea syndrome(OSAHS). METHODS: Retrospective analysis was made of 58 test subjects at Peking University Third Hospital with suspected OSAHS who were simultaneously monitored by MPSSM and polysomnography(PSG). The PSG test results were used as the gold standard in evaluating the sensitivity and specificity of OSAHS diagnosis of MPSSM. The test result consistency of sleep apnea and hypopnea index(AHI)and total apnea time of the two methods was evaluated. Real-time waveform comparison of sleep respiratory events of a randomly selected patient diagnosed with OSAHS was performed. RESULTS: For 58 test subjects, 48 were male, 10 were female, with an average age of(40.6±12.2)years. Thirty-nine out of the 58 test subjects were diagnosed with OSHAS by PSG. The sensitivity of MPSSM for OSAHS diagnosis was 92.3%, with 95% confidence interval of 79.1%-98.4%, and the specificity of MPSSM for OSAHS diagnosis was 100%, with 95% confidence interval of 82.3%-100%. Kappa test k=0.887 (P < 0.001) showed OSAHS diagnosis results of the two methods were almost identical. The AHI measured by MPSSM [12.0(2.6-32.2) times/h] and PSG [13.4(3.1-38.8) times/h] were highly correlated (ρ=0.939, P < 0.001). The total apnea time measured by MPSSM [37.9(9.9-80.5) min] and PSG [32.3(8.6-93.0) min] were highly correlated(ρ=0.924, P < 0.001). Bland-Altman plot showed that the consistency between the test results of the two methods was very high. CONCLUSION: As a portable, non-contact, fully automatic monitoring device, MPSSM is reliable in the screening of OSAHS compared with PSG. It is suitable to be promoted and applied in primary medical institutions, nursing homes and domestic usage. However, further research is required in improving the analysis of different sleep phase and the differentiation of central sleep apnea syndrome respiratory events in order to effectively assist medical personnel in making an accurate sleep apnea diagnosis.