자동형 양압유지기의 자동적정 알고리즘 개발
Development of Auto-titrating Algorithm for Auto-titrating Positive Airway Pressure
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초록
This study proposes an auto-titrating algorithm for auto-titrating positive airway pressure (APAP). The process of the proposed algorithm is as follows. First, sleep apnea-hypopnea and snoring events were detected using nasal pressure. Second, APAP base pressure and SDB events were used for automatic titration of optimal pressure. And, auto-titrating algorithm is built into M3 (MEK-ICS CO. Ltd., Republic of Korea) for evaluation. The detection results of SDB showed mean sensitivity (Sen.) and positive predictive value (PPV.) of 85.7% and 87.8%, respectively. The mean pressure and apnea-hypopnea index (AHI) of auto-titrating algorithm showed 13.0±5.2 cmH2O and 3.0±2.4 events/h, respectively. And, paired t-test was conducted to verify whether the performance of our algorithm has no significant difference with AutoSet S9 (p>0.05). These results represent better or comparable outcomes compared to those of previous APAP devices.
Abstract
This study proposes an auto-titrating algorithm for auto-titrating positive airway pressure (APAP). The process of the proposed algorithm is as follows. First, sleep apnea-hypopnea and snoring events were detected using nasal pressure. Second, APAP base pressure and SDB events were used for automatic titration of optimal pressure. And, auto-titrating algorithm is built into M3 (MEK-ICS CO. Ltd., Republic of Korea) for evaluation. The detection results of SDB showed mean sensitivity (Sen.) and positive predictive value (PPV.) of 85.7% and 87.8%, respectively. The mean pressure and apnea-hypopnea index (AHI) of auto-titrating algorithm showed 13.0±5.2 cmH2O and 3.0±2.4 events/h, respectively. And, paired t-test was conducted to verify whether the performance of our algorithm has no significant difference with AutoSet S9 (p>0.05). These results represent better or comparable outcomes compared to those of previous APAP devices.
참고문헌 (7)
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