颏舌
医学
人工智能
心理学
模式识别(心理学)
听力学
计算机科学
心脏病学
阻塞性睡眠呼吸暂停
作者
Zhou Yingqian,Guoping Yin,Jinkun Xu,Xin Cao,Jingying Ye
摘要
Abstract Objective This study aims to develop a novel method to classify different genioglossus (GG) responses to upper airway (UA) negative pressure in obstructive sleep apnea (OSA) patients. Study Design A single‐center, prospective, cohort study. Setting Sleep Medical Center. Methods Patients with OSA underwent drug‐induced sleep endoscopy with synchronous genioglossus electromyography (ggEMG) and UA pressure monitoring. In spontaneous obstructive apnea events, the value of epiglottis negative pressure at the end of inspiration (P epi ) and corresponding peak phasic ggEMG were recorded as pairing data for linear regression analysis to classify GG response modes: peak phasic ggEMG‐P epi linear mode ( P < .05) were classified as group 1; others ( P ≥ .05) were classified as group 2. Using nasopharyngeal tube (NPT) to reopen the palatopharyngeal cavity for comparing the improvement between the OSA patients with different GG response modes. Results Sixty subjects were analyzed for GG response modes: 22 patients were in group 1 ( r 2 = 0.233‐0.867), and 38 patients were in group 2. The proportion of partial (63.16% vs 59.09%) or complete (36.84% vs 22.73%) collapse rate of the tongue base in group 2 was significantly higher ( χ 2 = 7.823, P = .020). The improvement of the apnea‐hypopnea index after NPT placement in group 2 was significantly lower than in group 1 (59.09% vs 31.58%, χ 2 = 4.339, P = .037). Conclusion This novel method is advantageous for distinguishing OSA patients with different GG response abilities to UA negative pressure, whose GG responses conforming to peak phasic ggEMG‐P epi linear mode might be more suitable for palatopharyngeal surgery.
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