Classification of sleep-disordered breathing
Classification of sleep-disordered breathing
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DOI：
10.1164/ajrccm.163.2.9808132
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发表时间：
2001-02-01
影响因子：
24.7
通讯作者：
Rapoport, DM
中科院分区：
文献类型：
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作者：
Hosselet, JJ;Ayappa, I;Rapoport, DM
人们对睡眠障碍呼吸(SDB)及其发病率的认识不断提高，促使人们重新评估识别睡眠期间呼吸事件的技术。本研究旨在评估SDB的各种指标的实用性，并确定客观上与日间过度嗜睡(EDS)症状相关的最佳呼吸指标。指标来源于常规呼吸暂停/低呼吸、血流限制事件(通过使用无创鼻插管技术在血流/时间追踪上通过特征平坦化识别暂时性的上呼吸道阻力升高)、减饱和度和觉醒。共有137名受试者接受了临床评估和夜间多导睡眠图检查。在随机选择的34例受试者中，通过受试者曲线分析，确定了13例无EDS/鼾症患者和21例EDS伴鼾症患者的最佳鉴别指标。在所测试的指标和临界点中，总呼吸紊乱指数(RDITotal、呼吸暂停、低呼吸和血流受限事件的总和)被发现具有最好的判别能力(100%的敏感性和96%的特异性)。然后对其余103名受试者(14名非打鼾者，21名打鼾者非EDS者，68名打鼾者伴EDS者)进行前瞻性测试。使用18个事件/小时的截断值，我们获得了71%的敏感性和60%的特异性来识别患有EDS的受试者。我们的结论是，在上呼吸道功能障碍的受试者中，包含所有呼吸事件的指数提供了与EDS最佳的定量生理学相关性。
Increasing recognition of sleep-disordered breathing (SDB) and its morbidity have prompted reevaluation of techniques to identify respiratory events during sleep. The present study was designed to evaluate the utility of various metrics of SDB and to identify the optimal respiratory metric that objectively correlates to symptoms of excessive daytime somnolence (EDS). Metrics were derived from combinations of conventional apnea/hypopnea, flow limitation events (transient elevated upper airway resistance identified by characteristic flattening on the flow/time tracing, using a noninvasive nasal cannula technique), desaturation, and arousal. A total of 137 subjects underwent clinical evaluation and nocturnal polysomnogram. In 34 randomly selected subjects, the best metrics for discriminating between 13 subjects with no EDS/snoring and 21 patients with EDS and snoring were identified by receiver operator curve analysis. Of the metrics and cut points tested, a total respiratory disturbance index (RDITotal, sum of apneas, hypopnea, and flow limitation events) of 18 events/h was found to have the best discriminant ability (100% sensitivity and 96% specificity). Prospective testing of this metric was then performed with the remaining 103 subjects (14 nonsnoring non-EDS, 21 snoring non-EDS, 68 snoring with EDS). Using this cutoff of 18 events/h, we obtained 71% sensitivity and 60% specificity for identifying subjects with EDS. We conclude that, in subjects with upper airway dysfunction, an index that incorporates all respiratory events provides the best quantitative physiological correlate to EDS.