Reiter Joel, Zleik Bashar, Bazalakova Mihaela, Mehta Pankaj, Thomas Robert Joseph
Sleep Disorders Clinic, Departments of Medicine & Neurology, Beth Israel Deaconess Medical Center, Boston, MA.
Pediaric Pulmonary Unit, Department of Pediatrics, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.
J Clin Sleep Med. 2016 Aug 15;12(8):1153-8. doi: 10.5664/jcsm.6056.
To assess the frequency, severity, and determinants of residual respiratory events during continuous positive airway therapy (CPAP) for obstructive sleep apnea (OSA) as determined by device output.
Subjects were consecutive OSA patients at an American Academy of Sleep Medicine accredited multidisciplinary sleep center. Inclusion criteria included CPAP use for a minimum of 3 months, and a minimum nightly use of 4 hours. Compliance metrics and waveform data from 217 subjects were analyzed retrospectively. Events were scored manually when there was a clear reduction of amplitude (≥ 30%) or flow-limitation with 2-3 larger recovery breaths. Automatically detected versus manually scored events were subjected to statistical analyses included Bland-Altman plots, correlation coefficients, and logistic regression exploring predictors of residual events.
The mean patient age was 54.7 ± 14.2 years; 63% were males. All patients had a primary diagnosis of obstructive sleep apnea, 26% defined as complex sleep apnea. Residual flow measurement based apnea-hypopnea index (AHIFLOW) > 5, 10, and 15/h was seen in 32.3%, 9.7%, and 1.8% vs. 60.8%, 23%, and 7.8% of subjects based on automated vs. manual scoring of waveform data. Automatically detected versus manually scored average AHIFLOW was 4.4 ± 3.8 vs. 7.3 ± 5.1 per hour. In a logistic regression analysis, the only predictors for a manual AHIFLOW > 5/h were the absolute central apnea index (CAI), (odds ratio [OR]: 1.5, p: 0.01, CI: 1.1-2.0), or using a CAI threshold of 5/h of sleep (OR: 5.0, p: < 0.001, CI: 2.2-13.8). For AHIFLOW > 10/h, the OR was 1.14, p: 0.03 (CI: 1.1-1.3) per every CAI unit of 1/hour.
Residual respiratory events are common during CPAP treatment, may be missed by automated device detection and predicted by a high central apnea index on the baseline diagnostic study. Direct visualization of flow data is generally available and improves detection.
通过设备输出评估阻塞性睡眠呼吸暂停(OSA)患者持续气道正压通气(CPAP)治疗期间残余呼吸事件的频率、严重程度及决定因素。
研究对象为美国睡眠医学会认可的多学科睡眠中心的连续性OSA患者。纳入标准包括使用CPAP至少3个月,每晚至少使用4小时。对217名受试者的依从性指标和波形数据进行回顾性分析。当振幅明显降低(≥30%)或出现流量限制并伴有2 - 3次较大的恢复呼吸时,手动对事件进行评分。对自动检测与手动评分的事件进行统计分析,包括Bland - Altman图、相关系数以及探索残余事件预测因素的逻辑回归分析。
患者平均年龄为54.7±14.2岁;63%为男性。所有患者的初步诊断均为阻塞性睡眠呼吸暂停,26%被定义为复杂性睡眠呼吸暂停。基于残余流量测量的呼吸暂停低通气指数(AHIFLOW)>5、10和15次/小时的情况,在波形数据自动评分与手动评分的受试者中分别为32.3%、9.7%和1.8%,以及60.8%、23%和7.8%。自动检测与手动评分的平均AHIFLOW分别为每小时4.4±3.8次和7.3±5.1次。在逻辑回归分析中,手动AHIFLOW>5次/小时的唯一预测因素是绝对中枢性呼吸暂停指数(CAI)(比值比[OR]:1.5,p:0.01,可信区间[CI]:1.1 - 2.0),或使用睡眠期间CAI阈值为5次/小时(OR:5.0,p:<0.001,CI:2.2 - 13.8)。对于AHIFLOW>10次/小时,每1小时CAI单位的OR为1.14,p:0.03(CI:1.1 - 1.3)。
CPAP治疗期间残余呼吸事件很常见,自动设备检测可能会遗漏这些事件,且在基线诊断研究中可通过高中枢性呼吸暂停指数进行预测。流量数据的直接可视化通常是可行的,并且能改善检测效果。