阻塞性睡眠呼吸暂停低通气综合征患者睡眠片段的评估-脉搏传导时间微觉醒

目的脉搏传导时间(PTT)是一项反映周围血管阻力和胸腔内压变化的无创指标,因此和微觉醒相关的血压改变可通过PTT检测。本文评估PTT微觉醒能否作为阻塞性睡眠呼吸暂停低通气综合征患者睡眠片断的指标。方法选择疑诊有睡眠呼吸障碍者39例,使用Rembrandt和HypnoPTT睡眠监测系统进行同步夜间睡眠呼吸监测,监测前进行ESS(epworth sleepiness scale)嗜睡评分。对三项常规判断睡眠片断的客观指标:脑电图(EEG)微觉醒指数、呼吸暂停低通气量指数(AHI)、氧减指数(ODI)和反映嗜睡的主观指标ESS评分,同PTT微觉醒指数进行比较。结果PTT微觉醒指数和EEG微觉醒指数之间呈正相关(r=0.725,P<0.01);PTT微觉醒指数、EEG微觉醒指数分别与呼吸事件(AHI、ODI)之间呈正相关(r=0.791;r=0.670;r=0.755;r=0.765,P分别小于<0.01)。而PTT微觉醒指数和EEG微觉醒指数与ESS评分之间相关性较差(r=0.449;r=0.196,P分别>0.01)。结论PTT微觉醒和反映阻塞性睡眠呼吸暂停低通气患者睡眠片断的其他指标密切相关,可作为判断睡眠片断的一项简单而准确的客观指标。     

微动敏感床垫式睡眠监测系统(RS611)对阻塞性睡眠呼吸暂停低通气综合征的诊断价值

目的评价微动敏感床垫式睡眠监测系统(RS611)对阻塞性睡眠呼吸暂停低通气综合征(OSAHS)的诊断价值。方法 38例OSAHS患者行整夜多导睡眠呼吸监测和微动敏感床垫式睡眠监测系统(RS611)监测。多导睡眠呼吸监测根据标准规则判断睡眠呼吸事件;微动敏感床垫式系统(RS611),根据计算机设计程序自动运算,分析所采集分离出的心动波、呼吸节律、腿动及胸动冲击,计算出呼吸事件频率,睡眠结构和各种睡眠参数,得出睡眠呼吸暂停指数(SRM AHI)。将两种检查所得AHI指数进行统计学分析,比较其相关性、一致性及诊断价值检验。对两个睡眠结构图逐屏进行分析,比较两种检查的觉醒、睡眠一致性;觉醒、NREMS期睡眠、REM期睡眠的一致性。结果平均年龄(46.16±12.29)岁,身体质量指数(28.41±4.57)kg/m2,平均PSG AHI(32.29±20.41)h,平均RS611 AHI(39.23±23.52)h,PSG AHI和RS611 AHI指数间显著相关(r=0.83,P0.001),为评估PAT检测的敏感性和特异性,构建ROC曲线,以AHI的不同阈值(5,15,30),在不同阈值时最佳敏感度和特异度分别是100/75,100/77.8,77.8/100。两种睡眠结构比较,醒-睡一致性为91%,觉醒、NREMS、REMS期睡眠的一致性为68%。结论微动敏感床垫式睡眠监测系统(RS611)是一种精确检测OSAHS的装置,监测简便而准确。     

阻塞性睡眠呼吸暂停综合征并发心律失常临床观察

目的探讨阻塞性睡眠呼吸暂停综合征(OSAS)与心律失常的相关性。方法对经多导睡眠呼吸监测仪(polysomnogra-phy,PSG)监测确诊的62例患者行同步24 h动态心电图监测,根据PSG结果选20例单纯鼾症患者对照分析。结果观察发现OSAS患者体重、睡眠呼吸暂停低通气指数(AHI)、动态血氧饱和度改变及心律失常发生率较对照组有统计学意义(P0.01),OSAS组心律失常发生率明显高于鼾症患者。结论 OSAS患者心律失常的发生与呼吸暂停低通气指数及低氧血症密切相关。     

阻塞性睡眠呼吸暂停低通气综合征患者微觉醒与夜间心率变异的关系

目的探讨阻塞性睡眠呼吸暂停低通气综合征(OSAHS)患者微觉醒与夜间心率变异(HRV)的关系。方法本研究对象为27例经整夜多导睡眠图(PSG)诊断为中重度 OSAHS 的患者。所有患者每人选择1h 连续非快速动眼睡眠(NREM)的 PSG 记录,将1h 内每个呼吸紊乱相关微觉醒开始前10s 的平均心率(HR)和微觉醒开始后10s 的最高 HR 进行比较,同时计算1h 内呼吸紊乱相关微觉醒指数(B-ArI)和脉率升高指数(PRRI)并作相关分析。此外对18例中重度 OSAHS 患者选择NREM 睡眠时10个不伴微觉醒的事件和10个伴有微觉醒的事件[按最低动脉血氧饱和度(minSaO_2)进行匹配],比较两组事件终止前后心率变化(ΔHR)。结果微觉醒开始后10s 的最高 HR[(81.6±9.4)次/min]显著高于微觉醒开始前10s 的平均 HR[(69.6±7.3)次/min,t=-14.87、P<0.01],且 B-ArI 与 PRRI 呈显著正相关(r=0.97,P<0.01),伴有微觉醒的呼吸事件终止前后ΔHR[(11.1±2.8)次/min]显著高于不伴微觉醒的呼吸事件[(7.0±2.4)次/min,t=4.702、P<0.01]。结论 B-ArI 与夜间 HRV 相关,提示微觉醒可影响心血管调节功能,频繁的微觉醒是导致 OSAHS 患者心血管后果的重要原因之一。     

便携式睡眠监测与多导睡眠监测临床应用差异性比较

目的 比较便携式睡眠监测(PM)与多导睡眠监测(PSG)两种方法在临床上诊断阻塞性睡眠呼吸暂停综合征(OSAS)的差异性,为PM在临床中的应用提供参考.方法 对84例疑似OSAS并已行PSG的入选者行PM,将两组监测结果进行统计分析,比较其各主要参数的差异性,并分析PM的准确度.结果 两种监测方法在呼吸紊乱指数、氧减指...     

阻塞性睡眠呼吸暂停患者呼吸事件相关觉醒与脉率升高的关系

目的探讨阻塞性睡眠呼吸暂停(OSA)患者呼吸事件相关觉醒与脉率升高的关系, 评估脉率升高能否作为觉醒的替代标志物。方法选取2021年1月至2022年8月就诊于天津医科大学总医院呼吸与危重症医学科睡眠中心进行多导睡眠监测(PSG)的80例患者[男性40例、女性40例、年龄18～63(37±13)岁]稳定的非快速眼动睡眠(NREM)的PSG记录, 比较每个呼吸事件相关觉醒开始前10 s的平均脉率、最低脉率和觉醒结束后10 s内的最高脉率, 同时分析觉醒指数与脉率升高指数(PRRI)以及ΔPR1(最高脉率-最低脉率)和ΔPR2(最高脉率-平均脉率)分别与呼吸事件持续时间、觉醒持续时间、脉搏血氧饱和度(SpO2)下降幅度和最低SpO2的相关性。对其中53例患者各选择NREM时10个不伴觉醒的事件和10个伴有觉醒的事件(按SpO2下降幅度进行匹配), 比较两组事件终止前后ΔPR。此外, 选取50例患者同步进行便携式睡眠监测(PM), 并分为非重度OSA组(n=22)和重度OSA组(n=28), 分别采用呼吸事件后ΔPR≥3、≥6、≥9、≥12次作为觉醒的替代标志物, 将ΔPR进行手动评分并整合到...     

Watch-PAT睡眠监测系统与Compumedics多导睡眠监测系统的对比研究

目的 评价一种通过测定外周交感活性来判断呼吸事件的便携式睡眠仪Watch-PAT诊断阻塞性睡眠呼吸暂停低通气综合征(OSAHS)的效率和准确度.方法 对20例疑诊OSAHS的患者在睡眠室由专业的技术人员同时进行多导睡眠仪(Compumedics)和Watch-PAT(型号:WP-200)监测.PSG的数据根据AASM指南由专业技术人员进行分析;Watch-PAT通过记录外周动脉弹性、心率、血氧饱和度和体位来判断呼吸暂停和低通气事件、血氧以及睡眠状态,并自动分析和生成报告.对比PSG和Watch-PAT的数据,比较的指标包括呼吸暂停低通气指数(AHI)、平均血氧饱和度(SpO2 mean)、最低血氧饱和度(SpO2min)、总睡眠时间(TST)和睡眠结构(REM/NREM).结果 受试者的年龄为(47.95±12.43)岁,体质量指数(BMI)为(28.82±4.15)kg/m2.PSG监测的AHI是(37.65±31.34)次/h.Watch-PAT和PSG的AHI、SpO2 min、SpO2 mean、TST和REM/NREM均高度相关(r=0.99,0.97,0.98,0.78,0.69,P值均＜0.001).Watch-PAT和PSG计算的AHI差异无统计学意义[(37.41±28.85)次/h比(37.65±31.34)次/h],P＞0.05).但Watch-PAT的TST和REM/NREM要高于PSG的结果(P ＜0.01);Watch-PAT的SpO2 mean和SpO2 min也高于PSG的结果(P＜0.01).当PSG AHI≥5次/h为诊断界值时,Watch-PAT AHI的ROC曲线下面积为1.0,其诊断的灵敏度和特异度分别是100％和100％(Watch-PAT AHI≥6.95次/h).当PSG AHI≥15次/h为诊断界值时,Watch-PAT AHI 的ROC曲线下面积为0.98,其诊断的灵敏度和特异度分别是100％和85.7％ (Watch-PAT AHI≥18.4次/h).通过Bland Altman图,可以看出PSG和Watch-PAT的诊断结果具有较好的符合度.结论 Watch-PAT通过测定外周动脉弹性来判断呼吸事件和睡眠状态的方法简单易行,结果可靠.是一种简便有效的便携式睡眠监测仪.     

被动鼻呼吸多导睡眠图监测对儿童OSAHS诊断的初步报告

目的探讨被动鼻呼吸多导睡眠图(PSG)监测对诊断儿童阻塞性睡眠呼吸暂停低通气综合征(OSAHS)的临床应用价值。方法对比分析同一患儿张口呼吸及闭唇被动鼻呼吸PSG监测情况。结果PSG监测报告显示呼吸暂停低通气指数(AHI)、阻塞性呼吸暂停指数(OAI)参数在闭唇被动鼻呼吸状态较张口呼吸状态增高,最低血氧饱和度(LSaO_2)降低。结论张口呼吸状态睡眠监测掩饰了患儿的OSAHS严重程度,可尝试使用闭唇睡眠监测以提高儿童OSAHS的阳性检出率。     

两种方法诊断OSAHS的比较

目的探讨便携式睡眠监测仪在诊断阻塞性睡眠呼吸暂停低通气综合征（OSAHS）中的作用,为临床应用更简易、准确、低成本的诊断方法提供参考。方法采用某进口的多导睡眠仪（PSG）和便携式睡眠监测仪,对60例怀疑有OSAHS的对象均采用两种方法进行监测,比较两种诊断方法各指标的差异,以及便携式睡眠监测仪的敏感性、特异性。结果两种方法所得呼吸紊乱指数、平均血氧饱和度、最低血氧饱和度、低于90％的血氧饱和度时间等均无显著性差异（P〉0．05）。与PSG比,便携式睡眠监测仪的敏感性为100％,特异性为60％;对病情分度判断的符合率分别为轻度73．3％、中度71．4％、重度94．4％。结论便携式睡眠监测仪对诊断OSAHS有高敏感性,尤其对重度OSAS的诊断更为准确,适合于临床常规诊断。     

便携式睡眠呼吸监测对OSAHS的诊断价值

目的探讨便携式睡眠呼吸监测(PM)对阻塞性睡眠呼吸暂停低通气综合征(OSAHS)的诊断价值。方法对156例临床打鼾的患者首先行PM检查,经PM诊断为OSAHS患者,进一步行多导睡眠监测(PSG),比较两者监测参数的差异。结果 156例患者经PM诊断为OSAHS共有124例,单纯鼾症32例。两种检查方法在呼吸暂停低通气指数(AHI)、氧减指数(ODI)、最低血氧饱和度(LSpO2)、平均血氧饱和度(MSpO2)等参数之间的差异无统计学意义(P0.05)。结论 PM是一种简单、方便、灵敏的检测方法,对OSAHS具有临床诊断价值,适合基层医院推广应用。     

Nasal pressure recordings to detect obstructive sleep apnea

Obstructive sleep apnea (OSA) is a common disease. Given the costs of in-laboratory polysomnography (PSG), alternative ambulatory methods for accurate diagnosis are desirable. The objective of this study was to evaluate the performance of a simple device (SleepCheck) to identify patients with sleep apnea. A total of 30 consecutive patients with suspected OSA syndrome referred to the sleep clinic were prospectively evaluated with standard PSG and SleepCheck simultaneously during an in-laboratory, supervised full-night diagnostic study. The PSG apnea and hypopnea index (AHI) was evaluated according to standard criteria, and SleepCheck assessed the respiratory disturbance index (RDI) based on nasal cannula pressure fluctuations. Compared to the full-night PSG, SleepCheck systematically overscored respiratory events (the mean difference between SleepCheck RDI and PSG AHI was 27.4±13.3 events per hour). This overscoring was in part related to normal physiologic decreases in flow during rapid eye movement sleep or after an arousal. However, there was reasonable correlation between AHI and RDI (r=0.805). Receiver operating characteristic curves with threshold values of AHI of 10 and 20/h demonstrated areas under the curves (AUCs) of 0.915 and 0.910, respectively. Optimum combinations of sensitivity and specificity for these thresholds were calculated as 86.4/75.0 and 88.9/81.0, respectively. Overall, the SleepCheck substantially overscored apneas and hypopneas in patients with suspected OSA. However, after correction of the bias, the SleepCheck had reasonable accuracy with an AUC, sensitivity, and specificity similar to other ambulatory type 4 devices currently available.This study was conducted at the Sleep Laboratory and Division of Orthodontics, The University of British Columbia, Canada     

自动持续气道正压系统诊断睡眠呼吸暂停综合征的临床评价

目的评价简易的自动持续气道正压系统（AutoSet）在临床上诊断睡眠呼吸暂停综合征（SAS）的应用价值。方法120例患者同时进行AutoSet和多导睡眠图（PSG）的监测研究,比较两种方法的呼吸暂停指数（AI）及呼吸暂停＋低通气指数（AHI）。结果两种方法的AI及AHI呈显著相关（r＝0．88,P＜0．001;r＝0．93,P＜0．001）。AutoSet上显示的呼吸紊乱指数（RII）与PSG的觉醒指数（Ai）呈显著相关（r＝0．72,P＜0．001）。如以AHI≥5、10、15、20次／小时为诊断标准,AntoSet诊断SAS的敏感性分别为94％、92％、91％、91％,特异性分别为80％、85％、92％、91％。结论AutoSet系统是一个诊断SAS敏感和有价值的工具,尤其对AHI≥30次／小时的SAS患者,其诊断价值更大,但对于轻、中度患者有一定的误差。     

阻塞性睡眠呼吸暂停低通气综合征患者睡眠结构紊乱与肝酶水平升高的相关性研究

目的 研究阻塞性睡眠呼吸暂停低通气综合征(OSAHS)患者的睡眠结构紊乱及其对肝酶水平的影响。方法 研究2010-2013年苏州大学附属第二医院神经内科收治的多导睡眠监测(PSG)确诊的OSAHS组和对照组的睡眠参数,且根据睡眠呼吸暂停和(或)低通气指数(AHI)将OSAHS组分为轻、中、重度三组,比较各组间肝酶及睡眠结构的变化,并将肝酶水平与睡眠结构指标进行相关性分析。结果 与对照组比较,OSAHS组患者的AHI、呼吸相关微觉醒指数、最长呼吸暂停时间、睡眠时间1+2期比例及血清丙氨酸转氨酶(ATL)、天冬氨酸转氨酶(ASL)、血清γ-谷氨酰转肽酶(γ-GGT)水平显著增高,最低血氧饱和度(L-SaO2)及慢波睡眠比例显著降低(均P<0.05)。OSAHS组各亚组间比较,AHI差异有统计学意义;与重度亚组比较,轻、中度亚组呼吸相关微觉醒指数、最长呼吸暂停时间、睡眠时间1+2期比例、慢波睡眠比例及血清ATL、ASL的变化均有统计学意义;与重度亚组比较,轻度亚组的血清γ-GGT显著升高(P<0.05)。偏相关分析显示,血清ALT、AST与睡眠1+2期比例呈正相关,血清ALT与慢波睡眠比例呈负相关,与呼吸睡眠微觉醒呈正相关(均P<0.05)。结论 OSAHS患者存在睡眠结构紊乱及肝脏损伤,其肝酶水平的升高与睡眠结构紊乱有关。     

Sleep disordered breathing analysis in a general population using standard pulse oximeter signals

Objectives

Obstructive sleep apnea reported as the apnea–hypopnea index (AHI) is usually measured in sleep laboratories using a high number of electrodes connected to the patient’s body. In this study, we examined the use of a standard pulse oximeter system with an automated analysis based on the photoplethysmograph (PPG) signal for the diagnosis of sleep disordered breathing. Using a standard and simple device with high accuracy might provide a convenient diagnostic or screening solution for patient evaluation at home or in other out of center testing environments.

Methods

The study included 140 consecutive patients that were referred routinely to a sleep laboratory [SleepMed Inc.] for the diagnosis of sleep disordered breathing. Each patient underwent an overnight polysomnography (PSG) study according to AASM guidelines in an AASM-accredited sleep laboratory. The automatic analysis is based on photoplethysmographic and saturation signals only. Those two signals were recorded for the entire night as part of the full overnight PSG sleep study. The AHI calculated from the PPG analysis is compared to the AHI calculated from the manual scoring gold standard full PSG.

Results

The AHI and total respiratory events measured by the pulse oximeter analysis correlated very well with the corresponding results obtained by the gold standard full PSG. The sensitivity and specificity of AHI = or > 5 and 15 levels measured by the analysis are both above 90 %. The sensitivity and positive predictive value for the detection of respiratory event are both above 84 %.

Conclusions

The tested system in this study yielded an acceptable result of sleep disordered breathing compared to the gold standard PSG in patients with moderate to severe sleep apnea. Accordingly and given the convenience and simplicity of the standard pulse oximeter device, the new system can be considered suitable for home and ambulatory diagnosis or screening of sleep disordered breathing patients.     

Clinical diagnosis of sleep apnea based on single night of polysomnography vs. two nights of polysomnography

Purpose  The purpose of this study was to investigate apnea–hypopnea index (AHI) across two polysomnographies (PSGs) to examine AHI variability and impact on clinical diagnosis. Materials and methods  Two-night PSGs of 193 sleep clinic patients were reviewed, and the AHI variability was analyzed. Anonymized records from five patients with significant night-to-night AHI variability were used in this study: the two-night PSGs from two patients were represented as four individual PSGs; the two-night PSG for two others were represented as being obtained from two different sleep clinics; the last patient’s PSG was shown as a two-night study. Twenty-two sleep experts attending the Associated Professional Sleep Societies meeting were recruited to make diagnoses based on the PSGs. They were told that the PSGs were from seven patients: four with single-night PSG; two with two PSGs, each one from a different clinic; and one patient with a two-night PSG. Results  Twenty-one percent of the 193 sleep clinic patients had a nightly PSG AHI variability of greater than 5. Forty-eight percent of all patients had a significantly higher AHI on the first night, and 41% had a significantly higher AHI on the second night. Using an AHI > 15 diagnostic criteria, sleep apnea would have been undetected in 20% (n = 39) of patients due to low AHI on one night. Furthermore, 13% of all patients had a more severe sleep apnea classification based on the second night of PSG. For the seven cases, 27–36% of sleep experts failed to identify sleep apnea especially when presented with the PSG containing the lower AHI. Incidences of missed sleep apnea diagnoses were reduced to 15–18% when information from two PSGs was presented to the sleep experts. Conclusions  Utilizing a large patient population, this study supports the significant night-to-night variability in PSG respiratory variables. Identification of sleep apnea in some patients is reduced when sleep experts are provided with only one PSG recording. The clinical implication is that about 13% of sleep clinic patients might benefit from a second night of PSG. Disclosure statement: This study did not receive external funding.     

The accuracy of autotitrating CPAP-determined residual apnea–hypopnea index

Purpose

Autotitrating continuous positive airway pressure (auto-CPAP) devices not only titrate CPAP pressures but also measure residual respiratory events. The aim of the present study was to determine the accuracy of auto-CPAP-derived residual apnea–hypopnea index (AHI).

Methods

We studied 137 consecutive patients (72.3% men) with obstructive sleep apnea from January 2008 to December 2010 who underwent in-laboratory overnight polysomnography (PSG) using auto-CPAP. We excluded patients with comorbidities like congestive heart disease, chronic obstructive pulmonary disease, or hypoventilation syndromes and patients with central sleep apnea. Residual AHI obtained from the auto-CPAP device by smart card (CPAP-AHI) was compared simultaneously with AHI from an overnight PSG on auto-CPAP (PSG-AHI) using Bland–Altman analysis and Wilcoxon signed-rank test.

Results

The mean AHI on the diagnostic study was 45.08?±?1.8. During the titration, auto-CPAP markedly suppressed the respiratory events (PSG-AHI, 3.40?±?0.20). On the other hand, CPAP-AHI was 3.35?±?0.17. Bland–Altman analysis showed good agreement between auto-CPAP-AHI and PSG-AHI (AHI mean difference of 0.05, and the limits of agreement for the AHI were from +4.9 to ?4.8). Two methods have also been compared with paired samples t test and no statistically significant difference was found (p?>?0.05).

Conclusion

Auto-CPAP can identify residual respiratory events equivalent to the use of PSG in a selected population.     

Pulse transit time improves detection of sleep respiratory events and microarousals in children

OBJECTIVES: To evaluate the additional information provided by pulse transit time (PTT), a noninvasive tool, when using during polysomnography for the diagnosis of sleep breathing disorders in a pediatric population. MAIN FINDINGS: Respiratory and microarousals events were scored twice. The first scoring was performed using nasal pressure, thermistors, thoracic and abdominal movements, and oxygen saturation. The second scoring, blinded to the first scoring, was performed using PTT in combination with all the other signals. Microarousals were scored once visually on the EEG trace (cortical arousals [CAs]) and once using the PTT signal (autonomic arousals [AAs]) blinded to EEG. For the whole group of 16 children studied (mean age, 9.5 years), there was no significant difference between the respiratory disturbance index (RDI) with or without PTT analysis (22.4 +/- 13.5/h vs 20.4 +/- 14.3/h; not significant [mean +/- SD]). Among the children exhibiting a "without PTT" RDI < 30/h, 5 of 12 children (41.66%) showed a clinically significant >/= 5/h increase in RDI when using PTT. AAs detected by PTT were significantly more frequent than CAs during rapid eye movement (REM) sleep (7.4 +/- 3.9/h vs 3.2 +/- 2.3/h; p < 0.001) and slow wave sleep (SWS) [6.0 +/- 4.3/h vs 0.6 +/- 0.5/h; p < 0.0001]. CONCLUSIONS: The quantification of respiratory effort using PTT improves the detection of respiratory events in children. The detection of microarousals is improved particularly in REM and SWS.     

睡眠呼吸暂停综合征患者持续气道正压通气治疗前后微觉醒的变化及意义

目的探讨微觉醒的发生机制、临床意义及其在睡眠呼吸障碍性疾患诊断治疗中的应用价值。方法270例打鼾者均按国际标准方法进行多导睡眠呼吸监测（PSG）,据此计算睡眠呼吸暂停低通气指数(AHI)、睡眠潜伏期(SL)、每小时氧减饱和度4%以上的次数(ODI4)及每小时微觉醒的次数(MAI)。其中28例患者应用持续气道正压通气(CPAP)同时复查PSG,在治疗前后均填写Epworth睡眠问卷(ESS)以评价患者嗜睡的改善程度。结果270例鼾症患者中,247例符合睡眠呼吸暂停低通气综合征(SAHS)的诊断,其AHI、ODI4、MAI及SL平均值分别为(43±27)次/h,(44±23)次/h,(29±16)次/h,(12±17)分。AHI与MAI,ODI4与MAI均呈正相关(r均为0.38,P均<0.001)。MAI与SL显著负相关(r=-0.15,P=0.02),AHI与SL、ODI4与SL均无相关性(r分别为-0.09,-0.02,P均>0.1)。经CPAP治疗,28例患者的呼吸暂停基本消失,ODI4由(48±25)次/h降至(4±9)次/h,MAI由(27±18)次/h减至(15±9)次/h,主观(ESS)及客观(SL)评价均显示白天嗜睡改善。结论应用专门的计算机软件辅助分析SAHS患者睡眠状态下的脑电变化,可以判读最短持续时间达3秒的微觉醒。MAI可以作为白天嗜睡的重要指标,在SAHS诊断和CPAP疗效判断方面与AHI具有互补性。     

Validation of the MediByte? type 3 portable monitor compared with polysomnography for screening of obstructive sleep apnea

BACKGROUND:

Portable monitors are increasingly being used as a diagnostic screening tool for obstructive sleep apnea (OSA), and in-laboratory validation of these devices with polysomnography (PSG) is required.

OBJECTIVE:

To assess the reliability of the MediByte (Braebon Medical Corporation, Canada) type 3 screening device compared with overnight PSG.

METHODS:

To cover a range of OSA severity, a consecutive series of patients wore the screening device while simultaneously undergoing PSG. Data acquired from the screener and PSG were blinded and scored separately. The number of apneas and hypopneas per hour were calculated using recording time (respiratory disturbance index [RDI]) for the MediByte device, and sleep time (apnea-hypopnea index [AHI]) for PSG.

RESULTS:

Data from 73 patients with a mean age of 53 years and body mass index of 32.2 kg/m² showed high measurement association between the RDI and AHI, with a Pearson correlation of 0.92, accounting for 85% of the variance. Based on Bland-Altman measurement agreement, the mean difference between the RDI and AHI (−5.9±11.2 events/h) indicated screener under-reporting. For an AHI of greater than 15 events/h, the sensitivity and specificity of the screener was 80% and 97%, respectively; for an AHI of greater than 30 events/h, the positive predictive value was 100%, while the negative predictive value was 88%.

CONCLUSION:

The MediByte device accurately identified patients without OSA and had a high sensitivity for moderate-to-severe OSA.     

Comparison of esophageal pressure with pulse transit time as a measure of respiratory effort for scoring obstructive nonapneic respiratory events

Obstructive nonapneic respiratory events (ONAREs) are much more difficult to detect and classify than apneas unless sensitive measures of respiratory effort and airflow are employed. The aim of this study was to compare two measures of respiratory effort, esophageal pressure monitoring (Pes) and pulse transit time (PTT), for scoring of ONAREs by visual analysis. Nine men (age 49 +/- 10 yr) with mild to moderate sleep apnea syndrome (AHI of 25.1 +/- 10. 8/h) were studied and 340 ONAREs (hypopneas and upper airway resistance episodes) were randomly selected for scoring by two experienced observers. Each observer blindly scored each ONARE twice (once with Pes and once with PTT) with a concurrent pneumotachography trace available for airflow quantification. This permitted the respiratory events scored with PTT to be compared with those scored with Pes, and in addition interobserver variability could be assessed for each signal. Even though standard criteria were used for scoring, there was significant interobserver variability for both Pes (29.7%) and PTT (37.1%). Taking those events for which there was agreement between the observers, PTT had a sensitivity of 79.9% and a positive predictive value of 91.2% (using Pes as the gold standard). In those ONAREs for which there was agreement between the two observers there was a larger percentage reduction in airflow compared to ONAREs that did not concur (51 versus 30.3%, p < 0.001), a larger increase in respiratory effort as assessed by PTT (slope of PTT: 23.1 versus 14. 3 arbitrary units, p < 0.01), and a higher incidence in autonomic microarousals detected with PTT (90 versus 45% of ONAREs, p < 0.006). Subtle respiratory events are more difficult to detect than apneas or frank hypopneas. When comparing PTT with esophageal pressure in detecting those events the sensitivity of PTT is good but limited when the reduction in airflow, the increase in respiratory effort, or the arousal reaction is the less clear. However, PTT appears to be a good noninvasive alternative to Pes in the detection of nonapneic obstructive respiratory events, and its ability to detect autonomic arousal gives this physiological signal added clinical usefulness.