Prediction of sleep-disordered breathing by unattended overnight oximetry

Between January 1994 and July 1997, 793 patients suspected of having sleep-disordered breathing had unattended overnight oximetry in their homes followed by laboratory polysomnography. From the oximetry data we extracted cumulative percentage time at SaO2 < 90% (CT90) and a saturation variability index (delta Index, the sum of the differences between successive readings divided by the number of readings - 1). CT90 was weakly correlated with polysomnographic apnea/hypopnea index (AHI). (Spearman rho = 0.36, P < 0.0001) and with delta Index (rho = 0.71, P < 0.0001). delta Index was more closely correlated with AHI (rho = 0.59, P < 0.0001). In a multivariate model, only delta Index was significantly related to AHI, the relationship being AHI = 18.8 delta Index + 7.7. The 95% CI for the coefficient were 16.2, 21.4, and for the constant were 5.8, 9.7. The sensitivity of a delta Index cut-off of 0.4 for the detection of AHI > or = 15 was 88%, for detection of AHI > or = 20 was 90% and for the detection of AHI > or = 25 was 91%. The specificity of delta Index > or = 0.4 for AHI > or = 15 was 40%. In 113 further patients, oximetry was performed simultaneously with laboratory polysomnography. Under these circumstances delta Index was more closely correlated with AHI (rho = 0.74, P < 0.0001), as was CT90 (rho = 0.58, P < 0.0001). Sensitivity of delta Index > or = 0.4 for detection of AHI > or = 15 was not improved at 88%, but specificity was better at 70%. We concluded that oximetry using a saturation variability index is sensitive but nonspecific for the detection of obstructive sleep apnea, and that few false negative but a significant proportion of false positive results arise from night-to-night variability.     

Validation of a new system of tracheal sound analysis for the diagnosis of sleep apnea-hypopnea syndrome

STUDY OBJECTIVES: To evaluate the validity of a novel method of using tracheal sound analysis for the diagnosis of sleep apnea-hypopnea syndrome. DESIGN: Retrospective analysis in consecutive patients. SETTING: A sleep clinic in a general hospital. PATIENTS: A total of 383 patients who were referred for suspected sleep apnea-hypopnea syndrome and underwent diagnostic polysomnography with sufficient quality. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Ordinary polysomnography with simultaneous tracheal sound recording was performed. The apnea-hypopnea index (AHI) was calculated as the number of apnea and hypopnea events per hour of sleep. Tracheal sounds were digitized and recorded as power spectra. An automated computer program detected transient falls (TS-dip) in the time series of moving average of the logarithmic power of tracheal sound. We defined the tracheal sound-respiratory disturbance index (TS-RDI) as the number of TS-dips per hour of examination. We also calculated the oxygen desaturation index (the number of SaO2 dips of at least 4% per hour of examination). The TS-RDI highly correlated with AHI (r = 0.93). The mean (+/- SD) difference between the TS-RDI and AHI was -8.4 +/- 10.4. The diagnostic sensitivity and specificity of the TS-RDI when the same cutoff value was used as for AHI were 93% and 67% for the AHI cutoff value of 5 and 79% and 95% for the AHI cutoff value of 15. The agreement between the TS-RDI and AHI was better than that between the oxygen desaturation index and AHI. CONCLUSIONS: The fully automated tracheal sound analysis demonstrated a relatively high performance in the diagnosis of sleep apnea-hypopnea syndrome. We think that this method is useful for the portable monitoring of sleep apnea-hypopnea syndrome.     

Accuracy of oximetry with thermistor (OxiFlow) for diagnosis of obstructive sleep apnea and hypopnea

OBJECTIVES: To evaluate the diagnostic accuracy for obstructive sleep apnea and hypopnea (OSAH) of the OxiFlow (OF) device which combines oximetry with recording of thermistor airflow. DESIGN & SETTING: Patients scheduled for overnight diagnostic polysomnography (PSG) were studied with OF either simultaneously during laboratory PSG (L-OF, n=86), at home on a separate night (H-OF, n=66), or both (n=55). PATIENTS: 97 patients with suspected OSAH, of whom 40 had OSAH defined as an apnea-hypopnea index (AHI) of more than 15 events per hour of sleep on PSG. INTERVENTIONS: NA. MEASUREMENTS & RESULTS: The automated respiratory disturbance index (RDI) generated by the OF software considerably underestimated the AHI by PSG for both L-OF and H-OF. Altering the parameters for hypopnea identification by the software did not improve this. Visual inspection of the computerized OF tracings added considerable diagnostic information, but a manual count of RDI during visual review overestimated AHI. For the identification of cases vs. non-cases of OSAH, receiver operating characteristic area-under-the-curve statistics ranged from 0.77-0.90 for L-OF and from 0.71-0.77 for H-OF. Combining automated analysis with subsequent visual inspection of OF tracings yielded an overall sensitivity of 86% and specificity of 74% for the diagnosis of OSAH during H-OF recordings. Analysis of potential technician time saved indicated a benefit from the use of OF. CONCLUSIONS: OF has diagnostic utility for the identification of OSAH. However, because of hardware and software limitations, it is unclear whether this device is superior to oximetry alone.     

A novel adaptive wrist actigraphy algorithm for sleep-wake assessment in sleep apnea patients

STUDY OBJECTIVES: Current actigraphic algorithms are relatively less accurate in detecting sleep and wake in sleep apnea patients than in people without sleep apnea. In the current study, we attempted to validate a novel automatic algorithm, which was developed for actigraphic studies in normal subjects and patients with obstructive sleep apnea by comparing it on an epoch-by-epoch basis to standard polysomnography. DESIGN: Prospective cohort study. SETTING: Multicenter, university hospital, sleep laboratories. PARTICIPANTS: A total of 228 subjects from 3 different sleep centers (Skara, Boston, Haifa) participated. INTERVENTION AND MEASUREMENTS: Simultaneous recording of polysomnography and Watch_PAT100, an ambulatory device that contains a built-in actigraph. The automatic sleep/wake algorithm is based on both the quantification of motion (magnitude and duration) and the various periodic movement patterns, such as those occurring in patients with moderate to severe obstructive sleep apnea. RESULTS: The overall sensitivity and specificity to identify sleep was 89% and 69%, respectively. The agreement ranged from 86% in the normal subjects to 86%, 84%, and 80% in the patients with mild, moderate, and severe obstructive sleep apnea, respectively. There was a tight agreement between actigraphy and polysomnography in determining sleep efficiency (78.4 +/- 9.9 vs 78.8 +/- 13.4%), total sleep time (690 +/- 152 vs 690 +/- 154 epochs), and sleep latency (56.8 +/- 31.4 vs 43.3 +/- 45.4 epochs). While for most individuals the difference between the polysomnography and actigraphy was relatively small, for some there was a substantial disagreement. CONCLUSIONS: We conclude that this actigraphy algorithm provides a reasonably accurate estimation of sleep and wakefulness in normal subjects and patients with obstructive sleep apnea on an epoch-by-epoch basis. This simple method for assessment of total sleep time may provide a useful tool for the accurate quantification of obstructive sleep apnea in the home environment.     

Improving diagnostic ability of blood oxygen saturation from overnight pulse oximetry in obstructive sleep apnea detection by means of central tendency measure

OBJECTIVES: Nocturnal pulse oximetry is a widely used alternative to polysomnography (PSG) in screening for obstructive sleep apnea (OSA) syndrome. Several oximetric indexes have been derived from nocturnal blood oxygen saturation (SaO2). However, they suffer from several limitations. The present study is focused on the usefulness of nonlinear methods in deriving new measures from oximetry signals to improve the diagnostic accuracy of classical oximetric indexes. Specifically, we assessed the validity of central tendency measure (CTM) as a screening test for OSA in patients clinically suspected of suffering from this disease. MATERIALS AND METHODS: We studied 187 subjects suspected of suffering from OSA referred to the sleep unit. A nocturnal pulse oximetry study was applied simultaneously to a conventional PSG. Three different index groups were compared. The first one was composed by classical indexes provided by our oximeter: oxygen desaturation indexes (ODIs) and cumulative time spent below a saturation of 90% (CT90). The second one was formed by indexes derived from a nonlinear method previously studied by our group: approximate entropy (ApEn). The last one was composed by indexes derived from a CTM analysis. RESULTS: For a radius in the scatter plot equal to 1, CTM values corresponding to OSA positive patients (0.30+/-0.20, mean+/-S.D.) were significantly lower (p<0.001) than those values from OSA negative subjects (0.71+/-0.18, mean+/-S.D.). CTM was significantly correlated with classical indexes and indexes from ApEn analysis. CTM provided the highest correlation with the apnea-hipopnea index AHI (r=-0.74, p<0.0001). Moreover, it reached the best results from the receiver operating characteristics (ROC) curve analysis, with 90.1% sensitivity, 82.9% specificity, 88.5% positive predictive value, 85.1% negative predictive value, 87.2% accuracy and an area under the ROC curve of 0.924. Finally, the AHI derived from the quadratic regression curve for the CTM showed better agreement with the AHI from PSG than classical and ApEn derived indexes. CONCLUSION: The results suggest that CTM could improve the diagnostic ability of SaO2 signals recorded from portable monitoring. CTM could be a useful tool for physicians in the diagnosis of OSA syndrome.     

穿戴式呼吸感应体积描记用于睡眠呼吸事件检测

可穿戴式呼吸感应体积描记(背心式RIP)系统是我们根据呼吸感应体积描记技术的基本原理研发的一种可穿戴、低负荷的呼吸监测系统.在实现通气量无创测量的基础上,我们将该系统用于睡眠期呼吸事件检测,将该系统与多导睡眠图仪(PSG)对9例疑似睡眠呼吸暂停低通气综合症(SAHS)病人和7名健康男性志愿者进行同步对照检测与分析.通过对比实验,根据背心式RIP系统发生呼吸事件的特征性变化,提出了背心式RIP系统判别呼吸事件的规则.依据该规则,所有经背心式RIP系统诊断为SAHS患者的结果与PSG的诊断结果完全一致,背心式RIP系统检测呼吸事件的敏感性为97.8%,特异性为95.8%,实验结果表明背心式RIP系统能够可靠地检测出睡眠呼吸事件.由于其低生理、心理负荷特性,不需要佩带口鼻气流传感器,可用于家庭环境下、自然睡眠过程的睡眠呼吸紊乱性疾病的诊断.     

基于LSTM-CNN的睡眠呼吸暂停与低通气事件实时检测算法研究

睡眠呼吸暂停与低通气综合征(SAHS)严重影响睡眠质量, 是一种潜在的致死性呼吸疾病。为了兼顾对睡眠呼吸暂停与低通气(AH)事件检测的准确率与时间分辨率, 提出一种长短时记忆-卷积神经网络(LSTM-CNN)方法, 实现对AH事件的精准预测;同时基于事件检测结果, 提出一种呼吸紊乱指数(AHI)估计方法, 进而实现对SAHS严重程度的定量评估。选取美国国家心肺血液研究所睡眠健康数据库中54名受试者的腹部位移信号对LSTM-CNN算法进行测试。对于处理得到的超过90万数据片段, 正确率、敏感度、特异度分别为88.6%、88.2%、88.7%;54名被试的AHI预测结果与多导睡眠图(PSG)标注结果相比, 皮尔逊相关指数达到0.98;观察SAHS严重程度诊断结果, kappa系数达到0.95。结果表明, 所提出的方法不仅可以实现对AH事件的高精度检测, 而且可以对AHI指数与SAHS严重程度做出准确估计, 有望用于PSG检测之前SAHS的初步诊断以及成为家用SAHS长期监护工具。     

Utility of actigraphy in the diagnosis of obstructive sleep apnea

STUDY OBJECTIVES: To determine whether adding actimetry to simplified polygraphy (respiratory-parameter monitoring without neurophysiologic variable recording) improves apnea-hypopnea index (AHI) evaluation as compared to simplified polygraphy alone. DESIGN: Comparison of AHI values obtained by all-night polysomnography and by simplified polygraphy with and without actimetry. SETTING: A teaching-hospital sleep laboratory in Garches, France. PATIENTS: 20 adults with suspected obstructive sleep apnea syndrome (OSAS). MEASUREMENTS AND RESULTS: Data were analyzed by two scorers working independently. AHI was calculated as the number of apneas and hypopneas per hour of sleep time (polysomnography: AHI-pg), per hour of time in bed (simplified polygraphy: AHI-tib), and per hour of actimetry-estimated total sleep time (AHI-act). AHI-pg showed that 12 patients had OSAS (AHI>10), which was severe (AHI > or =30) in eight. AHI-act was more closely correlated to AHI-pg (r=0.976) than was AHI-tib (r=0.940). According to the Bland and Altman method, AHI-tib underestimated the AHI in two patients and AHI-act overestimated the AHI in one patient. For the diagnosis of severe OSAS, sensitivity and negative predictive value were 50% and 75% with AHI-tib as compared to 88% and 92.5% with AHI-act. CONCLUSIONS: Actimetry, when added to simplified polygraphy, may assist in the diagnosis of OSAS.     

Ambulatory detection of sleep apnea using a non‐contact biomotion sensor

The high prevalence of obstructive sleep apnea has led to increasing interest in ambulatory diagnosis. The SleepMinder? (SM) is a novel non‐contact device that employs radiofrequency wave technology to assess the breathing pattern, and thereby estimate obstructive sleep apnea severity. We assessed the performance of SleepMinder? in the home diagnosis of obstructive sleep apnea. One‐hundred and twenty‐two subjects were prospectively recruited in two protocols, one from an unselected sleep clinic cohort (n = 67, mean age 51 years) and a second from a hypertension clinic cohort (n = 55, mean age 58 years). All underwent 7 consecutive nights of home monitoring (SM_HOME) with the SleepMinder? as well as inpatient‐attended polysomnography in the sleep clinic cohort or cardiorespiratory polygraphy in the hypertension clinic cohort with simultaneous SleepMinder? recordings (SM_LAB). In the sleep clinic cohort, median SM_HOME apnea–hypopnea index correlated significantly with polysomnography apnea–hypopnea index (r = .68; p < .001), and in the hypertension clinic cohort with polygraphy apnea–hypopnea index (r = .7; p < .001). The median SM_HOME performance against polysomnography in the sleep clinic cohort showed a sensitivity and specificity of 72% and 94% for apnea–hypopnea index ≥ 15. Device performance was inferior in females. In the hypertension clinic cohort, SM_HOME showed a 50% sensitivity and 72% specificity for apnea–hypopnea index ≥ 15. SleepMinder? classified 92% of cases correctly or within one severity class of the polygraphy classification. Night‐to‐night variability in home testing was relatively high, especially at lower apnea–hypopnea index levels. We conclude that the SleepMinder? device provides a useful ambulatory screening tool, especially in a population suspected of obstructive sleep apnea, and is most accurate in moderate–severe obstructive sleep apnea.     

Utility of home oximetry as a screening test for patients with moderate to severe symptoms of obstructive sleep apnea

OBJECTIVE: To determine the value of home oximetry as a screening test in patients with moderate to severe symptoms of obstructive sleep apnea (OSA). DESIGN: Retrospective, observational study. SETTING: The Sleep Unit of a tertiary referral, university hospital. PATIENTS: 116 patients referred for evaluation of moderate to severe symptoms of OSA in which both home oximetry and polysomnography (PSG) were performed. INTERVENTIONS: NA. RESULTS: Three numerical oximetry indices were evaluated: average of desaturations > or =4% and average of resaturations > or =3% per hour of analysis time (DI4% and RI3%, respectively); and cumulative percentages of time spent at saturations below 90% (CT90%). A qualitative assessment was also performed. Oximetry indices were compared with apnea/hypopnea index (AHI) by simple linear regression and Bland-Altman analyses. Optimal cut-off points, in terms of sensitivity and specificity, for the oximetry indices were searched using ROC analysis, at an AHI threshold of > or =10. The correlation between AHI and the desaturation indices was r = 0.50 for CT90%, r = 0.60 for DI4%, and r = 0.58 for RI3%. No bias was found between PSG and oximetry indices in Bland-Altman plots. Neither the numerical indices nor the qualitative analysis achieved an adequate (>0.8) area under the ROC curve. A CT90% <0.79 excluded OSA with 84% sensitivity. A DI4% > or =31.4 or a RI3% > or =40.5 diagnosed OSA with 97% specificity. Using these values, 38% of the patients would have been correctly classified by oximetry alone, 10% would have been incorrectly classified, and 50% could not have been classified with certainty. Eleven (15%) OSA patients would have been missed by oximetry. CONCLUSIONS: Correlation between home oximetry and PSG was not high. Oximetry was more useful to confirm than to exclude OSA in our study. Qualitative assessment was not better than numerical analysis. The greatest value of oximetry in this setting seems to be as a tool to rapidly recognize and treat more severe OSA patients in waiting list for PSG.     

Associations of Moderate to Severe Asthma with Obstructive Sleep Apnea

Purpose

This study aimed to evaluate the correlation between associating factors of moderate to severe asthma with obstructive sleep apnea (OSA).

Materials and Methods

One hundred and sixty-seven patients who visited the pulmonary and sleep clinic in Severance Hospital presenting with symptoms of sleep-disordered breathing were evaluated. All subjects were screened with ApneaLink. Thirty-two subjects with a high likelihood of having OSA were assessed with full polysomnography (PSG).

Results

The mean age was 58.8±12.0 years and 58.7% of subjects were male. The mean ApneaLink apnea-hypopnea index (AHI) was 12.7±13.0/hr. The mean ApneaLink AHI for the 32 selected high risk patients of OSA was 22.3±13.2/hr, which was lower than the sleep laboratory-based PSG AHI of 39.1±20.5/hr. When OSA was defined at an ApneaLink AHI ≥5/hr, the positive correlating factors for OSA were age, male gender, and moderate to severe asthma.

Conclusion

Moderate to severe asthma showed strong correlation with OSA when defined at an ApneaLink AHI ≥5/hr.     

Added value of a mandible movement automated analysis in the screening of obstructive sleep apnea

In‐laboratory polysomnography is the ‘gold standard’ for diagnosing obstructive sleep apnea syndrome, but is time consuming and costly, with long waiting lists in many sleep laboratories. Therefore, the search for alternative methods to detect respiratory events is growing. In this prospective study, we compared attended polysomnography with two other methods, with or without mandible movement automated analysis provided by a distance‐meter and added to airflow and oxygen saturation analysis for the detection of respiratory events. The mandible movement automated analysis allows for the detection of salient mandible movement, which is a surrogate for arousal. All parameters were recorded simultaneously in 570 consecutive patients (M/F: 381/189; age: 50 ± 14 years; body mass index: 29 ± 7 kg m^?2) visiting a sleep laboratory. The most frequent main diagnoses were: obstructive sleep apnea (344; 60%); insomnia/anxiety/depression (75; 13%); and upper airway resistance syndrome (25; 4%). The correlation between polysomnography and the method with mandible movement automated analysis was excellent (r: 0.95; P < 0.001). Accuracy characteristics of the methods showed a statistical improvement in sensitivity and negative predictive value with the addition of mandible movement automated analysis. This was true for different diagnostic thresholds of obstructive sleep severity, with an excellent efficiency for moderate to severe index (apnea–hypopnea index ≥15 h^?1). A Bland & Altman plot corroborated the analysis. The addition of mandible movement automated analysis significantly improves the respiratory index calculation accuracy compared with an airflow and oxygen saturation analysis. This is an attractive method for the screening of obstructive sleep apnea syndrome, increasing the ability to detect hypopnea thanks to the salient mandible movement as a marker of arousals.     

Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry

Detection of desaturations on the pulse oximetry signal is of great importance for the diagnosis of sleep apneas. Using the counting of desaturations, an index can be built to help in the diagnosis of severe cases of obstructive sleep apnea–hypopnea syndrome. It is important to have automatic detection methods that allows the screening for this syndrome, reducing the need of the expensive polysomnography based studies. In this paper a novel recognition method based on the empirical mode decomposition of the pulse oximetry signal is proposed. The desaturations produce a very specific wave pattern that is extracted in the modes of the decomposition. Using this information, a detector based on properly selected thresholds and a set of simple rules is built. The oxygen desaturation index constructed from these detections produces a detector for obstructive sleep apnea–hypopnea syndrome with high sensitivity (0.838) and specificity (0.855) and yields better results than standard desaturation detection approaches.     

Comparison between a Single-Channel Nasal Airflow Device and Oximetry for the Diagnosis of Obstructive Sleep Apnea

Rationale:

The most common single channel devices used for obstructive sleep apnea (OSA) screening are nasal airflow and oximetry. No studies have directly compared their role in diagnosing OSA at home.

Study Objectives:

To prospectively compare the diagnostic utility of home-based nasal airflow and oximetry to attended polysomnography (PSG) and to assess the diagnostic value of adding oximetry to nasal airflow for OSA.

Design:

Cross-sectional study

Setting:

Laboratory and home

Participants:

Sleep clinic patients with suspected OSA.

Interventions:

All patients had laboratory PSG and 2 sets of 3 consecutive nights on each device; nasal airflow (Flow Wizard, DiagnoseIT, Australia) and oximetry (Radical Set, Masimo, USA) at home in random order.

Results:

Ninety-eight of the 105 patients enrolled completed home monitoring. The accuracy of nasal airflow respiratory disturbance index (NF RDI) was not different from oximetry (ODI 3%) for diagnosing OSA (area under the ROC curve (AUC) difference, 0.04; 95% CI of difference −0.05 to 0.12; P = 0.43) over 3 nights of at-home recording. The accuracy of NF RDI was higher after 3 nights compared to one night (AUC difference, 0.05; 95% CI of difference, 0.01 to 0.08; P = 0.04). Addition of oximetry to nasal airflow did not increase the accuracy for predicting OSA compared to nasal airflow alone (P > 0.1).

Conclusions:

Nasal flow and oximetry have equivalent accuracy for diagnosing OSA in the home setting. Choice of device for home screening of sleep apnea may depend on logistical and service delivery issues.

Citation:

Makarie Rofail L; Wong KKH; Unger G; Marks GB; Grunstein RR. Comparison between a single-channel nasal airflow device and oximetry for the diagnosis of obstructive sleep apnea. SLEEP 2010;33(8):1106-1114.     

Determining optimal sleep position in patients with positional sleep-disordered breathing using response surface analysis

A lateral position (LP) during sleep is effective in reducing sleep disorder symptoms in mild or moderate sleep apnea patients. However, the effect of head and shoulder posture in LP on reducing sleep disorders has not been reported. In this study, effective sleeping positions and a combination of sleep position determinants were evaluated with respect to their ability to reduce snoring and apnea. The positions evaluated included the following: cervical vertebrae support with head tilting (CVS-HT), scapula support (SS), and LP. A central composite design was applied for response surface analysis (RSA). Sixteen patients with mild or moderate positional sleep apnea and snoring who underwent polysomnography for two nights were evaluated. Based on an estimated RSA equation, LP (with a rotation of at least 30°) had the most dominant effect [ P  = 0.0057 for snoring rate, P  = 0.0319 for apnea–hypopnea index (AHI)]. In addition, the LP was found to interact with CVS-HT ( P  = 0.0423) for snoring rate and CVS-HT ( P  = 0.0310) and SS ( P  = 0.0265) for AHI. The optimal sleep position reduced mild snoring by more than 80% (i.e. snoring rate in the supine position was <20%) and the snoring rate was approximately zero with a 40° rotation. To achieve at least 80% reduction of AHI, LP and SS should be >30° and/or 20 mm respectively. To determine an effective sleep position, CVS-HT and SS, as well as the degree of the LP, should be concurrently considered in patients with positional sleep apnea or snoring.     

Social inequalities in sleep‐disordered breathing: Evidence from the CoLaus|HypnoLaus study

Sleep‐disordered breathing is a common condition, related to a higher cardiometabolic and neurocognitive risk. The main risk factors for sleep‐disordered breathing include obesity, craniofacial characteristics, male sex and age. However, some studies have suggested that adverse socioeconomic circumstances and lifestyle‐related behaviours such as smoking and alcohol use, may also be risk factors for sleep‐disordered breathing. Here, we investigate the associations between socioeconomic status and sleep‐disordered breathing, as measured by sleep apnea–hypopnea and oxygen desaturation indexes. Furthermore, we assess whether these associations are explained by lifestyle‐related factors (smoking, sedentary behaviour, alcohol use and body mass index [BMI]). We used data from the CoLaus|HypnoLaus study, a population‐based study including 2162 participants from Lausanne (Switzerland). Socioeconomic status was measured through occupation and education. Sleep‐disordered breathing was assessed through polysomnography and measured using the apnea–hypopnea index (AHI: number of apnea/hypopnea events/hr: ≥15/≥30 events), and the ≥3% oxygen desaturation index (ODI: number of oxygen desaturation events/hr: ≥15/≥30 events). Lower occupation and education were associated with higher AHI and ODI (occupation: AHI30, odds ratio (OR) = 1.88, 95% confidence interval (CI) [1.07; 3.31]; ODI30, OR = 2.29, 95% CI [1.19; 4.39]; education: AHI30, OR = 1.21, 95% CI [0.85; 1.72]; ODI30, OR = 1.26, 95% CI [0.83; 1.91]). BMI was associated with socioeconomic status and AHI/ODI, and contributed to the socioeconomic gradient in SDB, with mediation estimates ranging between 43% and 78%. In this Swiss population‐based study, we found that low socioeconomic status is a risk factor for sleep‐disordered breathing, and that these associations are partly explained by BMI. These findings provide a better understanding of the mechanisms underlying social differences in sleep‐disordered breathing and may help implement policies for identifying high‐risk profiles for this disorder.     

The Utility of Three Screening Questionnaires for Obstructive Sleep Apnea in a Sleep Clinic Setting

Purpose

The aim of this study was to determine the diagnostic value of three screening questionnaires in identifying Korean patients at high risk for obstructive sleep apnea (OSA) in a sleep clinic setting in Korea.

Materials and Methods

Data were collected from 592 adult patients with suspected OSA who visited a sleep center. All patients completed the Sleep Apnea of Sleep Disorder Questionnaire (SA-SDQ), the Berlin questionnaire, and the STOP-Bang questionnaire. Estimated OSA risk was compared to a diagnosis of OSA. The sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each questionnaire.

Results

The prevalence of OSA was 83.6% using an apnea-hypopnea index (AHI) ≥5/h and 58.4% for an AHI ≥15/h. The STOP-Bang questionnaire had a high sensitivity (97% for AHI ≥5/h, 98% for AHI ≥15/h), but the specificity was low (19% and 11%, respectively). In contrast, the sensitivity of the SA-SDQ was not high enough (68% for AHI ≥5/h, 74% for AHI ≥15/h) to be useful in a clinical setting, whereas the specificity was relatively good (66% and 61%, respectively). The sensitivity and specificity values of the Berlin questionnaire fell between those of the STOP-Bang questionnaire and the SA-SDQ.

Conclusion

The STOP-Bang questionnaire may be useful for screening OSA in a sleep clinic setting, but its specificity is lower than the acceptable level for this purpose. A new screening questionnaire with a high sensitivity and acceptable specificity is therefore needed in a sleep clinic setting.     

Low leptin concentration may identify heart failure patients with central sleep apnea

Low leptin concentration has been shown to be associated with central sleep apnea in heart failure patients. We hypothesized that low leptin concentration predicts central sleep apnea. Consecutive ambulatory New York Heart Association (NYHA ) classes I–IV heart failure patients were studied prospectively, including measurement of serum leptin, echocardiography and polysomnography. Sleep apnea was defined by type (central/mixed/obstructive) and by apnea–hypopnea index ≥5 by polysomnography. Subjects were divided into four groups by polysomnography: (1) central sleep apnea, (2) mixed apnea, (3) no apnea and (4) obstructive sleep apnea. Fifty‐six subjects were included. Eighteen subjects were diagnosed with central sleep apnea, 15 with mixed apnea, 12 with obstructive apnea and 11 with no sleep apnea. Leptin concentration was significantly lower in central sleep apnea compared to obstructive apnea (8 ± 10.7 ng mL^?1 versus 19.7 ± 14.7 ng mL^?1, P  ? 0.01) or no sleep apnea (8 ± 10.7 ng mL^?1 versus 17.1 ± 8.4 ng mL^?1, P  ? 0.01). Logistic regression showed leptin to be associated independently with central sleep apnea [odds ratio (OR ): 0.19; 95% confidence interval (CI ): 0.06–0.62; area under the curve (AUC ): 0.80, P  < 0.01]. For the detection of central sleep apnea, a cut‐off value for leptin concentration 5 ng mL^?1 yielded a sensitivity of 50% and specificity of 89%. In conclusion, a low leptin concentration may have utility for the screening of heart failure patients for central sleep apnea.     

The Utility of Single-Channel Nasal Airflow Pressure Transducer in the Diagnosis Of OSA at Home

Rationale:

Given the high prevalence of obstructive sleep apnea (OSA) and the demand on polysomnography (PSG), there is a need for low cost accurate simple diagnostic modalities that can be easily deployed in primary care to improve access to diagnosis.

Study Objectives:

The aim was to examine the utility of single-channel nasal airflow monitoring using a pressure transducer at home in patients with suspected OSA.

Design:

Cross-sectional study

Setting:

Laboratory and home

Participants:

The study was conducted in two populations. Consecutive patients with suspected OSA were recruited from the sleep disorders clinic at a tertiary referral center and from 6 local metropolitan primary care centers.

Interventions:

All patients answered questionnaires and had laboratory PSG. Nasal airflow was monitored for 3 consecutive nights at home in random order either before or after PSG.

Results:

A total of 193 patients participated (105 sleep clinic patients and 88 from primary care). The mean bias PSG apnea hypopnea index (AHI) minus nasal flow respiratory disturbance index (NF RDI) was –4.9 events per hour with limits of agreement (2 SD) of 27.8. NF RDI monitored over 3 nights had high accuracy for diagnosing both severe OSA (defined as PSG AHI > 30 events per hour) with area under the receiver operating characteristic curve (AUC) 0.92 (95% confidence interval (CI) 0.88-0.96) and any OSA (PSG AHI >5), AUC 0.87 (95% CI 0.80-0.94).

Conclusions:

Single-channel nasal airflow can be implemented as an accurate diagnostic tool for OSA at home in both primary care and sleep clinic populations.

Citation:

Makarie Rofail L; Wong KKH; Unger G; Marks GB; Grunstein RR. The utility of single-channel nasal airflow pressure transducer in the diagnosis of OSA at home. SLEEP 2010;33(8):1097-1105.     

Nocturnal oximetry parameters as predictors of sleep apnea severity in resource-limited settings

Nocturnal oximetry is an alternative modality for evaluating obstructive sleep apnea syndrome (OSAS) severity when polysomnography is not available. The Oxygen Desaturation (≥3%) Index (ODI3) and McGill Oximetry Score (MOS) are used as predictors of moderate-to-severe OSAS (apnea-hypopnea index-AHI >5 episodes/h), an indication for adenotonsillectomy. We hypothesised that ODI3 is a better predictive parameter for AHI >5 episodes/h than the MOS. All polysomnograms performed in otherwise healthy, snoring children with tonsillar hypertrophy in a tertiary hospital (November 2014 to May 2019) were analysed. The ODI3 and MOS were derived from the oximetry channel of each polysomnogram. Logistic regression was applied to assess associations of ODI3 or MOS (predictors) with an AHI >5 episodes/h (primary outcome). Receiver operating characteristic (ROC) curves and areas under ROC curves were used to compare the ODI3 and MOS as predictors of moderate-to-severe OSAS. The optimal cut-off value for each oximetry parameter was determined using Youden's index. Polysomnograms of 112 children (median [interquartile range] age 6.1 [3.9–9.1] years; 35.7% overweight) were analysed. Moderate-to-severe OSAS prevalence was 49.1%. The ODI3 and MOS were significant predictors of moderate-to-severe OSAS after adjustment for overweight, sex, and age (odds ratio [OR] 1.34, 95% confidence interval [CI] 1.19–1.51); and OR 4.10, 95% CI 2.06–8.15, respectively; p < 0.001 for both). Area under the ROC curve was higher for the ODI3 than for MOS (0.903 [95% CI 0.842–0.964] versus 0.745 [95% CI 0.668–0.821]; p < 0.001). Optimal cut-off values for the ODI3 and MOS were ≥4.3 episodes/h and ≥2, respectively. The ODI3 emerges as preferable or at least a complementary oximetry parameter to MOS for detecting moderate-to-severe OSAS in snoring children when polysomnography is not available.