Type III home sleep testing versus pulse oximetry: is the respiratory disturbance index better than the oxygen desaturation index to predict the apnoea-hypopnoea index measured during laboratory polysomnography?

Yield of overnight pulse oximetry in screening commercial drivers for obstructive sleep apnea

PURPOSE

To assess the efficacy of overnight pulse oximetry in screening male commercial drivers (CDs) for obstructive sleep apnea (OSA).

METHODS

Consecutive male CDs undergoing their annual scheduled occupational health visit were enrolled from ten transportation facilities. All subjects underwent a home sleep apnea test (HSAT) to determine the Respiratory Event Index (REI). Oxygen desaturation indices (ODIs) below the 3% and 4% thresholds were computed using the built-in HSAT pulse oximeter. We then assessed the association between ODI values and the presence of OSA (defined as an REI ≥ 5 events/hour) as well as moderate to severe OSA (REI ≥ 15 events/hour).

RESULTS

Of 331 CDs recruited, 278 (84%) completed the study protocol and 53 subjects were excluded due to inadequate HSAT quality. The included and excluded subjects were comparable in demographics and clinical characteristics. The included CDs had a median age of 49 years (interquartile range (IQR) = 15 years) and a median body mass index of 27 kg/m2 (IQR = 5 kg/m2). One hundred ninety-nine (72%) CDs had OSA, of which 48 (17%) were with moderate OSA and 45 (16%) with severe OSA. The ODI3 and ODI4 receiving operating characteristic curve value were 0.95 for predicting OSA and 0.98-0.96 for predicting moderate to severe OSA.

CONCLUSION

Overnight oxygen oximetry may be an effective means to screen CDs for OSA.

Clinical impact of manual scoring of peripheral arterial tonometry in patients with sleep apnea

PURPOSE

The objective was to analyze the clinical implications of manual scoring of sleep studies using peripheral arterial tonometry (PAT) and to compare the manual and automated scoring algorithms.

METHODS

Patients with suspected sleep-disordered breathing underwent sleep studies using PAT. The recordings were analyzed using a validated automated computer-based scoring and a novel manual scoring algorithm. The two methods were compared regarding sleep stages and respiratory events.

RESULTS

Recordings of 130 patients were compared. The sleep stages and time were not significantly different between the scoring methods. PAT-derived apnea-hypopnea index (pAHI) was on average 8.4 events/h lower in the manually scored data (27.5±17.4/h vs.19.1±15.2/h, p<0.001). The OSA severity classification decreased in 66 (51%) of 130 recordings. A similar effect was found for the PAT-derived respiratory disturbance index with a reduction from 31.2±16.5/h to 21.7±14.4/h (p<0.001), for automated and manual scoring, respectively. A lower pAHI for manual scoring was found in all body positions and sleep stages and was independent of gender and body mass index. The absolute difference of pAHI increased with sleep apnea severity, while the relative difference decreased. Pearson's correlation coefficient between pAHI and oxygen desaturation index (ODI) significantly improved from 0.89 to 0.94 with manual scoring (p<0.001).

CONCLUSIONS

Manual scoring results in a lower pAHI while improving the correlation to ODI. With manual scoring, the OSA category decreases in a clinically relevant proportion of patients. Sleep stages and time do not change significantly with manual scoring. In the authors' opinion, manual oversight is recommended if clinical decisions are likely to change.

A novel sleep oximetry scoring tool for pediatric laryngomalacia

OBJECTIVE

Despite being a more accessible and less resource intensive modality than polysomnography, the utility of sleep oximetry (SO) in pediatric laryngomalacia (LM) is not well understood or validated. We aimed to retrospectively evaluate the utility of overnight home based SO in children with LM by developing and internally validating the Modified Laryngomalacia Oximetry Score (MLOS) scoring system to triage severity and guide clinical decision making.

METHODS

We evaluated pediatric patients with a diagnosis of LM at our tertiary referral centre. Data from initial and post-treatment SO including mean oxygen saturation (spO2) nadir and mean oxygen desaturation index (ODI) were aggregated. The MLOS ranging from I-VI (inconclusive to severe) was created by two otolaryngologists to incorporate bradycardia associated desaturation events during SO. Corresponding McGill Oximetry Score (MOS) was also determined.

RESULTS

172 patients were included in final analysis. The average age was 9.2 ± 14.3 months. 98 (57%) of patients were identified as Thompson severity score 1, and 87 (50.6%) of patients underwent supraglottoplasty. The surgical cohort had a significantly higher MLOS and MOS scores of 4 and 2 respectively, and higher mean ODI and spO2 nadir metrics. When evaluating post-supraglottoplasty SO tracings, all parameters improved significantly, including median MLOS score from 4 to 1. Only the mean ODI improved in the non-surgical cohort. Patients with Thompson severity score 2/3 had significantly higher MLOS.

CONCLUSION

We present a simple scoring system based on overnight SO, the MLOS, to help triage severity of pediatric LM and guide decision-making. MLOS is associated with worse clinical severity and a need for surgery, and shows significant improvement after surgery.

Performance evaluation of a wrist-worn reflectance pulse oximeter during sleep

OBJECTIVES

To characterize and evaluate the estimation of oxygen saturation measured by a wrist-worn reflectance pulse oximeter during sleep.

METHODS

Ninety-seven adults with sleep disturbances were enrolled. Oxygen saturation was simultaneously measured using a reflectance pulse oximeter (Galaxy Watch 4 [GW4], Samsung, South Korea) and a transmittance pulse oximeter (polysomnography) as a reference. The performance of the device was evaluated using the root mean squared error (RMSE) and coverage rate. Additionally, GW4-derived oxygen desaturation index (ODI) was compared with the apnea-hypopnea index (AHI) derived from polysomnography.

RESULTS

The GW4 had an overall RMSE of 2.3% and negligible bias of -0.2%. A Bland-Altman density plot showed good agreement between the GW4 and the reference pulse oximeter. RMSEs were 1.65 ± 0.57%, 1.76 ± 0.65%, 1.93 ± 0.54%, and 2.93 ± 1.71% for normal (n = 18), mild (n = 21), moderate (n = 23), and severe obstructive sleep apnea (n = 35), respectively. The data rejection rate was 26.5%, which was caused by fluctuations in contact pressure and the discarding of data less than 70% of saturation. A GW4-ODI ≥5/h had the highest ability to predict AHI ≥15/h with sensitivity, specificity, accuracy, and area under the curve of 89.7%, 64.1%, 79.4%, and 0.908, respectively.

CONCLUSIONS

This study evaluated the estimation of oxygen saturation by the GW4 during sleep. This device complies with both Food and Drug Administration and International Organization for Standardization standards. Further improvements in the algorithms of wearable devices are required to obtain more accurate and reliable information about oxygen saturation measurements.

Home Sleep Testing of Sleep Apnea

Measurement methods with graded complexity for use in the lab as well as for home sleep testing (HST) are available for the diagnosis of sleep apnea, and there are different classification systems in existence. Simplified HST measurements, which record fewer parameters than traditional four- to six-channel devices, can indicate sleep apnea and can be used as screening tool in high-prevalence patient groups. Peripheral arterial tonometry (PAT) is a technique which can be suitable for the diagnosis of sleep apnea in certain cases. Different measurement methods are used, which has an influence on the significance of the results. New minimal-contact and non-contact technologies of recording and analysis of surrogate parameters are under development. If they are validated by clinical studies, it will be possible to detect sleep apnea in need of treatment more effectively. In addition, this could become a solution to monitor the effectiveness of such treatment.

Oximetry Indices in the Management of Sleep Apnea: From Overnight Minimum Saturation to the Novel Hypoxemia Measures

Obstructive sleep apnea (OSA) is a multidimensional disease often underdiagnosed due to the complexity and unavailability of its standard diagnostic method: the polysomnography. Among the alternative abbreviated tests searching for a compromise between simplicity and accurateness, oximetry is probably the most popular. The blood oxygen saturation (SpO₂) signal is characterized by a near-constant profile in healthy subjects breathing normally, while marked drops (desaturations) are linked to respiratory events. Parameterization of the desaturations has led to a great number of indices of severity assessment commonly used to assist in OSA diagnosis. In this chapter, the main methodologies used to characterize the overnight oximetry profile are reviewed, from visual inspection and simple statistics to complex measures involving signal processing and pattern recognition techniques. We focus on the individual performance of each approach, but also on the complementarity among the great amount of indices existing in the state of the art, looking for the most relevant oximetric feature subset. Finally, a quick overview of SpO₂-based deep learning applications for OSA management is carried out, where the raw oximetry signal is analyzed without previous parameterization. Our research allows us to conclude that all the methodologies (conventional, time, frequency, nonlinear, and hypoxemia-based) demonstrate high ability to provide relevant oximetric indices, but only a reduced set provide non-redundant complementary information leading to a significant performance increase. Finally, although oximetry is a robust tool, greater standardization and prospective validation of the measures derived from complex signal processing techniques are still needed to homogenize interpretation and increase generalizability.

A Minimum Set of Physiological Parameters to Diagnose Obstructive Sleep Apnea Syndrome Using Non-Invasive Portable Monitors. A Systematic Review

Introduction. Despite its high accuracy, polysomnography (PSG) has several drawbacks for diagnosing obstructive sleep apnea (OSA). Consequently, multiple portable monitors (PMs) have been proposed. Objective. This systematic review aims to investigate the current literature to analyze the sets of physiological parameters captured by a PM to select the minimum number of such physiological signals while maintaining accurate results in OSA detection. Methods. Inclusion and exclusion criteria for the selection of publications were established prior to the search. The evaluation of the publications was made based on one central question and several specific questions. Results. The abilities to detect hypopneas, sleep time, or awakenings were some of the features studied to investigate the full functionality of the PMs to select the most relevant set of physiological signals. Based on the physiological parameters collected (one to six), the PMs were classified into sets according to the level of evidence. The advantages and the disadvantages of each possible set of signals were explained by answering the research questions proposed in the methods. Conclusions. The minimum number of physiological signals detected by PMs for the detection of OSA depends mainly on the purpose and context of the sleep study. The set of three physiological signals showed the best results in the detection of OSA.

Diagnostic accuracy of oximetry for obstructive sleep apnea: a study on older adults in a home setting

OBJECTIVES

Owing to the fact that obstructive sleep apnea (OSA) is an underreported disease, the strategy used for the diagnosis of OSA has been extensively dissected to devise a simplified process that can be accessed by the public health services. Polysomnography (PSG) type I, the gold standard for the diagnosis of OSA, is expensive and difficult to access by low-income populations. In this study, we aimed to verify the accuracy of the oxyhemoglobin desaturation index (ODI) in comparison to the apnea-hypopnea index (AHI) using a portable monitor.

METHODS

We evaluated 94 type III PSG home test results of 65 elderly patients (69.21±6.94 years old), along with information, such as the body mass index (BMI) and sex, using data obtained from a clinical trial database.

RESULTS

A significant linear positive correlation (r=0.93, p<0.05) was observed between ODI and AHI, without any interference from sex, BMI, and positional component. The sensitivity of ODI compared to that of AHI increased with an increase in the severity of OSA, while the specificity of ODI in comparison to that of AHI was high for all degrees of severity. The accuracy of ODI was 80.7% for distinguishing between patients with mild and moderate apnea and 84.4% for distinguishing between patients with moderate and severe apnea.

CONCLUSION

The ODI values obtained in uncontrolled conditions exhibited high sensitivity for identifying severe apnea compared to the AHI values, and correctly identified the severity of OSA in more than 80% of the cases. Thus, oximetry is promising strategy for diagnosing OSA.

Nocturnal oximetry in bariatric surgery patients referred to overnight in-lab polysomnography

OBJECTIVE

This study aimed to evaluate nocturnal oximetry approaches in identifying obstructive sleep apnea (OSA) among bariatric surgical candidates.

METHODS

This was a cross-sectional study involving adult bariatric patients who were undergoing in-lab polysomnography and who were previously screened with the GOAL questionnaire. OSA severity was established as any OSA, moderate/severe OSA, and severe OSA. Oximetry data were evaluated as oxygen saturation (average and nadir), oxygen desaturation index (ODI) at 3%, and proportion of time spent with oxygen saturation <90%. Associations between oximetry data and the apnea-hypopnea index (AHI) were assessed by Spearman correlation index (r), linear regression, logistic regression, and discrimination.

RESULTS

All oximetry values were significantly correlated with the AHI among 1,178 individuals, with the ODI emerging as the better parameter (r = 0.911, p < 0.001). Using linear regression, the ODI was the only predictor of the AHI (β = 0.952, p < 0.001). In the multivariate analysis, the ODI was the only independent parameter predicting OSA at all severity levels. In addition, the ODI exhibited excellent discrimination to predict OSA and displayed improved performance among individuals screened as being at high risk versus those at low risk with the GOAL instrument.

CONCLUSIONS

The ODI emerges as a valid surrogate predictor of the AHI, particularly among those screened as being at high risk for OSA.

Postprandial hyperglycemia in type 2 diabetes and obstructive sleep apnea

OBJECTIVES

Postprandial hyperglycemia is common in type 2 diabetes even in those with acceptable glycemic control and conveys an increased risk of cardiovascular morbidity and mortality. Although obstructive sleep apnea (OSA) has been associated with altered glucose metabolism, data regarding its association with postprandial hyperglycemia in type 2 diabetes are limited. Thus, the current study sought to characterize the association between OSA and postprandial hyperglycemia in adults with type 2 diabetes.

METHODS

A cross-sectional study of adults with type 2 diabetes was conducted. Home sleep testing was used to assess OSA severity as determined by the oxygen desaturation index (ODI). Self-monitoring of blood glucose (SMBG) was performed before and 2-h after breakfast, lunch, and dinner for three days. The association between OSA and glucose levels before and after each meal was examined using multivariable logistic regression.

RESULTS

The study sample consisted of 195 adults with 52% being men. OSA severity, as assessed by ODI quartiles, was associated with higher postprandial glucose values after dinner but not after breakfast or lunch. The adjusted odds ratios (95% confidence intervals) for a higher post-dinner glucose level for four ODI quartiles were 1.00 (Reference), 2.16 (0.96, 4.87), 2.23 (1.03, 4.83), and 2.58 (1.18, 5.94). Stratified analyses showed that this association was present in men but not women.

CONCLUSIONS

Increasing OSA severity is associated with postprandial hyperglycemia in type 2 diabetes and may contribute to impaired glycemic control. Future studies examining the impact of OSA treatment on glucose metabolism should consider meal-related glycemic excursions as a potential outcome.

The effect of gradually increased mandibular advancement on the efficacy of an oral appliance in the treatment of obstructive sleep apnea

STUDY OBJECTIVES

To analyze the effect of gradual increments of mandibular advancement on the treatment efficacy of mandibular advancement devices and identify determinants of effective and target protrusion for OSA.

METHODS

Patients were prospectively recruited. The mandible was titrated from 0 mm with a stepwise increment of 0.5 mm until the AHI was reduced to the lowest level. Rhinospirometry, rhinomanometry, and magnetic resonance imaging were used to observe the change of respiratory function and upper airway morphology.

RESULTS

Forty-two patients aged 41.5 ± 9.0 years participated. There was a dose-dependent relationship between mandibular protrusion and the AHI improvement rate, the success rate, and the normalization rate; the changing curves plateaued after approximately 70% of maximal mandibular protrusion was achieved. The correlation between AHI and mandibular protrusion became stronger as the severity of OSA increased. The target protrusion for patients with mild, moderate, and severe OSA was 3.5 ± 1.8 mm (38.6 ± 19.4% maximal mandibular protrusion), 5.8 ± 1.9 mm (62.9 ± 18.8% maximal mandibular protrusion), and 5.9 ± 2.2 mm (68.8 ± 15.6% maximal mandibular protrusion), respectively. Regression analysis revealed that the factors influencing effective and target protrusion included change of maximal lateral dimension of the total upper airway with mandibular advancement devices, mean lateral dimension of the oropharynx, and soft palate length. Further protrusion brought more lateral expansion of the velopharynx, whereas the change in nasal ventilation was not significant.

CONCLUSIONS

The dose-dependent effect of mandibular protrusion on reduction of AHI by mandibular advancement devices was nonlinear and became more pronounced with increased severity of OSA. The mandibular protrusion should be more personalized to each patient.

CLINICAL TRIAL REGISTRATION

Registry: Chinese Clinical Trial Registry; Name: Study of the Onset Point of Oral Appliance Treatment in Obstructive Sleep Apnea and Hypopnea Syndrome; URL: http://www.chictr.org.cn/showproj.aspx?proj=22291; Identifier: ChiCTR-IND-17013232.

Contribution of pulse oximetry in relation to respiratory flow events in a home-based approach aimed at diagnosing obstructive sleep apnea

Objective

To compare pulse oximetry with manual analysis against all signals of respiratory polygraphy.

Material and Methods

This retrospective study estimated sensitivity (S), specificity (Sp) and positive/negative likelihood ratio (LR+/-) of the oxygen desaturation index (ODI-test) and apnea-hypopnea index (AHI-reference).

Results

3854 patients (61.5% men) were included. Age, BMI, Epworth sleepiness scale and AHI were: 55 years (44-65), 30.9kg/m² (27-36), 7 points (4-11), and 14 events/hour (6-25), respectively. 18% showed an AHI <5 events/hour, 34% = 5 and <15, 27% = or > 15 and < 30, and 31% > 30. The S, Sp, and LR+/- of ODI for AHI = 5 events/hour was 93%, 92%, 12 and 0.08 with an accuracy of 93%. For AHI = 15 events/hour, the values were: S 94%, Sp 94%, LR+ 15 and LR- 0.06 and 94% accuracy (r⁽²⁾ Spearman: 0.92).

Conclusion

In a population at a high risk for OSA, home-based pulse oximetry had a diagnostic accuracy > 90% when is compared against all respiratory signals obtained from simplified home sleep testing.

Predictive performance of oximetry in detecting sleep apnea in surgical patients with cardiovascular risk factors

INTRODUCTION

In adults with cardiovascular risk factors undergoing major noncardiac surgery, unrecognized obstructive sleep apnea (OSA) was associated with postoperative cardiovascular complications. There is a need for an easy and accessible home device in predicting sleep apnea. The objective of the study is to determine the predictive performance of the overnight pulse oximetry in predicting OSA in at-risk surgical patients.

METHODS

This was a planned post-hoc analysis of multicenter prospective cohort study involving 1,218 at-risk surgical patients without prior diagnosis of sleep apnea. All patients underwent home sleep apnea testing (ApneaLink Plus, ResMed) simultaneously with pulse oximetry (PULSOX-300i, Konica Minolta Sensing, Inc). The predictive performance of the 4% oxygen desaturation index (ODI) versus apnea-hypopnea index (AHI) were determined.

RESULTS

Of 1,218 patients, the mean age was 67.2 ± 9.2 years and body mass index (BMI) was 27.0 ± 5.3 kg/m2. The optimal cut-off for predicting moderate-to-severe and severe OSA was ODI ≥15 events/hour. For predicting moderate-to-severe OSA (AHI ≥15), the sensitivity and specificity of ODI ≥ 15 events per hour were 88.4% (95% confidence interval [CI], 85.7-90.6) and 95.4% (95% CI, 94.2-96.4). For severe OSA (AHI ≥30), the sensitivity and specificity were 97.2% (95% CI, 92.7-99.1) and 78.8% (95% CI, 78.2-79.0). The area under the curve (AUC) for moderate-to-severe and severe OSA was 0.983 (95% CI, 0.977-0.988) and 0.979 (95% CI, 0.97-0.909) respectively.

DISCUSSION

ODI from oximetry is sensitive and specific in predicting moderate-to-severe or severe OSA in at-risk surgical population. It provides an easy, accurate, and accessible tool for at-risk surgical patients with suspected OSA.

Predictive Performance of Oximetry to Detect Sleep Apnea in Patients Taking Opioids

BACKGROUND

Long-term use of opioids for treatment of chronic pain is associated with significant risks including worsening unrecognized or untreated sleep apnea that may increase morbidity and mortality. Overnight oximetry has been validated for predicting sleep apnea in surgical and sleep clinic patients. The objective of the study was to assess the predictive accuracy of oxygen desaturation index (ODI 4%) from home overnight oximetry when compared to apnea hypopnea index (AHI) from polysomnography for predicting sleep apnea in patients taking opioids for chronic pain.

METHODS

This was a planned post hoc analysis of a prospective cohort study conducted at 5 pain clinics. Patient characteristics and daily morphine milligram equivalent (MME) dose were recorded. All consented patients underwent home overnight oximetry (PULSOX-300i, Konica Minolta Sensing, Inc, Osaka, Japan) and in-laboratory polysomnography. The predictive performance of ODI 4% from oximetry was assessed against AHI from polysomnography.

RESULTS

Among 332 consented patients, 181 with polysomnography and overnight oximetry data were analyzed. The mean age and body mass index of 181 patients were 52 ± 13 years and 29 ± 6 kg/m2, respectively, with 40% men. The area under the receiver operating curve for ODI to predict moderate-to-severe sleep apnea (AHI ≥15 events/h) and severe sleep apnea (AHI ≥30 events/h) was 0.82 (95% confidence interval [CI], 0.75-0.88) and 0.87 (95% CI, 0.80-0.94). ODI ≥5 events/h had a sensitivity of 85% (95% CI, 74-92) and specificity of 57% (95% CI, 52-61) to predict moderate-to-severe sleep apnea. ODI ≥15 events/h had a sensitivity of 71% (95% CI, 55-83) and specificity of 88% (95% CI, 84-91) to predict severe sleep apnea.

CONCLUSIONS

Overnight home oximetry has a high predictive performance in predicting moderate-to-severe and severe sleep apnea in patients on opioids for chronic pain. It is a useful additional tool for health care providers for the screening of sleep apnea in this high-risk group.

Usefulness of Home Overnight Pulse Oximetry in Patients with Suspected Sleep-Disordered Breathing

Methods

Prospective study conducted in a university hospital. Subjects with a clinical suspicion of SAHS were included. All of them underwent home polygraphy and oximetry on the same night. A correlation was made between the apnea-hypopnea index (AHI) and the oximetry variables. The variable with the highest diagnostic value was calculated using the area under the curve (AUC), and the best cut-off point for discriminating between patients with SAHS and severe SAHS was identified.

Results

One hundred and four subjects were included; 73 were men (70%); mean age was 52 ± 10.1 years; body mass index was 30 ± 4.1, and AHI = 29 ± 23.2/h. A correlation was observed between the AHI and oximetry variables, particularly ODI3 (r = 0.850; P < 0.001) and ODI4 (r = 0.912; P < 0.001). For an AHI ≥ 10/h, the ODI3 had an AUC = 0.941 (95% confidence interval (CI) = 0.899–0.982) and the ODI4, an AUC = 0.984 (95% CI = 0.964–1), with the ODI4 having the best cut-off point (5.4/h). Similarly, for an AHI ≥ 30/h, the ODI4 had an AUC = 0.922 (95% CI = 0.859–0.986), with the best cut-off point being 10.5/h.

Conclusion

Nocturnal oximetry is useful for diagnosing and evaluating the severity of SAHS. The ODI4 variable was most closely correlated with AHI for both diagnosis.

Pre-diabetic patients with severe obstructive sleep apnea: novel parameters of hypoxia during sleep correlate with insulin resistance

Obstructive sleep apnea (OSA) is an increasingly prevalent sleep disorder with estimated prevalence of moderate to severe sleep apnea ranging between 6-13% in the adult population. Nocturnal intermittent hypoxia has been associated with an increased risk of developing type 2 diabetes and insulin resistance (IR). The existing indices of hypoxia, used in polysomnography (PSG), cannot express accurately the influence of the mild desaturations precisely during sleep. In the present study, 73 subjects without other comorbidities were examined by PSG. Hypoxia parameters were analyzed, in the intervals with low values of SpO₂ signal. The thresholds were set at 94% and 92% and the average value (M) of the SpO₂ signal, in areas below thresholds, were calculated. The desaturations were analyzed together with their duration within the recording in terms of SpO₂ signal parameters. Blood samples were taken for biochemical analysis. A total of 50 subjects were diagnosed with OSAS with mean AHI of 56.11±27.70/h and 23 subjects had no sleep apnea with mean AHI of 3.47±0.6/h. The amount of desaturations was significantly correlated with insulin levels (r=0.301, p=0.034) and the percentage of desaturation events (Dev) that were longer than 6 points (2 sec) (r=0.301, p=0.034). In addition, mean duration of desaturations was significantly correlated with IR as expressed by HOMA index (r=0.289, p=0.047), as well as with total duration of desaturation of SpO₂ (r=0.322, p =0.025) and percentage of Dev that were long than 6 points (2 sec) (r=0.292, p=0.044). A strong correlation was also revealed between total duration of desaturations and fasting glucose (r=0.887, p=0.000). Results suggest that hypoxia parameters derived from SpO₂ signal analysis, are strongly correlated with IR and fasting glucose levels, implying a role of hypoxia in the pathogenesis of diabetes.

Diagnostic performance of nocturnal oximetry in the detection of obstructive sleep apnea syndrome: a Brazilian study

OBJECTIVE

Due to the increasing prevalence of obstructive sleep apnea (OSA), more practical diagnostic methods than polysomnography (PSG) have become necessary. This research aims to analyze the performance of nocturnal oximetry (NO) in the diagnosis of OSA.

METHODS

In this cross-sectional study, we analyzed 41 variables provided by the oximetry of all PSG performed by the LabSono of University Hospital Gaffrée and Guinle, a total of 83 exams. We evaluated the correlation coefficients (Spearman) between these data and the Apnea/Hypopnea Index (AHI) and then calculated the diagnostics performances, by the area under the curve (ROC) (AUC), of the best correlated variables and their respective cutoffs, in the identification of an AHI ≥ 15/h.

RESULTS

Virtually all oximetric data showed good correlations with AHI, except for some temporal data. We chose 5 of them and calculated their diagnostic performances. T < 90% shows AUC of 0.904 (0.835-0.972) and, at cutoff > 19 min, a sensitivity (Sens.) of 75.68% and specificity (Spec.) of 95.65%. DO3/10Total, AUC 0.936 (0.888-0.989), and at the cutoff > 51 has Sens. 97.3% and Spec. 76.09%. ODI3/10/h has AUC 0.932 (0.884-0.988), at the cutoff > 7/h, Sens. 97.3% and Spec. 78.26%. DO4/5Total AUC 0.932 (0.882-0.981), at the cutoff > 64 has Sens. 86.49% and Spec. 82.61% and ODI4/5/h has AUC 0.930 (0.880-0.981), the cutoff > 5.69/h Sens. 97.3% and Spec. 73.91%.

CONCLUSIONS

Our study concludes that NO is accurate in identifying AHI > 15/h, and provides reliable information on PSG replacement, which could make the diagnosis of OSA cheaper and more comfortable.

Louis EK, Penzel T, Dawson D, Westbrook PR. A comparison between auto-scored apnea-hypopnea index and oxygen desaturation index in the characterization of positional obstructive sleep apnea

OBJECTIVE

Evaluate the concordance between overall and positional oxygen desaturation indices (ODI) and apnea-hypopnea indices (AHI) according to two different definitions for positional obstructive sleep apnea (POSA).

METHODS

A total of 184 in-home polysomnograms were edited to simulate Level III home sleep apnea tests (HSAT) with the auto-scored AHI and ODI based on recording time. POSA was determined using 132 records with an AHI≥5 and at least 20 mins of recording time in both supine and non-supine positions. POSA was defined independently for the AHI and ODI based on ratios of overall/non-supine event/h ≥1.4 (O/NS) and supine/non-supine event/h≥2.0 (S/NS).

RESULTS

Correlation between the AHI and ODI was 0.97 overall, 0.94 for supine, and 0.96 for non-supine recording times (all p<0.001). For most records, differences between the AHI and ODI were small, with only 14% of the records having a AHI-ODI difference exceeding >5/hr, and 6% exceeding >10 events/hr. The positive and negative percent agreements were uniformly good to excellent across varying clinical POSA cutoffs; percent agreements (positive, negative) were: AHI≥5=0.99, 0.78; AHI≥10=0.96, 0.89; and AHI≥15=0.96, 0.89. Cohen's Kappa scores also showed substantial agreement for overall as well as supine and non-supine positions across varying clinical cutoffs of the AHI. Frequency of POSA was reproducibly uniform between 59% and 61% for both POSA criteria. When the O/NS and S/NS definitions conflicted in POSA characterization, O/NS was superior for identifying patients who might exhibit a greater response to supine restriction positional therapy.

CONCLUSIONS

Auto-scored positional oximetry is a clinically viable alternative to an auto-scored Level III HSAT AHI in the characterization of POSA based on a 3% desaturation.

Obstructive Sleep Apnea, Sleepiness, and Glycemic Control in Type 2 Diabetes

STUDY OBJECTIVES

Self-reported sleepiness is common in patients with obstructive sleep apnea (OSA) and is being increasingly recognized as an effect modifier of the association between OSA and cardiovascular outcomes. However, data on whether sleepiness modifies the association between OSA and glycemic outcomes are lacking. The current study sought to characterize the association between glycemic control and sleepiness in people with OSA and type 2 diabetes.

METHODS

Adults with non-insulin requiring type 2 diabetes and undiagnosed moderate to severe OSA were recruited from the community. Demographic data, Epworth Sleepiness Scale (ESS), hemoglobin A1c (HbA1c), as well a type III home sleep test were obtained. The association between self-reported sleepiness and glycemic control was examined using quantile regression.

RESULTS

The study cohort included 311 participants with 56% of the sample being men. Stratified analyses by sex demonstrated that self-reported sleepiness was associated with a higher HbA1c level, but this association was present only in men with a body mass index (BMI) < 35 kg/m². Mean HbA1c levels were higher by 0.57% (95% confidence interval: 0.11, 1.02) in men with an ESS ≥ 11 compared to men with an ESS < 11. No such association was observed in men with a BMI ≥ 35 kg/m² or in women of any BMI category.

CONCLUSIONS

The association between self-reported sleepiness and glycemic control in people with type 2 diabetes and moderate to severe OSA varies a function of BMI and sex. The noted differences in association should be considered when assessing possible treatment effects of therapy for OSA on metabolic outcomes.

Oximetry as an Accurate Tool for Identifying Moderate to Severe Sleep Apnea in Patients With Acute Stroke

STUDY OBJECTIVES

Sleep-disordered breathing (SDB) is highly prevalent in patients with acute stroke. SDB is often underdiagnosed and associated with neurological deterioration and stroke recurrence. Polysomnography or home sleep apnea testing (HSAT) is typically used as the diagnostic modality; however, it may not be feasible to use regularly in patients with acute stroke. We investigated the predictive performance of pulse oximetry, a simpler alternative, to identify SDB.

METHODS

The records of 254 patients, who were admitted to Boston Medical Center for acute stroke and underwent HSAT, were retrospectively reviewed. Oxygen desaturation index (ODI) from pulse oximetry channel were compared to respiratory event index (REI) obtained from HSAT devices. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ODI were calculated, and different ODI cutoff values to predict SDB were proposed.

RESULTS

ODI had a strong correlation (r = .902) and agreement with REI. ODI was accurate in predicting SDB at different REI thresholds (REI ≥ 5, REI ≥ 15, and REI ≥ 30 events/h) with the area under the curve (AUC) of .965, .974, and .951, respectively. An ODI ≥ 5 events/h rules in the presence of SDB (specificity 91.7%, PPV 96.3%). An ODI ≥ 15 events/h rules in moderate to severe SDB (specificity 96.4%, PPV 95%) and an ODI < 5 events/h rules out moderate to severe SDB (sensitivity 100%, NPV 100%).

CONCLUSIONS

Nocturnal pulse oximetry has a high diagnostic accuracy in predicting moderate to severe SDB in patients with acute stroke. Oximetry can be a simple modality to rapidly recognize patients with more severe SDB and facilitate the referral to the confirmation sleep study.

Opportunities for utilizing polysomnography signals to characterize obstructive sleep apnea subtypes and severity

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder with many pathophysiological pathways to disease. Currently, the diagnosis and classification of OSA is based on the apnea-hypopnea index, which poorly correlates to underlying pathology and clinical consequences. A large number of in-laboratory sleep studies are performed around the world every year, already collecting an enormous amount of physiological data within an individual. Clinically, we have not yet fully taken advantage of this data, but combined with existing analytical approaches, we have the potential to transform the way OSA is managed within an individual patient. Currently, respiratory signals are used to count apneas and hypopneas, but patterns such as inspiratory flow signals can be used to predict optimal OSA treatment. Electrocardiographic data can reveal arrhythmias, but patterns such as heart rate variability can also be used to detect and classify OSA. Electroencephalography is used to score sleep stages and arousals, but specific patterns such as the odds-ratio product can be used to classify how OSA patients responds differently to arousals.

OBJECTIVE

In this review, we examine these and many other existing computer-aided polysomnography signal processing algorithms and how they can reflect an individual's manifestation of OSA.

SIGNIFICANCE

Together with current technological advance, it is only a matter of time before advanced automatic signal processing and analysis is widely applied to precision medicine of OSA in the clinical setting.

Assessment of automated analysis of portable oximetry as a screening test for moderate-to-severe sleep apnea in patients with chronic obstructive pulmonary disease

BACKGROUND

The coexistence of obstructive sleep apnea syndrome (OSAS) and chronic obstructive pulmonary disease (COPD) leads to increased morbidity and mortality. The development of home-based screening tests is essential to expedite diagnosis. Nevertheless, there is still very limited evidence on the effectiveness of portable monitoring to diagnose OSAS in patients with pulmonary comorbidities.

OBJECTIVE

To assess the influence of suffering from COPD in the performance of an oximetry-based screening test for moderate-to-severe OSAS, both in the hospital and at home.

METHODS

A total of 407 patients showing moderate-to-high clinical suspicion of OSAS were involved in the study. All subjects underwent (i) supervised portable oximetry simultaneously to in-hospital polysomnography (PSG) and (ii) unsupervised portable oximetry at home. A regression-based multilayer perceptron (MLP) artificial neural network (ANN) was trained to estimate the apnea-hypopnea index (AHI) from portable oximetry recordings. Two independent validation datasets were analyzed: COPD versus non-COPD.

RESULTS

The portable oximetry-based MLP ANN reached similar intra-class correlation coefficient (ICC) values between the estimated AHI and the actual AHI for the non-COPD and the COPD groups either in the hospital (non-COPD: 0.937, 0.909-0.956 CI95%; COPD: 0.936, 0.899-0.960 CI95%) and at home (non-COPD: 0.731, 0.631-0.808 CI95%; COPD: 0.788, 0.678-0.864 CI95%). Regarding the area under the receiver operating characteristics curve (AUC), no statistically significant differences (p >0.01) between COPD and non-COPD groups were found in both settings, particularly for severe OSAS (AHI ≥30 events/h): 0.97 (0.92-0.99 CI95%) non-COPD vs. 0.98 (0.92-1.0 CI95%) COPD in the hospital, and 0.87 (0.79-0.92 CI95%) non-COPD vs. 0.86 (0.75-0.93 CI95%) COPD at home.

CONCLUSION

The agreement and the diagnostic performance of the estimated AHI from automated analysis of portable oximetry were similar regardless of the presence of COPD both in-lab and at-home. Particularly, portable oximetry could be used as an abbreviated screening test for moderate-to-severe OSAS in patients with COPD.

Methodological strategies in using home sleep apnea testing in research and practice

PURPOSE

Home sleep apnea testing (HSAT) has increased due to improvements in technology, accessibility, and changes in third party reimbursement requirements. Research studies using HSAT have not consistently reported procedures and methodological challenges. This paper had two objectives: (1) summarize the literature on use of HSAT in research of adults and (2) identify methodological strategies to use in research and practice to standardize HSAT procedures and information.

METHODS

Search strategy included studies of participants undergoing sleep testing for OSA using HSAT. MEDLINE via PubMed, CINAHL, and Embase with the following search terms: "polysomnography," "home," "level III," "obstructive sleep apnea," and "out of center testing."

RESULTS

Research articles that met inclusion criteria (n = 34) inconsistently reported methods and methodological challenges in terms of: (a) participant sampling; (b) instrumentation issues; (c) clinical variables; (d) data processing; and (e) patient acceptability. Ten methodological strategies were identified for adoption when using HSAT in research and practice.

CONCLUSIONS

Future studies need to address the methodological challenges summarized in this paper as well as identify and report consistent HSAT procedures and information.

Comparison of two home sleep testing devices with different strategies for diagnosis of OSA

PURPOSE

Home sleep testing devices are being widely used in diagnosis/screening for obstructive sleep apnea (OSA). We examined differences in OSA metrics obtained from two devices with divergent home monitoring strategies, the Apnea Risk Evaluation System (ARES™, multiple signals plus forehead reflectance oximetry) and the Nonin WristOx₂™ (single channel finger transmission pulse oximeter), compared to differences from night-night variability of OSA.

METHODS

One hundred fifty-two male/26 female subjects (BMI = 30.3 ± 5.6 kg/m², age = 52.5 ± 8.9 years) were recruited without regard to OSA symptoms and simultaneously wore both ARES™ and Nonin WristOx₂™ for two nights (n = 351 nights). Automated analysis of the WristOx₂ yielded oxygen desaturation index (ODI_Ox2, ≥4% O2 dips/h), and automated analysis with manual editing of ARES™ yielded AHI4_ARES (apneas + hypopneas with ≥4% O2 dips/h) and RDI_ARES (apneas + hypopneas with ≥4% O2 dips/h or arousal surrogates). Baseline awake oxygen saturation, percent time < 90% O2 saturation (%time < 90%O2Sat), and O2 signal loss were compared between the two methods.

RESULTS

Correlation between AHI4_ARES and ODI_Ox2 was high (ICC = 0.9, 95% CI = 0.87-0.92, p < 0.001, bias ± SD = 0.7 ± 6.1 events/h). Agreement values for OSA diagnosis (77-85%) between devices were similar to those seen from night-to-night variability of OSA using a single device. Awake baseline O2 saturation was significantly higher in the ARES™ (96.2 ± 1.6%) than WristOx₂™ (92.2 ± 2.1%, p < 0.01). There was a significantly lower %time < 90%O2Sat reported by the ARES™ compared to WristOx₂ (median (IQR) 0.5 (0.0, 2.6) vs. 2.1 (0.3, 9.7), p < 0.001), and the correlation was low (ICC = 0.2).

CONCLUSIONS

OSA severity metrics predominantly dependent on change in oxygen saturation and metrics used in diagnosis of OSA (AHI4 and ODI) correlated well across devices tested. However, differences in cumulative oxygen desaturation measures (i.e., %time < 90%O2Sat) between the devices suggest that caution is needed when interpreting this metric particularly in populations likely to have significant hypoxia.

Validation of ApneaLink™ Plus for the diagnosis of sleep apnea

PURPOSE

The aim of this study is to evaluate the validation of ApneaLink™ Plus (ALP) based on a large number of subjects in a prospective design.

METHOD

We recommended enrolling of 200 consecutive patients who had been referred because of habitual snoring or witnessed apnea during sleep. If consent was obtained, patients underwent standard polysomnography (PSG) and ALP evaluation simultaneously at the hospital (ALP_lab), and repeated ALP at home (ALP_home) within 1 month. The parameters of ALP were scored based on three different systems, Manual, Auto AASM, and Auto scoring systems.

RESULT

Among the 200 patients who were recommended for enrollment, 149 completed the study. Sensitivity was good for all three scoring systems, while specificity was poor for the Auto scoring system. The area under curve was highest for the manual scoring system and lowest for the auto scoring system, and increased as the apnea-hypopnea index (AHI) cutoff value increased from 5 to 30. Regarding agreement with PSG, the manual scoring system was most superior, followed by the Auto AASM, and Auto scoring systems. The degree of agreement between PSG and ALP was affected by sleep efficiency and the arousal index. Moderate agreement between PSG and ALP based on central apnea index was observed.

CONCLUSION

ALP is an accurate and reliable device for the diagnosis of OSA. Manual scoring is recommended; however, Auto AASM is also acceptable. ALP detects central sleep apnea to a certain degree. Both sleep efficiency and the arousal index affect the results of ALP.

Evaluation of the Sleepy Patient: Differential Diagnosis

Excessive daytime sleepiness is defined as the inability to maintain wakefulness during waking hours, resulting in unintended lapses into sleep. It is important to distinguish sleepiness from fatigue. The evaluation of a sleep patient begins with a careful clinical assessment that includes a detailed sleep history, medical and psychiatric history, a review of medications, as well as a social and family history. Physical examination should include a general medical examination with careful attention to the upper airway and the neurologic examination. Appropriate objective testing with a polysomnogram and a multiple sleep latency test if needed will help confirm the diagnosis and direct the appropriate treatment plan.

Subclinical sleep apnoea and plasma levels of endothelin-1 among young and healthy adults

Objective

Obstructive sleep apnoea (OSA) is a risk factor for vascular disease and other adverse outcomes. These associations may be at least partly due to early endothelin-1 (ET-1)-mediated endothelial dysfunction (ED). Therefore, we assessed the relationships between subclinical sleep apnoea and plasma levels of ET-1.

Methods

We performed a population-based study among 1255 young and healthy adults aged 25–41 years. Cardiovascular disease, diabetes or a body mass index >35 kg/m² were exclusion criteria. Plasma levels of ET-1 were measured using a high-sensitivity, single-molecule counting technology. The relationships between subclinical sleep apnoea (OSA indices: respiratory event index (REI), oxygen desaturation index (ODI), mean night-time blood oxygen saturation (SpO₂)) and ET-1 levels were assessed by multivariable linear regression analysis.

Results

Median age of the cohort was 35 years. Median ET-1 levels were 2.9 (IQR 2.4–3.6) and 2.5 pg/mL (IQR 2.1–3.0) among patients with (n=105; 8%) and without subclinical sleep apnoea (REI 5–14), respectively. After multivariable adjustment, subclinical sleep apnoea remained significantly associated with plasma levels of ET-1 (β=0.13 (95% CI 0.06 to 0.20) p=0.0002 for a REI 5–14; β=0.10 (95% CI 0.03 to 0.16) p=0.003 for an ODI≥5). Every 1% decrease in mean night-time SpO₂ increased ET-1 levels by 0.1 pg/mL, an association that remained significant after multivariable adjustment (β=0.02 (95% CI 0.003 to 0.033) p=0.02).

Conclusions

In this study of young and healthy adults, we found that participants with subclinical sleep apnoea had elevated plasma ET-1 levels, an association that was due to night-time hypoxaemia. Our results suggest that ED may already be an important consequence of subclinical sleep apnoea.

Oxygen Desaturation Index Differs Significantly Between Types of Sleep Software

STUDY OBJECTIVES

The aim of this study was to compare the oxygen desaturation index (ODI) generated by two different sleep software systems.

METHODS

Participants undergoing diagnostic polysomnography for suspected obstructive sleep apnea underwent simultaneous oximetry recording using the ResMed ApneaLink Plus device (AL) and Compumedics Profusion PSG3 system (Comp). The ODI was calculated by the algorithms in the respective software of each system. To determine if differences were due to algorithm or recording devices, the Comp software was also used to generate ODI values using oximetry data from the AL.

RESULTS

In 106 participants, there was good correlation but poor agreement in the ODI generated by the two systems. AL ODI values tended to be higher than Comp ODI values, but with significant variability. For ODI4%, bias was 4.4 events/h (95% limits of agreement -5.8 to 14.6 events/h). There was excellent correlation and agreement when the same oximetry raw data was analyzed by both systems. For ODI4%, bias was 0.03 events/h (95% limits of agreement -2.7 to 2.8 events/h). Similar results were evident when the ODI3% was used.

CONCLUSIONS

There is a clinically significant difference in ODI values generated by the two systems, likely due to device signal processing, rather than difference in ODI calculation algorithms.

Sleep and Breathing … and Cancer?

Sleep, like eating and breathing, is an essential part of the daily life cycle. Although the science is still emerging, sleep plays an important role in immune, cardiovascular, and neurocognitive function. Despite its great importance, nearly 40% of U.S. adults experience problems with sleep ranging from insufficient total sleep time, trouble initiating or maintaining sleep (Insomnia), circadian rhythm disorders, sleep-related movement disorders, and sleep-related breathing disorders such as obstructive sleep apnea (OSA). Herein, we discuss new evidence that suggests that sleep may also affect carcinogenesis. Specifically, we review recent epidemiologic data suggesting links between cancer and OSA. As OSA is a common, underdiagnosed, and undertreated condition, this has public health implications. Intriguing animal model data support a link between cancer and sleep/OSA, although mechanisms are not yet clear. Leaders in the fields of sleep medicine, pulmonology, and oncology recently met to review and discuss these data, as well as to outline future directions of study. We propose a multidisciplinary, three-pronged approach to studying the associations between cancer and sleep, utilizing mutually interactive epidemiologic studies, preclinical models, and early-phase clinical trials. Cancer Prev Res; 9(11); 821-7. ©2016 AACR.

Agreement Between Results of Home Sleep Testing for Obstructive Sleep Apnea with and Without a Sleep Specialist

BACKGROUND

Obstructive sleep apnea is a prevalent yet underdiagnosed condition associated with cardiovascular morbidity and mortality. Home sleep testing offers an efficient means for diagnosing obstructive sleep apnea but has been deployed primarily in clinical samples with a high pretest probability. The present study sought to assess whether obstructive sleep apnea can be diagnosed with home sleep testing in a nonreferred sample without involvement of a sleep medicine specialist.

METHODS

A study of community-based adults with untreated obstructive sleep apnea was undertaken. Misclassification of disease severity according to home sleep testing with and without involvement of a sleep medicine specialist was assessed, and agreement was characterized using scatter plots, Pearson's correlation coefficient, Bland-Altman analysis, and the κ statistic. Analyses were also conducted to assess whether any observed differences varied as a function of pretest probability of obstructive sleep apnea or subjective sleepiness.

RESULTS

The sample consisted of 191 subjects, with more than half (56.5%) having obstructive sleep apnea. Without involvement of a sleep medicine specialist, obstructive sleep apnea was not identified in only 5.8% of the sample. Analyses comparing the categorical assessment of disease severity with and without a sleep medicine specialist showed that in total, 32 subjects (16.8%) were misclassified. Agreement in the disease severity with and without a sleep medicine specialist was not influenced by the pretest probability or daytime sleep tendency.

CONCLUSION

Obstructive sleep apnea can be reliably identified with home sleep testing in a nonreferred sample, irrespective of the pretest probability of the disease.