Effect of recording duration on the diagnostic accuracy of out-of-center sleep testing for obstructive sleep apnea

Chinese consensus report on the assessment and management of obstructive sleep apnea in patients with cardiovascular disease: 2024 edition

As cardiovascular disease (CVD) incidence and mortality rates continue to rise in China, the importance of identifying and managing CVD risk factors grows. Obstructive sleep apnea (OSA) is a prevalent sleep-related breathing disorder, affecting an estimated 936 million individuals aged 30-69 worldwide, with China leading globally with about 176 million affected. Increasing research indicates a close association between OSA and the onset and progression of various CVD, significantly affecting outcomes. However, OSA has long been underrecognized and undertreated in CVD clinical practice. To address this gap, a multidisciplinary expert panel developed evidence-based recommendations using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology and the Delphi process. This consensus provides 17 recommendations on core clinical issues such as screening, diagnosis, treatment, and follow-up of CVD patients with OSA, aiming to standardize care and improve patient outcomes. The recommendations were informed by current evidence-based research and extensive expert consensus discussions. This approach seeks to support clinical decision-making, improve the quality of care, and address the unique challenges of managing OSA in Chinese CVD patients.

A new telemedicine-based sleep service using WatchPAT® ONE for patients with suspected OSA: what does the patient experience?

PURPOSE

Obstructive Sleep Apnea is a widespread disease but is very underdiagnosed and undertreated. The aim of this study is to assess the effectiveness and patient satisfaction of using the WatchPAT® ONE, a disposable home sleep apnea test device, within a telemedicine-based management pathway.

METHODS

All patients who used the telemedicine services for OSA diagnosis using the WatchPAT® ONE were prospectively enrolled in the study. Patients receive the device at home and download its associated application to learn how to perform the test autonomously at night. Clinicians then review automated results transmitted by the cloud and conduct the follow-up visit via telemedicine, providing diagnostic and therapeutic guidance.

RESULTS

The study included 167 patients (78% male; mean age 55 ± 14 years; BMI: 27.5 ± 4.5 kg/cm²), with a mean distance of 147.29 ± 172.35 km from our hospital. The median time from test request to result delivery was 5 working days. The study cohort showed a median pAHI of 16.7 events/h, a median pODI was 7.9 events/h, and an pRDI of 20.7 events/h. 99% of respondents were satisfied with the remote management. Half of the subjects found both the application installation and the device operation extremely easy, and 60% of them were willing to recommend the use of WatchPAT® ONE.

CONCLUSION

The telemedicine pathway represents an efficient and patient-friendly method for diagnosing OSA. This approach improves diagnostic ease and accessibility while reducing time to diagnosis and societal and healthcare costs. Further large-scale studies are necessary to confirm these results.

Are scoring respiratory effort-related arousals worth the effort? --A study comparing outcomes between 4 % vs 3 % hypopnea scoring rules

STUDY OBJECTIVES

The respiratory effort-related arousal (RERA) has been combined with apneas and hypopneas into the respiratory disturbance index (RDI). RERAs are characterized by ≥ 10 s of increasing upper airway effort terminating in arousal without meeting hypopnea criteria. The recent change to hypopnea definitions now includes a ≥30 % reduction in airflow for 10 s with EITHER a 3 % oxygen desaturation OR an arousal. Consequently, many events previously categorized as RERAs will now be included in the 3 % hypopneas, likely reducing the number of events scored as RERAs. We hypothesized that the 3 % apnea-hypopnea index (3%AHI) would approximate the 4%RDI, with the number of 3 % RERAs being negligible.

RESEARCH QUESTION

How does the transition from the 4 % to the 3 % hypopnea rules impact the significance of RERAs in clinical practice, and how we should relate the AHI and RDI using the different hypopnea rules?

METHODS

We prospectively collected 76 consecutive polysomnography results in 4 adult age groups. We re-scored the respiratory events utilizing both the 3 % and the 4 % hypopnea rules and compared the outcomes.

RESULTS

Among 76 diagnostic studies (mean age 47.5 years, males 47.4 %), the 3 % RERA index [0.8 (0.0, 3.1)] [median (Q1, Q3)] was significantly lower than the 4 % RERA index [3.5 (1.0, 7.3)]. The 3%AHI was 3.07 ± 9.23 (mean ± SD) higher than the 4%RDI (p = 0.005). The 3%AHI was 8.63 ± 8.86 higher than the 4%AHI in all age groups (p < 0.001). This was mainly due to an increased hypopnea index (+8.51 ± 9.03, p < 0.001). In patients with obstructive sleep apnea (OSA), the 3%RERA contributes 4.3 % to the 3%RDI, while the 4%RERA contributes 27.7 % to the 4%RDI.

INTERPRETATIONS

Both 3%RDI and 3%AHI are higher than the 4%RDI, primarily due to identification of more hypopnea events, resulting in more patients being classified as having OSA. This change in criteria complicates the comparison of hypopnea and RERA contributions between sleep studies scored using the different hypopnea rules.

Evaluation of Minimum Recording Time and the Influence of Time in the Supine Position on Out-of-Center Sleep Tests

Introduction  The prevalence of moderate to severe sleep-disordered breathing is of 17% among men aged between 50 and 70-years, and of 9% among women in the same age group. In Brazil, obstructive sleep apnea (OSA) is also highly prevalent, and it is associated with metabolic and cardiovascular impacts, excessive daytime sleepiness, and increasing risk of traffic accidents. Laboratory-based polysomnography is the gold standard test for OSA diagnosis. However, its complexity has led to the search for alternatives to simplify the diagnosis, such as the out-of-center sleep test (OCST). Objectives  To discusses the minimum OCST recording time and the potential effects of the supine position on this parameter. Data Synthesis  We conducted a search on the PubMed, Web of Science, Scopus, and Embase databases to identify relevant studies on OCST recording time and a possible association with body position. We used a combination of terms, including Obstructive Sleep Apnea and Home Monitoring OR Home Care Services OR Portable Monitoring AND Supine OR Position OR Recording Time OR Positional Obstructive Sleep Apnea . The references of the selected articles were also reviewed to find other relevant studies. Through our approach, eighteen articles were retrieved and included in the present study. Conclusion  Since OCSTs are conducted in an unattended environment, with potential signal loss during the night, it is crucial to determine the minimum recording time to validate the test and assess how the time spent in the supine position affects this parameter. After reviewing the literature, this topic remains to be clarified, and additional studies should focus on that matter.

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.

Screening for obstructive sleep apnea in patients with cancer - a machine learning approach

Background

Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder associated with daytime sleepiness, fatigue, and increased all-cause mortality risk in patients with cancer. Existing screening tools for OSA do not account for the interaction of cancer-related features that may increase OSA risk.

Study Design and Methods

This is a retrospective study of patients with cancer at a single tertiary cancer institution who underwent a home sleep apnea test (HSAT) to evaluate for OSA. Unsupervised machine learning (ML) was used to reduce the dimensions and extract significant features associated with OSA. ML classifiers were applied to principal components and model hyperparameters were optimized using k-fold cross-validation. Training models for OSA were subsequently tested and compared with the STOP-Bang questionnaire on a prospective unseen test set of patients who underwent an HSAT.

Results

From a training dataset of 249 patients, kernel principal component analysis (PCA) extracted eight components through dimension reduction to explain the maximum variance with OSA at 98%. Predictors of OSA were smoking, asthma, chronic kidney disease, STOP-Bang score, race, diabetes, radiation to head/neck/thorax (RT-HNT), type of cancer, and cancer metastases. Of the ML models, PCA + RF had the highest sensitivity (96.8%), specificity (92.3%), negative predictive value (92%), F1 score (0.93), and ROC-AUC score (0.88). The PCA + RF screening algorithm also performed better than the STOP-Bang questionnaire alone when tested on a prospective unseen test set.

Conclusions

The PCA + RF ML model had the highest accuracy in screening for OSA in patients with cancer. History of RT-HNT, cancer metastases, and type of cancer were identified as cancer-related risk factors for OSA.

Evaluating an under-mattress sleep monitor compared to a peripheral arterial tonometry home sleep apnea test device in the diagnosis of obstructive sleep apnea

STUDY OBJECTIVES

To evaluate whether or not the apnea-hypopnea index (AHI) from a peripheral arterial tonometry (PAT) home sleep apnea test (HSAT) is equivalent to the AHI provided by the mean of one, three, or seven nights from the Withings Sleep Analyzer (WSA) under-mattress device.

METHODS

We prospectively enrolled patients with suspected OSA in whom a PAT-HSAT was ordered. Eligible patients used the WSA for seven to nine nights. PAT data were scored using the device's intrinsic machine learning algorithms to arrive at the AHI using both 3% and 4% desaturation criteria for hypopnea estimations (PAT3%-AHI and PAT4%-AHI, respectively). These were then compared with the WSA-estimated AHI (WSA-AHI).

RESULTS

Of 61 patients enrolled, 35 completed the study with valid PAT and WSA data. Of the 35 completers 16 (46%) had at least moderately severe OSA (PAT3%-AHI ≥ 15). The seven-night mean WSA-AHI was 2.13 (95%CI =  - 0.88, 5.14) less than the PAT3%-AHI, but 5.64 (95%CI = 2.54, 8.73) greater than the PAT4%-AHI. The accuracy and area under the receiver operating curve (AUC) using the PAT3%-AHI ≥ 15 were 77% and 0.87 and for PAT4%-AHI ≥ 15 were 77% and 0.85, respectively. The one-, three-, or seven-night WSA-AHI were not equivalent to either the 3% or 4% PAT-AHI (equivalency threshold of ± 2.5 using the two one-sided t-test method).

CONCLUSIONS

The WSA derives estimates of the AHI unobtrusively over many nights, which may prove to be a valuable clinical tool. However, the WSA-AHI over- or underestimates the PAT-AHI in clinical use, and the appropriate use of the WSA in clinical practice will require further evaluation.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04778748.

Documentation of polysomnographic and home sleep apnea test interpretations: room for improvement?

STUDY OBJECTIVES

Obstructive sleep apnea (OSA), a heterogeneous disorder with many different presentations, is diagnosed with sleep studies. In standard clinical practice, test data are reviewed and scored, and interpretations are documented. Little standardization exists regarding what should be included in interpretations. We aimed to determine how consistently the documented interpretation included references to study quality parameters and accepted disease phenotypes.

METHODS

This study was performed at a single academic center in January 2021. From the literature, we formulated a list of test and titration quality criteria and OSA phenotypes that should be reflected in study interpretations, including total recording time, total sleep time, positionality, and supine rapid eye movement (REM) sleep during titration. We retrospectively reviewed the documentation of sleep studies to determine how often these factors were reflected in interpretation reports or clinical notes.

RESULTS

Of 134 patients in the study, 81 were diagnosed with OSA. A finding of inadequate total recording time during polysomnography or total sleep time on home sleep apnea testing was most often not documented. Positionality of OSA was not documented in 33% of applicable studies. The absence of supine REM sleep during positive airway pressure titration was not mentioned in 15% of interpretations.

CONCLUSIONS

The documentation of quality concerns and clinically important OSA phenotypes in interpretations was inconsistent. Documentation of meaningful test quality information and sleep apnea phenotypes might be improved with report standardization or by developing enhanced data displays.

CITATION

Herberts MB, Morgenthaler TI. Documentation of polysomnographic and home sleep apnea test interpretations: room for improvement? J Clin Sleep Med. 2023;19(6):1043-1049.

Two effective clinical prediction models to screen for obstructive sleep apnoea based on body mass index and other parameters

BACKGROUND AND OBJECTIVE

The diagnosis of obstructive sleep apnea (OSA) relies on polysomnography which is time-consuming and expensive. We therefore aimed to develop two simple, non-invasive models to screen adults for OSA.

METHODS

The effectiveness of using body mass index (BMI) and a new visual prediction model to screen for OSA was evaluated using a development set (1769 participants) and confirmed using an independent validation set (642 participants).

RESULTS

Based on the development set, the best BMI cut-off value for diagnosing OSA was 26.45 kg/m², with an area under the curve (AUC) of 0.7213 (95% confidence interval (CI), 0.6861-0.7566), a sensitivity of 57% and a specificity of 78%. Through forward conditional logistic regression analysis using a stepwise selection model developed from observed data, seven clinical variables were evaluated as independent predictors of OSA: age, BMI, sex, Epworth Sleepiness Scale score, witnessed apnoeas, dry mouth and arrhythmias. With this new model, the AUC was 0.7991 (95% CI, 0.7668-0.8314) for diagnosing OSA (sensitivity, 75%; specificity, 71%). The results were confirmed using the validation set. A nomogram for predicting OSA was generated based on this new model using statistical software.

CONCLUSIONS

BMI can be used as an indicator to screen for OSA in the community. We created an internally validated, highly distinguishable, visual and parsimonious prediction model comprising BMI and other parameters that can be used to identify patients with OSA among outpatients. Use of this prediction model may help to improve clinical decision-making.

Poor performance of screening questionnaires for obstructive sleep apnea in male commercial drivers

PURPOSE

Screening commercial drivers (CDs) for obstructive sleep apnea (OSA) reduces the risk of motor vehicle accidents. We evaluated the accuracy of standard OSA questionnaires in a cohort of CDs.

STUDY DESIGN AND METHODS

We enrolled consecutive male CDs at 10 discrete transportation companies during their yearly scheduled occupational health visit. The CDs had their anthropometric measures taken; completed the Berlin, STOP, STOP-BANG, OSAS-TTI, SACS, EUROSAS, and ARES questionnaires; and underwent a home sleep apnea test (HSAT) for the determination of their respiratory events index (REI). We assessed the questionnaires' ability to predict OSA (REI ≥ 5 events/h) and moderate-to-severe OSA (REI ≥ 15 events/h).

RESULTS

Among 315 CDs recruited, 243 (77%) completed the study protocol, while 72 subjects were excluded for inadequate HSAT quality. The demographics and clinical data were comparable in both the included and excluded subjects. The included CDs had a median age of 50 years (interquartile range (IQR) 25-70) and a mean body mass index of 27 ± 4 kg/m². One hundred and seventy-one subjects (71%) had OSA, and 68 (28%) had moderate-to-severe OSA. A receiver operating characteristic curve of the questionnaires were 0.51-0.71 for predicting OSA and 0.51-0.66 for moderate-to-severe OSA. The STOP-BANG questionnaire had an unsatisfactory positive predictive value, while all of the other questionnaires had an inadequate negative predictive value.

CONCLUSIONS

Standard OSA questionnaires are not suited for screening among CDs. The use of the HSAT could provide an objective evaluation of for OSA in this special population.