Predicting Obstructive Sleep Apnea in Patients with Insomnia: A Comparative Study with Four Screening Instruments

A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension

Background

Obstructive sleep apnea (OSA) is common in patients with hypertension. Nonetheless, OSA is underdiagnosed despite considerable evidence of the association between OSA and adverse health outcomes. This study developed and validated a clinical nomogram to predict OSA in patients with hypertension based on the Epworth Sleepiness Scale (ESS) score and OSA-related parameters.

Methods

A total of 347 hypertensive patients with suspected OSA were retrospectively enrolled and randomly assigned to a training set and a validation set at 70 : 30 (N = 242/N = 105) ratio. OSA was diagnosed through sleep monitoring and was defined as an apnea-hypopnea index ≥5 events/h. Using the least absolute shrinkage and selection operator regression model, we identified potential predictors of OSA and constructed a nomogram model in the training set. The predictive performance of the nomogram was assessed and validated by discrimination and calibration. The nomogram was also compared with ESS scores according to decision curve analysis (DCA), integrated discrimination index (IDI), and net reclassification index (NRI).

Results

ESS scores, body mass index, neck circumference, snoring, and observed apnea predicted OSA are considered. The nomogram showed similar discrimination between the training set (AUC: 0.799, 95% CI: 0.743–0.847) and validation set (AUC: 0.766, 95% CI: 0.673–0.843) and good calibration in the training (P=0.925 > 0.05) and validation (P=0.906 > 0.05) sets. Compared with the predictive value of the ESS, the nomogram was clinically useful and significantly improved reclassification accuracy (NRI: 0.552, 95% CI: 0.282–0.822, P < 0.001; IDI: 0.088, 95% CI: 0.045–0.133, P < 0.001) at a probability threshold of >42%.

Conclusions

We developed a novel OSA prediction nomogram based on ESS scores and OSA-related parameters. This nomogram may help improve clinical decision-making, especially in communities and primary clinics, where polysomnography is unavailable.

Development and validation of a simple clinical nomogram for predicting obstructive sleep apnea

Obstructive sleep apnea is the most common type of sleep breathing disorder. Therefore, the purpose of our research is to construct and verify an objective and easy-to-use nomogram that can accurately predict a patient's risk of obstructive sleep apnea. In this study, we retrospectively collected the data of patients undergoing polysomnography at the Sleep Medicine Center of the First Affiliated Hospital of Guangzhou Medical University. Participants were randomly assigned to a training cohort (50%) and a validation cohort (50%). Logistic regression and Lasso regression models were used to reduce data dimensions, select factors and construct the nomogram. C-index, calibration curve, decision curve analysis and clinical impact curve analysis were used to evaluate the identification, calibration and clinical effectiveness of the nomogram. Nomograph validation was performed in the validation cohort. The study included 1035 people in the training cohort and 1078 people in the validation cohort. Logistic and Lasso regression analysis identified age, gender, diastolic blood pressure, body mass index, neck circumference and Epworth Sleepiness Scale as the predictive factors included in the nomogram. The training cohort (C-index = 0.741) and validation cohort (C-index = 0.745) had better identification and calibration effects. The areas under the curve of the nomogram and STOP-Bang were 0.741 (0.713-0.767) and 0.728 (0.700-0.755), respectively. Decision curve analysis and clinical impact curve analysis showed that the nomogram is clinically useful. We have established a concise and practical nomogram that will help doctors better determine the priority of patients referred to the sleep centre.

Influence of nocturnal insomnia symptoms on obstructive sleep apnea diagnosis in a clinical referral cohort

STUDY OBJECTIVES

To assess whether nocturnal symptoms of insomnia influence the prevalence of obstructive sleep apnea (OSA) in a clinical referral cohort.

METHODS

Insomnia was defined by the presence of one or more of the following complaints: difficulty initiating sleep, difficulty maintaining sleep, and/or early morning awakenings. OSA severity was based on an apnea-hypopnea index: ≥ 5.0/h (any OSA), ≥ 15.0/h (moderate/severe OSA), and ≥ 30/h (severe OSA). Multivariate logistic regression analysis was used to evaluate predictive factors for OSA diagnosis and severity.

RESULTS

Overall, 12,021 outpatients referred for polysomnography (PSG) were grouped into two cohorts: without insomnia (58.2%) and with insomnia (41.8%). Individuals without insomnia had a higher prevalence of OSA than those with insomnia (p < 0.001, for all OSA severity levels). The presence of insomnia was negatively associated with diagnosis of any OSA (adjusted odds ratio [OR]: 0.852; 95% confidence interval [CI]: 0.769-0.944), moderate/severe OSA (adjusted OR: 0.819; 95% CI: 0.751-0.892), and severe OSA (adjusted OR: 0.816; 95% CI: 0.746-0.892). Moreover, the number of nocturnal symptoms of insomnia was associated with a lower likelihood of OSA, even when adjusted for other confounders such as sex, age, body mass index, neck circumference, excessive daytime sleepiness, hypertension, and type 2 diabetes mellitus.

CONCLUSIONS

In this present study that included a large sample of consecutive outpatients, there was an inverse relationship between the number of nocturnal symptoms of insomnia and OSA diagnosis.

The influence of sex on anthropometric methods and four scales for screening obstructive sleep apnea

OBJECTIVES

Obstructive Sleep Apnea (OSA) is a kind of respiratory disease that occurs apnea repeatedly during sleep. The purpose of this study was to investigate the influence of sex on anthropometric methods and four scales for screening OSA.

METHODS

The basic data and PSG data of 2108 patients who underwent PSG examination at the Sleep Medicine Center of the First Affiliated Hospital of Guangzhou Medical University from July 2017 to December 2020 were continuously included. Then the sensitivity, specificity, positive predictive value, negative predictive value, AUC and DOR of the anthropometric method and the four scales were calculated.

RESULTS

2108 OSA patients were enrolled from the Sleep Medicine Center, including 1644 males (78.0%). The average neck circumference and waist circumference of male and female patients were respectively (39.4±3.4) cm and (96.7±13.8) cm,(34.6±3.5) cm and (90.1±11.6) cm. In female patients. the AUC of NoSAS was the largest. When AHI was 5, 15, and 30 evens/h as the cut-off point, in male patients, the sensitivity of NHR was the highest,in female patients, the sensitivity of WHR was the highest.

CONCLUSIONS

NHR and WHR are good tools for screening OSA in male and female patients respectively. They are worthy of promotion.

Comparison of six assessment tools to screen for obstructive sleep apnea in patients with hypertension

Background

Obstructive sleep apnea (OSA) is often accompanied by other complications, especially hypertension.

Hypothesis

The purpose of this study is to compare the application value of six tools in the screening of OSA in patients with hypertension. Compared with other questionnaires, we hypothesized that Berlin performed better in screening hypertensive patients suspected of OSA.

Methods

In this study, we collected the basic data and polysomnography (PSG) data of patients diagnosed with hypertension who underwent PSG at the Sleep Medicine Center of the First Affiliated Hospital of Guangzhou Medical University from April 2012 to March 2021. The sensitivity, specificity, positive predictive value, negative predictive value, area under the curv (AUC) and diagnostic odds ratio (DOR) of the six screening tools were then calculated, and their correlation with the sleep apnea hypopnea index (AHI) analyzed.

Results

There were 303 males (303/398, 76.1%) out of 398 hypertension patients suspected of OSA. The area under the curve of the Berlin questionnaire's receiver operating characteristic (ROC) curve reached 0.753 (95%CI: 0.707–0.794). When the AHI was 5, 15 and 30 times/h as the cut‐off points, the sensitivity and negative predictive value of Berlin were the highest at 0.947 and 0.630, 0.970 and 0.851, and 0.988 and 0.957 respectively, while the specificity and positive predictive value of the Epworth Sleepiness Scale (ESS) were the highest at 0.696 and 0.729, 0.750 and 0.887, and 0.674 and 0.575 respectively. The DOR value of the Berlin questionnaire could reach 18.333 when the AHI cut‐off point was 30 times/h. Berlin had the largest rank correlation coefficient with AHI at 0.466.

Conclusion

The Berlin questionnaire can be considered a priority for the screening and stratifying of hypertensive patients suspected of OSA.

BASAN index (Body mass index, Age, Sex, Arterial hypertension and Neck circumference) predicts severe apnoea in adults living at high altitude

OBJECTIVES

Obstructive sleep apnoea (OSA)/hypopnoea syndrome is associated with serious and major multiorgan morbidities, particularly in its most severe forms. However, no severe OSA screening instruments are available for high altitude residents that enable adequate identification and clinical prioritisation of such patients. We aimed at developing a severe OSA prediction tool based on the clinical characteristics and anthropometric measurements of a clinical referral cohort living at 2640 m.a.s.l.

DESIGN

Cohort-nested cross-sectional study.

SETTING

Sleep laboratory for standard polysomnography (PSG) in Colombia.

PARTICIPANTS

A predictive model was generated from 8718 participants referred to the PSG laboratory. Results were subsequently validated in a second cohort of 1898 participants.

PRIMARY OUTCOME

To identify clinical and anthropometric variables associated with severe OSA (>30 events/hour) and to include them in a binary logistic regression model.

RESULTS

The significant variables that were retained with the presence of severe OSA included Body mass index (BMI), Age, Sex, Arterial hypertension and Neck circumference (BASAN). The area under the receiver operating characteristic curvefor the BASAN index was 0.69 (95% CI: 0.68 to 0.70) in the derivation cohort and 0.67 (95% CI: 0.65 to 0.69) in the validation cohort, whereby a BASAN index ≥2 had a sensitivity of 95% and a specificity of 17% to detect severe OSA.

CONCLUSION

An objectively based approach to screen for the presence of severe OSA, the BASAN index, exhibits favourable sensitivity characteristics that should enable its operational use as a screening tool in a Hispanic population with a clinical suspicion of OSA and living at high altitude.

A meta-analysis of the diagnostic value of NoSAS in patients with sleep apnea syndrome

OBJECTIVE

The NoSAS score is a new tool widely used in recent years to screen for obstructive sleep apnea. A number of studies have shown that the NoSAS score is more accurate than previous tools, such as the Berlin, STOP-Bang, and STOP questionnaires. Therefore, this meta-analysis assessed the diagnostic value of the NoSAS score for sleep apnea syndrome in comparison to polysomnography.

METHODS

Two researchers searched the PubMed, EMBASE, Cochrane, and Web of Science databases through November 13, 2020. This paper used Endnote9.3 software to manage the literature and RevMan 5.3 and STATA12.0 software to perform the meta-analysis.

RESULTS

A total of 10 studies were included in this meta-analysis, including 14,510 patients. The meta-analysis showed that the pooled sensitivity was 0.798 (95% CI 0.757, 0.833), the pooled specificity was 0.582 (95% CI 0.510, 0.651), the positive likelihood ratio was 1.909 (95% CI 1.652, 2.206), the negative likelihood ratio was 0.347 (95% CI 0.300, 0.403), the diagnostic OR was 5.495 (95% CI 4.348, 6.945), and the area under the SROC curve was 0.77 (95% CI 0.73, 0.80). The NoSAS score has good efficacy in identifying patients likely to have obstructive sleep apnea.

CONCLUSION

The NoSAS score can accurately identify patients likely to have obstructive sleep apnea. Therefore, in the absence of polysomnography, one should use the NoSAS score to evaluate patients with suspected sleep apnea syndrome.

Prevalence of obstructive sleep apnea at an outpatient memory clinic

OBJECTIVES

Obstructive sleep apnea (OSA) is a common sleep disorder that has several health hazards, including cognitive dysfunction. Studies have thus far primarily focussed on the prevalence of cognitive impairment in patients diagnosed with OSA at sleep clinics. The present study aims to investigate the prevalence of OSA at an outpatient memory clinic.

METHODS

A dataset of patients who visited our memory clinic in the period from June 2015 to September 2019 was retrospectively examined for the presence of OSA. The primary outcome measure was the prevalence of OSA, subdivided into three cognitive syndrome diagnosis groups: subjective cognitive complaints (SCC), mild cognitive impairment and dementia. Secondary outcome measures included age, education level, body mass index, substance use, depression and OSA criteria.

RESULTS

Of the 885 patients included in this study, 153 patients had already been or were diagnosed with OSA (17.3%). The percentage of OSA in the SCC group was significantly higher compared with the dementia group (26.7% vs 8.0%; OR 3.83 [95%CI 2.43-5.99]). Age differed significantly between the SCC group and the dementia group: 63.5 vs 71.5 years (7.6 ± 1.810; P < .001). Higher education level was associated with a lower prevalence of dementia compared to SCC (OR 0.068[95%CI 0.008-0.588]). Severity parameters of OSA did not show significant differences across the various cognitive syndrome diagnosis groups.

CONCLUSIONS

Prevalence of OSA at our outpatient memory clinic is generally high. Especially in patients with SCC. We would therefore advocate screening for OSA at memory clinics.

Prediction of obstructive sleep apnea using GOAL questionnaire in adults with or without excessive daytime sleepiness: A cross-sectional study

OBJECTIVE

Obstructive sleep apnea (OSA) is a prevalent disorder and excessive daytime sleepiness (EDS) is a frequently associated complaint. Our objectives were (1) to evaluate the predictive performance of the GOAL questionnaire in patients with or without EDS and (2) to compare its discrimination with that of 3 other validated instruments: STOP-Bang, No-Apnea, and NoSAS.

METHODS

A cross-sectional study from July 2019 to March 2020 was designed with consecutive adults undergoing full polysomnography. Participants were grouped into 2 cohorts according to the Epworth Sleepiness Scale (ESS): without EDS (ESS <11) or with EDS (ESS ≥11). Discrimination was assessed by area under the curve, while predictive parameters were calculated using contingency tables. OSA severity was classified based on apnea/hypopnea index thresholds: ≥ 5.0/h (OSA_≥5), ≥ 15.0/h (OSA_≥15), and ≥ 30.0/h (OSA_≥30).

RESULTS

Overall, 2627 patients were enrolled. In 1477 individuals without EDS, for the screening of OSA_≥5, OSA_≥15, and OSA_≥30, GOAL showed sensitivities ranging from 79.3% to 91.5% and specificities ranging from 60.6% to 40.2%. In 1150 individuals with EDS, for the screening of OSA_≥5, OSA_≥15, and OSA_≥30, GOAL reported sensitivities ranging from 86.2% to 94.5% and specificities ranging from 63.9% to 36.0%. In both cohorts, GOAL showed similar discrimination to STOP-Bang, No-Apnea, and NoSAS for predicting OSA_≥5, OSA_≥15, and OSA_≥30 (all P values >.05).

CONCLUSIONS

The GOAL questionnaire, a practical 4-item instrument, showed adequate predictive performance for the prediction of OSA. Moreover, its discrimination was satisfactory and non-inferior to that of STOP-Bang, No-Apnea, and NoSAS.

Prediction of obstructive sleep apnea: comparative performance of three screening instruments on the apnea-hypopnea index and the oxygen desaturation index

Purpose

To evaluate the performance of the NoSAS (neck, obesity, snoring, age, sex) score, the STOP-Bang (snoring, tiredness, observed apneas, blood pressure, body mass index, age, neck circumference, gender) questionnaire, and the Epworth sleepiness score (ESS) as a screening tool for obstructive sleep apnea (OSA) severity based on the apnea-hypopnea index (AHI) and the oxygen desaturation index (ODI).

Methods

Data from 235 patients who were monitored by ambulant polysomnography (PSG) were retrospectively analyzed. OSA severity was classified based on the AHI; similar classification categories were made based on the ODI. Discrimination was assessed by the area under the curve (AUC), while predictive parameters were calculated by four-grid contingency tables.

Results

The NoSAS score and the STOP-Bang questionnaire were both equally adequate screening tools for the AHI and the ODI with AUC ranging from 0.695 to 0.767 and 0.684 to 0.767, respectively. Both questionnaires perform better when used as a continuous variable. The ESS did not show adequate discrimination for screening for OSA (AUC ranging from 0.450 to 0.525). Male gender, age, and BMI proved to be the strongest individual predictors in this cohort.

Conclusion

This is the first study to evaluate the predictive performance of three different screening instruments with respect to both the AHI and the ODI. This is important, due to increasing evidence that the ODI may have a higher reproducibility in the clinical setting. The NoSAS score and the STOP-Bang questionnaire proved to be equally adequate to predict OSA severity based on both the AHI and the ODI.

Electronic supplementary material

The online version of this article (10.1007/s11325-020-02219-6) contains supplementary material, which is available to authorized users.

Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic

Background

There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies.

Aim

To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire.

Methods

We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening.

Results

Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI ≥ 5), moderate-to-severe (AHI ≥ 15), and severe (AHI ≥ 30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655–0.775) of diagnosing SDB at AHI cutoff of ≥5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046).

Conclusion

The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice.

Obstructive Sleep Apnea Screening with a 4-Item Instrument, Named GOAL Questionnaire: Development, Validation and Comparative Study with No-Apnea, STOP-Bang, and NoSAS

BACKGROUND

Obstructive sleep apnea (OSA) is a very prevalent disorder. Here, we aimed to develop and validate a practical questionnaire with yes-or-no answers, and to compare its performance with other well-validated instruments: No-Apnea, STOP-Bang, and NoSAS.

METHODS

A cross-sectional study containing consecutively selected sleep-lab subjects underwent full polysomnography. A 4-item model, named GOAL questionnaire (gender, obesity, age, and loud snoring), was developed and subsequently validated, with item-scoring of 0-4 points (≥2 points indicating high risk for OSA). Discrimination was assessed by area under the curve (AUC), while predictive parameters were calculated using contingency tables. OSA severity was classified based on conventionally accepted apnea/hypopnea index thresholds: ≥5.0/h (OSA_≥5), ≥15.0/h (OSA_≥15), and ≥30.0/h (OSA_≥30).

RESULTS

Overall, 7377 adults were grouped into two large and independent cohorts: derivation (n = 3771) and validation (n = 3606). In the derivation cohort, screening of OSA_≥5, OSA_≥15, and OSA_≥30 revealed that GOAL questionnaire achieved sensitivity ranging from 83.3% to 94.0% and specificity ranging from 62.4% to 38.5%. In the validation cohort, screening of OSA_≥5, OSA_≥15, and OSA_≥30, corroborated validation steps with sensitivity ranging from 83.7% to 94.2% and specificity from 63.4% to 37.7%. In both cohorts, discriminatory ability of GOAL questionnaire for screening of OSA_≥5, OSA_≥15, and OSA_≥30 was similar to No-Apnea, STOP-Bang or NoSAS.

CONCLUSION

All four instruments had similar performance, leading to a possible greater practical implementation of the GOAL questionnaire, a simple instrument with only four parameters easily obtained during clinical evaluation.

Co-Morbid Insomnia and Sleep Apnea (COMISA): Prevalence, Consequences, Methodological Considerations, and Recent Randomized Controlled Trials

Co-morbid insomnia and sleep apnea (COMISA) is a highly prevalent and debilitating disorder, which results in additive impairments to patients' sleep, daytime functioning, and quality of life, and complex diagnostic and treatment decisions for clinicians. Although the presence of COMISA was first recognized by Christian Guilleminault and colleagues in 1973, it received very little research attention for almost three decades, until the publication of two articles in 1999 and 2001 which collectively reported a 30%-50% co-morbid prevalence rate, and re-ignited research interest in the field. Since 1999, there has been an exponential increase in research documenting the high prevalence, common characteristics, treatment complexities, and bi-directional relationships of COMISA. Recent trials indicate that co-morbid insomnia symptoms may be treated with cognitive and behavioral therapy for insomnia, to increase acceptance and use of continuous positive airway pressure therapy. Hence, the treatment of COMISA appears to require nuanced diagnostic considerations, and multi-faceted treatment approaches provided by multi-disciplinary teams of psychologists and physicians. In this narrative review, we present a brief overview of the history of COMISA research, describe the importance of measuring and managing insomnia symptoms in the presence of sleep apnea, discuss important methodological and diagnostic considerations for COMISA, and review several recent randomized controlled trials investigating the combination of CBTi and CPAP therapy. We aim to provide clinicians with pragmatic suggestions and tools to identify, and manage this prevalent COMISA disorder in clinical settings, and discuss future avenues of research to progress the field.