Scoring criteria for portable monitor recordings: a comparison of four hypopnoea definitions in a population-based cohort

Vat, Sopharat; Haba‐Rubio, José; Tafti, Mehdi; Tobback, Nadia; Andries, Daniela; Heinzer, Raphaël

doi:10.1136/thoraxjnl-2014-205982

Cited by 32 publications

(35 citation statements)

References 36 publications

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“…Type 3 monitors lack EEG signals for determination of sleep times that may lead to inaccurate AHI estimations. However, a recent study comparing type 3 portable monitor device with PSG in a general population sample found that portable monitor AHI had good concordance with PSG AHI …”

Section: Discussionmentioning

confidence: 95%

Prevalence of sleep‐disordered breathing in a multiethnic Asian population in Singapore: A community‐based study

et al. 2016

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Background and objective: Limited data exist on the prevalence variation in sleep-disordered breathing (SDB) across different Asian ethnicities. This population study aimed to estimate the prevalence of SDB in Singapore, a multiethnic nation, and to quantify the prevalence variation among Chinese, Malays and Indians. Methods: The Singapore Health Study 2012 was a cross-sectional population study conducted on adults aged 21-79 years. Among 2329 participants who completed baseline examination, a sample of 242 subjects completed home-based sleep testing with an Embletta device (type 3 monitor). Moderate-to-severe SDB, defined as an apnoea-hypopnoea index (AHI) of ≥15 events/h, was used to estimate prevalence. Results: The weighted estimates of the population prevalence of moderate-to-severe SDB and sleep apnoea syndrome were 30.5% and 18.1%, respectively. Of subjects with AHI ≥15, 91.0% were previously undiagnosed. Moderate-to-severe SDB prevalence varied across the Chinese (32.1%), Malays (33.8%) and Indians (16.5%). The mean body mass index (BMI) was lowest in Chinese (23.3 kg/m 2 ) and highest among Malays (26.0 kg/m 2 ) and Indians (25.4 kg/m 2 ). Compared with Chinese, Indians had lower odds of moderate-to-severe SDB after adjustment for age, sex and BMI (odds ratio 0.82, 95% CI: 0.70-0.96, P = 0.02). Conclusion: Sleep-disordered breathing is prevalent but mostly undiagnosed among Asians in Singapore. There was a lower prevalence of SDB among Indians compared with Chinese that remained after adjustment for age, sex and BMI. Strategies are needed to optimize diagnosis and recognize ethnic differences in SDB prevalence.

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Section: Discussionmentioning

confidence: 95%

Prevalence of sleep‐disordered breathing in a multiethnic Asian population in Singapore: A community‐based study

et al. 2016

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“…In fact, rescoring with only portable monitor parameters using a 3% desaturation criteria, which was similar to what we used for our primary analysis, had the best diagnostic accuracy. 26 In conclusion, we found that the Berlin questionnaire may be used as a screening tool in the general population in view of its good sensitivity and high negative predictive value in ruling out severe OSA.…”

Section: -23mentioning

confidence: 99%

Using the Berlin Questionnaire to Predict Obstructive Sleep Apnea in the General Population

Tan

Yin

Tan

et al. 2017

Journal of Clinical Sleep Medicine

104

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Study Objectives: The Berlin questionnaire is a self-administered questionnaire that was developed to identify subjects with obstructive sleep apnea (OSA) in primary care settings. This study evaluated the performance of the questionnaire to predict OSA in the general population. Methods: A sample of 242 subjects in a population-based cohort completed a home-based sleep study with an Embletta device (type 3 monitor). Subjects completed the Berlin questionnaire on the evening just prior to the sleep study. The sleep studies were manually scored according to the 2012 American Academy of Sleep Medicine (AASM) criteria. Results: The prevalence of moderate-to-severe and severe OSA defined as apnea-hypopnea index (AHI) of ≥ 15 and ≥ 30 was 28.1% and 10.7%, respectively. Seventy-nine subjects (32.6%) were classified as high risk according to the Berlin questionnaire. The sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) of the questionnaire to predict an AHI ≥ 15 was 58.8%, 77.6%, 82.9%, and 50.6%, respectively. The area under the receiving operator characteristic (ROC) curve for moderate-to-severe OSA was 0.682. When used to predict an AHI ≥ 30, the sensitivity of the questionnaire increased to 76.9% with a small drop in specificity to 72.7%. The corresponding NPV, PPV, and area under the ROC curve of the questionnaire to predict severe OSA were 96.3%, 25.3%, and 0.748, respectively. Conclusions: The Berlin questionnaire may have utility in the general population setting as a screening tool for OSA in view of its good sensitivity and high NPV in ruling out severe OSA.

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“…irdly, we diagnosed SDB based on type III portable monitor rather than inlaboratory polysomnography, the gold standard method for SDB diagnosis. A previous population-based study showed a good AHI concordance between portable monitors and polysomnography, but portable monitors tended to slightly underestimate AHI [22]. However, in the present study, portable monitoring was conducted in hospital by trained clinicians, instead of at home by the patients themselves, to ensure the accuracy of the testing and reducing the discordance.…”

Section: Discussionmentioning

confidence: 79%

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

Rong

Wang

et al. 2020

Canadian Respiratory Journal

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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.

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Scoring criteria for portable monitor recordings: a comparison of four hypopnoea definitions in a population-based cohort

Abstract: Interpretation of PM recordings using hypopnoea criteria which include 3% desaturation without PWA drops as EEG arousal surrogate showed the best diagnosis accuracy compared with full PSG.

Cited by 32 publications

References 36 publications

Prevalence of sleep‐disordered breathing in a multiethnic Asian population in Singapore: A community‐based study

Prevalence of sleep‐disordered breathing in a multiethnic Asian population in Singapore: A community‐based study

Using the Berlin Questionnaire to Predict Obstructive Sleep Apnea in the General Population

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

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