Evaluating the performance of five scoring systems for prescreening obstructive sleep apnea-hypopnea syndrome

Wang, Wenjing; Su, Yuan; Grange, Jehane Michael Le; Zheng, Hongzhi; Yao, Tianci; Peng, Wei; Zhang, J

doi:10.1007/s11325-020-02227-6

Cited by 6 publications

(5 citation statements)

References 29 publications

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“…Xiong et al, in a 2019 study on five questionnaires in screening COPD patients with OSA showed that SACS had a moderate predictive value in screening severe OSA, with an AUC of 0.750 (Xiong et al, 2019). While Wang et al (2021) showed that SACS had excellent sensitivity (93.4-94.6%) and a negative predictive value (77.3-90.9%) in evaluating the prevalence of OSA in patients with COPD. In our study, SACS has a good predictive value, but there are few studies on the predictive value of SACS in COPD patients with OSA, and more studies are still needed.…”

Section: Discussionmentioning

confidence: 99%

A risk-predictive model for obstructive sleep apnea in patients with chronic obstructive pulmonary disease

Peng

Wang

et al. 2023

Front. Neurosci.

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BackgroundObstructive sleep apnea syndrome (OSA) is increasingly reported in patients with chronic obstructive pulmonary disease (COPD). Our research aimed to analyze the clinical characteristics of patients with overlap syndrome (OS) and develop a nomogram for predicting OSA in patients with COPD.MethodsWe retroactively collected data on 330 patients with COPD treated at Wuhan Union Hospital (Wuhan, China) from March 2017 to March 2022. Multivariate logistic regression was used to select predictors applied to develop a simple nomogram. The area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the value of the model.ResultsA total of 330 consecutive patients with COPD were enrolled in this study, with 96 patients (29.1%) confirmed with OSA. Patients were randomly divided into the training group (70%, n = 230) and the validation group (30%, n = 100). Age [odds ratio (OR): 1.062, 1.003–1.124], type 2 diabetes (OR: 3.166, 1.263–7.939), neck circumference (NC) (OR: 1.370, 1.098–1,709), modified Medical Research Council (mMRC) dyspnea scale (OR: 0.503, 0.325–0.777), Sleep Apnea Clinical Score (SACS) (OR: 1.083, 1.004–1.168), and C-reactive protein (CRP) (OR: 0.977, 0.962–0.993) were identified as valuable predictors used for developing a nomogram. The prediction model performed good discrimination [AUC: 0.928, 95% confidence interval (CI): 0.873–0.984] and calibration in the validation group. The DCA showed excellent clinical practicability.ConclusionWe established a concise and practical nomogram that will benefit the advanced diagnosis of OSA in patients with COPD.

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Section: Discussionmentioning

confidence: 99%

A risk-predictive model for obstructive sleep apnea in patients with chronic obstructive pulmonary disease

Peng

Wang

et al. 2023

Front. Neurosci.

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“…SBQ is a part-self-administered questionnaire based on the Berlin instrument, and includes both subjective symptoms and objective indicators; the design is thus more reasonable than that of the ESS. SBQ is an acronym derived from the first letters of the questions ( 18 , 19 ), facilitating completion of the instrument. Many researchers consider SBQ to be one of the best measures for OSA screening.…”

Section: Discussionmentioning

confidence: 99%

“…A recent report also indicated that SBQ was diagnostically more accurate than the ESS ( 10 ). However, similar to most questionnaires, SBQ affords high sensitivity but only low specificity when diagnosing mild, moderate, and severe OSA ( 12 , 13 ), and no one cutoff is appropriate for all populations ( 14 , 18 ). We found that SBQ was moderately effective when used to predict moderate-to-severe OSA, and the performance was better than ESS and NoSAS.…”

Section: Discussionmentioning

confidence: 99%

“…The NoSAS score has been widely used including Chinese ( 16 , 17 ), and the final score can range from 0–17, with 4 points for an NC ≥40 cm; 3 for a BMI 25–30 kg/m 2 or 5 for a BMI ≥30 kg/m 2 ; 2 for snoring; 4 for age ≥55 years; and 2 for being male. The SBQ features eight questions exploring snoring (S), tiredness (T), observed breathing cessation (O), blood pressure (P), BMI (B), age (A), NC, and gender (G) with better performance in Chinese ( 18 , 19 ).…”

Section: Methodsmentioning

confidence: 99%

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An effective model for screening moderate-to-severe obstructive sleep apnea based on the STOP-BANG questionnaire

Wang¹,

Xu²,

Jiang³

et al. 2022

J Thorac Dis

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Background: This study aimed to develop a more effective screening model for moderate-to-severe obstructive sleep apnea (OSA) based on the best tool among Epworth Sleepiness Scale (ESS), NoSAS score and STOP-BANG questionnaire (SBQ). Methods: This study screened 2,031 consecutive subjects referred with suspected OSA from 2012 to 2016, including the test cohort from 2012 to 2014 and the validation cohort from 2014 to 2016. Anthropometric measurements, polysomnographic data, ESS, NoSAS scores and SBQ scores were recorded. Receiver operating characteristic curve analyses were performed and the final predictive models were verified in a validation cohort.Results: A total of 1,840 adults were finally included. The performance of ESS, NoSAS score and SBQ in screening OSA was compared. The diagnostic accuracy of SBQ was superior to ESS and NoSAS. A predictive model based on SBQ yielded an area under the curve (AUC) of 0.931 (95% CI: 0.915-0.946), and the sensitivity and specificity were 84.47 (95% CI: 81.4-87.2) and 87.36 (95% CI: 83.9-90.3) respectively.In the validation cohort, the AUC was 0.955 (95% CI: 0.938-0.969), with a sensitivity and specificity of 86.79 (95% CI: 83.2-89.9) and 90.88 (95% CI: 87.2-93.8) respectively. In addition, the model performed moderately in screening mild OSA with the AUC being 0.771 (95% CI: 0.721-0.815). Conclusions:The SBQ was effective in screening moderate-to-severe OSA. And a SBQ -based predictive model afforded excellent diagnostic efficacy, which could be applied in clinical practice.

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“…10,11 Gong et al found that although the ESS alone has acceptable clinical predictive value for OSAHS patients with hypertension, but the severity of OSAHS could not be precisely predicted from ESS score. 12 Therefore, it is rationale to take the advantages of two or more approaches via combination, and evaluation of the screening ability upon combining these questionnaires is lacking. Considering that the ESS score is mainly based on subjective cognition and the SBQ scores are mainly based on objective index, we develop a screening approach by weighted combining the ESS and SBQ based on calculation and evaluate its predicting values for OSAHS in Chinese hypertensive patients.…”

Section: Introductionmentioning

confidence: 99%

The Weighted Combination of the Epworth Sleepiness Scale and the STOP-Bang Questionnaire Improved the Predictive Value of for OSAHS in Hypertensive Patients

Sun¹,

Xu²,

Wang³

et al. 2022

IJGM

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Hypertension interrelated with obstructive sleep apnea hypopnea syndrome (OSAHS), worsening morbidity and mortality. It is urgent to screening OSAHS from hypertensive patients. An ideal effective questionnaire screening approach for OSAHS is lacking. In this study, we aimed to explore a new OSAHS screening method via weighted combining the current used Epworth sleepiness scale (ESS) and STOP-Bang questionnaire (SBQ) upon calculation. Patients and Methods: Three hundred and sixteen hypertensive patients with suspicion of the OSAHS were enrolled and randomized in the study into ESS, SBQ and portable respiratory polysomnography (RP) tests. The predictive value of ESS, SBQ and weighted combination were evaluated by calculating the area under curve (AUC), sensitivity and specificity, positive and negative likelihood ratio. Results: Both the two scales alone and weighted combination were closely related with apnea hypopnea index (AHI), minimum oxygen saturation and average oxygen saturation at night (P < 0.05). The AUC, sensitivity and specificity, positive predictive value (PPV) and negative predictive value (NPV) of ESS in predicting OSAHS were 79.

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Evaluating the performance of five scoring systems for prescreening obstructive sleep apnea-hypopnea syndrome

Cited by 6 publications

References 29 publications

A risk-predictive model for obstructive sleep apnea in patients with chronic obstructive pulmonary disease

A risk-predictive model for obstructive sleep apnea in patients with chronic obstructive pulmonary disease

An effective model for screening moderate-to-severe obstructive sleep apnea based on the STOP-BANG questionnaire

The Weighted Combination of the Epworth Sleepiness Scale and the STOP-Bang Questionnaire Improved the Predictive Value of for OSAHS in Hypertensive Patients

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