• Zhonghua Jie He He Hu Xi Za Zhi · Jun 2015

    [The applications of the STOP-Bang questionnaire in screening obstructive sleep apnea in patients with metabolic syndrome].

    • Yunjie Teng, Yan Xiong, and Ning Wang.
    • Department of No.1 Cadre Ward Medicine, First Affiliated Hospital, Xinjiang Medical University, Urumqi 830054, China.
    • Zhonghua Jie He He Hu Xi Za Zhi. 2015 Jun 1; 38 (6): 461-6.

    ObjectiveTo evaluate the predictive performance of the STOP-Bang questionnaire screening obstructive sleep apnea (OSA) in patients with metabolic syndrome(MS).MethodsFrom May 2013 to September 2014, patients with MS were recruited at the First Affiliated Hospital of Xinjiang Medical University. We applied the STOP questionnaire to these patients. Information concerning Bang was collected. Portable polysomnography (PSG) was performed in these patients. There were 317 patients with successful PSG and completed STOP-Bang questionnaire results. The results of the STOP-Bang sore and PSG were compared, and their crude accuracy, kappa index and correlation were analyzed. Fourfold table was used to calculate sensitivity, specificity, positive predictive value, and negative predictive values for each score, and the area under receiver operating characteristic (ROC) curve was calculated.ResultsAs the components of the questionnaire, loud snore, observed apnea, gender, age, neck circumference worked well to identify OSA patient with MS. The STOP-Bang score showed an increase with increased severity of OSA (2.30 ± 1.01, 3.48 ± 1.30, 3.82 ± 1.26, 4.57 ± 1.43). In 317 MS patients, a STOP-Bang score of 3 had a high sensitivity of 86.36% and a reasonable sensitivity of 50.94% for identifying MS patient with OSA. When predicting all OSA, moderate/severe OSA or severe OSA, a STOP-Bang score of 4 had a higher accuracy. Using the STOP-Bang score to predict MS patients with all OSA (AHI ≥ 5), moderate/severe OSA (AHI>15), and severe OSA (AHI>30), the area under the ROC curve was 0.824 (95%CI: 0.771-0.876), 0.851 (95%CI: 0.801-0.901), 0.892 (95%CI: 0.843-0.941), respectively (P<0.001).ConclusionThe STOP-Bang questionnaire has high accuracy and feasibility in screening OSA and can predict the severity of OSA among patients with MS.

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