Saleh Abdelbaset M, Ahmed Magda A, El Said Eman A, Awadalla Nabil J, Attia Amira A M M
Department of Chest Medicine, Sleep Disordered Breathing Unit, Faculty of Medicine, Mansoura University, Egypt.
Department of Public Health and Community Medicine, Faculty of Medicine Mansoura University, Egypt.
Sleep Med X. 2023 Aug 14;6:100083. doi: 10.1016/j.sleepx.2023.100083. eCollection 2023 Dec 15.
Polysomnography (PSG) is the gold-standard diagnostic tool for Obstructive Sleep Apnea (OSA). However, the availability of PSG is limited, and OSA is widely underdiagnosed; more than 80% of most developed nations undiagnosed. There is no diagnostic validated simple tool with clear cutoff point for predicting and roll out patient with OSA in primary care clinics significantly alters clinical outcomes.
Our study aimed to assess the validity of BASET scoring as a new potential tool for screening and grading the severity of OSA patients.
After institution review board approval and formal patient consent, 144 subjects for suspected OSA and their relatives were enrolled. All subjects were subjected to a full night PSG study after history taking, sleep questionnaires, and physical examination, including BASET score components: = Body Mass Index (BMI), = Abdominal circumference (AC), S = Snoring, = Epworth Sleepiness Scale, and T= Tongue teeth imprint. ROC analysis that used to assess the optimal cutoff point of the BASET score and to compare its accuracy for predicting OSA with Berlin and STOP-Bang scores.
This study included 63 OSAS patients, 33 (52.38%) males and 30 (47.62%) females, and 81 controls; 22 (27.16%) males and 50 (72.84%) females. The Cronbach's alpha for the 5 BASET score components was 0.846, indicating the internal consistency reliability of the scale. Moreover, BASET score has a moderately strong positive significant correlation (r = 0.778, p<0.001) with AHI. By ROC analysis, the accuracy of the three measures was generally high, with BASET score predicting OSA most accurately (AUC=0.984, 95%CI: 0.956-0.999), followed by STOP-Bang (AUC=0.939, 95%CI: (0.887-0.972) and Berlin (AUC=0.901, 95%CI: 0.841-0.945). The AUC of BASET score was significantly higher compared to the Berlin score (difference= 0.0825, 95%CI: 0.039-0.125) and STOP-Bang score (difference= 0.0447, 95%CI: 0.011-0.078). On the other hand, there was no difference between the AUC of Berlin and STOP-Bang scores (difference=0.0378, 95%CI: 0.006 - 0.081 4). BASET score was significantly (p<0.001) associated with OSA grades.
BASET score is a convenient, reliable, and valid tool for diagnosing OSA. BASET score is more accurate for predicting OSA than Berlin and STOP-Bang scores, while there is no difference between Berlin and STOP-Bang scores. BASET score indicates OSA grades.
NCT05511974.
ClinicalTrials.gov URL: https://clinicaltrials.gov/.
多导睡眠图（PSG）是阻塞性睡眠呼吸暂停（OSA）的金标准诊断工具。然而，PSG的可用性有限，OSA普遍诊断不足；在大多数发达国家，超过80%的患者未被诊断。在基层医疗诊所中，尚无经过诊断验证的、具有明确临界点的简单工具来预测和筛查OSA患者，这显著改变了临床结果。
我们的研究旨在评估BASET评分作为一种筛查和分级OSA患者严重程度的新潜在工具的有效性。
在获得机构审查委员会批准并获得患者正式同意后，招募了144名疑似OSA患者及其亲属。在进行病史采集、睡眠问卷和体格检查后，所有受试者均接受了整夜的PSG研究，包括BASET评分的组成部分：=体重指数（BMI），=腹围（AC），S =打鼾，=爱泼华嗜睡量表，以及T =舌齿印。采用ROC分析来评估BASET评分的最佳临界点，并将其预测OSA的准确性与柏林评分和STOP-Bang评分进行比较。
本研究包括63例OSAS患者，其中男性33例（52.38%），女性30例（47.62%），以及81名对照者；男性22例（27.16%），女性50例（72.84%）。BASET评分5个组成部分的Cronbach's alpha为0.846，表明该量表的内部一致性可靠性。此外，BASET评分与呼吸暂停低通气指数（AHI）具有中等强度的显著正相关（r = 0.778，p<0.001）。通过ROC分析，这三种测量方法的准确性总体较高，其中BASET评分预测OSA最准确（曲线下面积[AUC]=0.984，95%可信区间：0.956 - 0.999），其次是STOP-Bang评分（AUC = 0.939，95%可信区间：0.887 - 0.972）和柏林评分（AUC = 0.901，95%可信区间：0.841 - 0.945）。与柏林评分相比，BASET评分的AUC显著更高（差异 = 0.0825，95%可信区间：0.039 - 0.125），与STOP-Bang评分相比也显著更高（差异 = 0.0447，95%可信区间：0.011 - 0.078）。另一方面，柏林评分和STOP-Bang评分的AUC之间没有差异（差异 = 0.0378，95%可信区间：0.006 - 0.0814）。BASET评分与OSA分级显著相关（p<0.001）。
BASET评分是一种方便、可靠且有效的OSA诊断工具。BASET评分在预测OSA方面比柏林评分和STOP-Bang评分更准确，而柏林评分和STOP-Bang评分之间没有差异。BASET评分可指示OSA分级。
NCT05511974。
ClinicalTrials.gov
