BASET scoring: A novel simple biometric score for screening and grading obstructive sleep apnea

Abdelbaset M Saleh; Magda A Ahmed; Eman A El Said; Nabil J Awadalla; Amira A M M Attia

doi:10.1016/j.sleepx.2023.100083

BASET scoring: A novel simple biometric score for screening and grading obstructive sleep apnea

Sleep Med X. 2023 Aug 14:6:100083. doi: 10.1016/j.sleepx.2023.100083. eCollection 2023 Dec 15.

Authors

Abdelbaset M Saleh¹, Magda A Ahmed¹, Eman A El Said¹, Nabil J Awadalla², Amira A M M Attia³

Affiliations

¹ Department of Chest Medicine, Sleep Disordered Breathing Unit, Faculty of Medicine, Mansoura University, Egypt.
² Department of Public Health and Community Medicine, Faculty of Medicine Mansoura University, Egypt.
³ Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Mansoura University, Egypt.

Abstract

Background: 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.

Objectives: Our study aimed to assess the validity of BASET scoring as a new potential tool for screening and grading the severity of OSA patients.

Methods: 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: B= Body Mass Index (BMI), A= Abdominal circumference (AC), S = Snoring, E= 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.

Results: 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.

Conclusion: 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.

Registration of clinical trials by number: NCT05511974.

Name of the registry: ClinicalTrials.gov URL: https://clinicaltrials.gov/.

Keywords: BASET score; Berlin questionnaire; OSA; STOP-Bang; Validity.

Associated data

ClinicalTrials.gov/NCT05511974