The Usefulness of Sleep Subdomain of SNOT-22 as a Screening Tool for Obstructive Sleep Apnea in Patients with Chronic Rhinosinusitis

Introduction: Comorbid obstructive sleep apnea (OSA) is seen in up to 20% of patients with chronic rhinosinusitis (CRS) undergoing endoscopic sinus surgery (ESS) and can lead to increased perioperative morbidity. While there are tools to assess for OSA such as the STOP-BANG, preoperative screening for OSA is not universally performed. The Sinonasal Outcomes Test-22 (SNOT-22) is one of the most common questionnaires administered preoperatively to patients undergoing ESS. The sleep subdomain is one of the four subdomains of SNOT-22. The objective of this study was to assess if the sleep subdomain score of SNOT-22 (SD-SNOT) can be utilized as a surrogate to screen for OSA in patients undergoing ESS for CRS.

Methods: Patients from a tertiary care center were included if they underwent ESS for CRS between 2017 and 2021. SD-SNOT, STOP-BANG scores, and OSA status were collected. Preoperative and postoperative (less than 8 weeks) SD-SNOT scores were compared with OSA status. Receiver operating characteristic curve was utilized to assess the cutoff scores, sensitivity, and specificity for the prediction of OSA using pre -and postoperative SD-SNOT and STOP-BANG scores.

Results: Out of 563 patients, 7% (n = 41) had documented OSA. Comparison of OSA and non-OSA groups revealed that patients with OSA were 2.1 times more likely to be male (68 vs. 49.5%; p = 0.02), older (55.24 ± 10.09 vs. 48.92 ± 18.42 years; p = 0.03), and with higher BMI (31.9 ± 5.5 vs. 27.38 ± 6.24 kg/m²; p = 0.003). Preoperative SD-SNOT scores (p = 0.08) were comparable between both groups; however, postoperative scores (19.59 ± 13.49 vs. 12.17 ± 11.25; p = 0.01) were significantly higher in the OSA group. While preoperative STOP-BANG scores were comparable (p = 0.14), postoperative STOP-BANG scores were significantly higher in the OSA cohort (3.77 ± 1.83 vs. 2.16 ± 1.33; p < 0.001). There was no significant correlation between preoperative SD-SNOT and STOP-BANG scores in both OSA (r = 0.4; p = 0.43) and non-OSA (r = 0.11; p = 0.57) groups. Similarly, there was no correlation between postoperative SD-SNOT and STOP-BANG in both OSA (r = 0.07; p = 0.74) and non-OSA (r = 0.08; p = 0.47) groups. In comparison to preoperative SD-SNOT scores (AUC = 0.6), it was observed that preoperative STOP-BANG (AUC = 0.76) had a better ability to differentiate between the presence and absence of OSA. Similarly, postoperative STOP-BANG scores (AUC = 0.74) had better discriminative ability than postoperative SD-SNOT (AUC = 0.66) to diagnose OSA. Additionally, postoperative SD-SNOT scores were a better predictor for OSA than preoperative SD-SNOT scores.

Conclusion: Patients with OSA continue to have higher postoperative SD-SNOT and STOP-BANG scores, unlike non-OSA patients. Postoperative STOP-BANG scores had the best ability to distinguish between OSA and non-OSA. Additionally, SD-SNOT can potentially be used as a surrogate to screen for postoperative OSA, if STOP-BANG cannot be administered.

 

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No conflict of interest has been declared by the author(s).

Publication History

Article published online:
15 February 2022