ABSTRACT
BACKGROUND AND AIMS: Obstructive sleep apnoea (OSA) is largely undiagnosed in surgical population. Airway-related complication account for 35% of anaesthesia-related deaths and OSA patients have higher occurrence of difficult intubation (DIT). The aim of the study is to estimate the occurrence and compare utility of OSA screening parameters in predicting difficult mask ventilation (DMV) and DIT in patients with undiagnosed OSA. METHODS: A prospective observational study was conducted in a tertiary care centre in patients undergoing elective surgery. STOP-BANG questionnaire was administered preoperatively along with collection of demographic data and airway assessment. Population was divided in to OSA and non-OSA groups based on STOP-BANG score >3. Occurrence of DMV, laryngoscopy (DL), and DIT were compared between both groups using DMV score, Cormack-Lehane grading, and intubation difficulty scale score, respectively. RESULTS: A total of 54 patients in OSA and 46 patients in non-OSA group were studied. A total of 49 cases of DMV, 14 cases of DIT, and 25 cases of DL were encountered. In the OSA group, there was 77.7% DMV, 22.2% DIT, and 33.3% DL. History of snoring had the highest sensitivity and negative predictive value while history of apnea, body mass index >35, sleep apnoea clinical score had the highest specificity in determining occurrence of difficult airway. Multivariate logistic regression analysis demonstrated STOP-BANG score as the single most important predictor of DMV (odds ratio 3.15, 95% confidence interval, 2.06-4.8). CONCLUSION: Positive screening test for OSA is associated with difficult airway management.
ABSTRACT
BACKGROUND: Most individuals with OSA remain undiagnosed, mainly due to limited access to effective screening tools and diagnostic facilities. Therefore, the objective of this study was to identify craniofacial and anthropometric measurements that predict OSA in an Indian population. METHODS AND FINDINGS: Male subjects (n = 76) between 25 and 50 years of age were recruited for the study from the general population. The study measures consisted of home-based type IV polysomnography and a total of 40 anthropometric and craniofacial measurements. Key measures were identified, and a model was developed with these variables, which predicted the presence of OSA with a sensitivity, specificity and overall accuracy of 93.1, 20.0 and 74.4%, respectively. CONCLUSION: This preliminary study shows the utility of craniofacial and anthropometric variables in the identification of individuals at risk of OSA. These findings need to be further validated against the results of overnight polysomnography in a large independent population.
