Current practice guidelines recommend obstructive sleep apnea (OSA) patients to stay in the post anesthetic care unit (PACU) until the risk of respiratory depression has subsided. Inevitably, a greater demand on hospital resource utilization in these patients will increase health care cost. Polysomnography (PSG) and screening questionnaires can identify OSA but they are limited by accessibility and false positive results, respectively. Inaccurate OSA identification misguides postoperative surveillance plan. In contrast with MRI and CT scans, ultrasound is more accessible and more likely a practical tool for OSA screening. However, before clinical application, airway ultrasound (US) exam must undergo vigorous testing to check its utility, accuracy, inter-observer reliability and its ability to identify OSA and its severity.
The investigators plan to recruit surgical patients at risk of OSA, exposed to sedatives,and/or general anesthesia. Surface ultrasound measurements will be conducted in a separate setting, and be correlated with the sleep study results, and a set of ultrasound parameters will be validated in this setting. Relevant clinical outcomes will be captured as well.
Study Type
OBSERVATIONAL
Enrollment
200
Toronto Western Hospital
Toronto, Ontario, Canada
Correlation of airway parameter measurements with Apnea-Hypopnea Index (AHI) values on Polysomnography (PSG)
The primary study outcome will be the discriminatory performance of each one of the airway parameters, against the OSA status (moderate/severe) as diagnosed by PSG.
Time frame: 2 years
Feasibility of airway Ultrasound (US) examination;
1. The feasibility and efficiency of completing the US exam and reading the measurements; 2. The inter-rater reliability for measuring each one of the airway parameters; 3. The statistical association between each airway parameter and OSA severity level (none/mild/moderate/severe); 4. The diagnostic accuracy for STOPBang (SB) score (ROC curve, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio, negative likelihood ratios, and diagnostic odds ratio (DOR) for different cut off levels); 5. The correlation between each one of the airway parameters and the SB score; and 6. The benefit of considering airway parameters in addition to SB in a prediction model for OSA.
Time frame: 2 years
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