Abstract

Patients with obstructive sleep apnea (OSA) are at increased risk of postoperative cardiorespiratory complications and death. Attempts to stratify this risk have been inadequate, and predictors from large well-characterized cohort studies are needed. What is the relationship between OSA severity, defined by various polysomnography-derived metrics, and risk of postoperative cardiorespiratory complications or death, and which metrics best identify such risk? Cohort study of 6770 consecutive patients who underwent diagnostic polysomnography for possible OSA and a procedure involving general anesthesia within a period spanning 2 years before and at least 5 years after polysomnography. Participants were identified by linking polysomnography and health databases. Relationships between OSA severity measures and the composite primary outcome of cardiorespiratory complications or death within 30 days of hospital discharge were investigated using univariable and multivariable analyses. The primary outcome was observed in 5.3% (n=361) of the cohort. While univariable analysis showed strong dose-response relationships between this outcome and multiple OSA severity measures, multivariable analysis showed its independent predictors were: age >65 years (OR 2.67 [95%CI 2.03-3.52], p<0.0001); age 55.1-65 years (OR 1.47 [1.09-1.98], p=0.0111); time between polysomnography and procedure ≥5 years (OR 1.32 [1.02-1.70], p=0.0331), body mass index ≥35kg/m2 (OR 1.43 [1.13-1.82], p=0.0032); presence of known cardiorespiratory risk factor (OR 1.63 [1.29-2.06], p<0.0001); >4.7% of sleep time at SpO2 less than 90% (T90) (OR 1.91 [1.51-2.42], p<0.0001); and cardiothoracic procedures (OR 7.95 [5.71-11.08], p<0.001). For non-cardiothoracic procedures, age, BMI, presence of known cardiorespiratory risk factor and T90 remained the significant predictors, and a risk score based on their odds ratios was predictive of outcome (area under receiver operating characteristic curve 0.7 [95%CI 0.64-0.75]). These findings provide a basis for better identifying high-risk OSA patients and determining appropriate postoperative care.

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