Building a Perioperative Sleep Apnea Algorithm: Applying the Literature to Your Practice

Abstract

Obstructive sleep apnea (OSA) is a common comorbidity in the patient population undergoing bariatric surgery. Up to 70% of patients undergoing weight loss surgery suffer from the disease and its physiologic sequelae. Subjecting these patients to surgery, an anesthetic, opioid therapy, and other sedating medications may place them at increased risk for an adverse event in the perioperative period. There is extensive medical literature outlining post-surgical complications in patients with OSA and growing evidence that both preoperative and postoperative considerations should be made in caring for these patients. There is an increasing number of perioperative care recommendations from national societies and patient safety organizations outlining management strategies for OSA patients. However, there is not yet a faultless predictive model determining which patients with OSA are at highest risk after surgery. This article serves specifically to address OSA in the bariatric population, apply sleep apnea literature in real practice, and demonstrate a large hospital-system algorithm used to assess, risk-stratify, and care for this population.