Obesity Phenotype is a Predictor of COVID‐19 Disease Susceptibility

Abstract

To the Editor: After having read your recent Editorial, “COVID 19 and the Patient with Obesity – The Editors Speak Out” ((1)), I wish to share my personal experience. I am an anesthesiologist working on the frontline of the coronavirus (COVID-19) pandemic at a busy New York City tertiary care teaching center, Weill Cornell Medical College, New York-Presbyterian Hospital. As Director of the Bariatric Anesthesia division and an airway expert, I was assigned to the COVID-19 intubation team in March 2020. We are at ground zero of the public health care crisis, intubating as many as 15 to 20 patients in a 24-hour period. I began to field calls from other physicians, asking, “Could you help out? We have a 150-kg patient.” A few of my colleagues came to me for technical advice. Upon closer inspection, I noted that most of my patients were male, over age 60, had extensive medical comorbidities, and had obesity. They overwhelmingly possessed the classic obstructive sleep apnea (OSA) phenotype ((2)): older male, high BMI (in kilograms per meter squared), hypersomnia, airway abnormalities, and metabolic syndrome with abdominal obesity as assessed by waist circumference and waist to hip ratio ((2)), and they often had longstanding hypertension, diabetes, and cardiac and renal disease. Patients with obesity class III and full expression of the OSA phenotype, OSA Subtype B2, are already known to have a high prevalence of cardiovascular disease risk, obtain less benefit from noninvasive positive pressure ventilation, and require medical management of comorbidities. Such patients have high risk for all-cause, cardiovascular, and cancer mortality ((3)) and often present with a deconditioned proinflammatory profile ((3)). The Centers for Disease Control and Prevention classes patients with obesity at risk for flu ((1)), and ostensibly COVID-19 complications, as has been shown in the 2009 influenza A infection. As pointed out in the Editorial ((1)), these patients are at risk for infections, particularly respiratory infections, and for influenza-like illness despite vaccination ((4)). This may also prove to be the case with COVID-19. Patients with severe obesity appear to be highly represented in the severe COVID-19 disease population. In order to determine the actual representation, national or international retrospective large-scale medical studies of hospital admissions of admitting and discharge diagnoses on COVID-19 patients need to be conducted. Several such studies are ongoing ((5)) and they have indicated that the most frequent comorbidities represented in the severe COVID-19 infected population are hypertension, obesity, and diabetes. These studies offer a regional perspective and are helpful, although they have limitations. It is difficult to compare data in disparate health care systems without uniform definitions of quality and outcome. Risk stratification of data points should allow resources to be deployed in the most cost-effective manner and focus attention on the most fragile cohort of patients during the healing phase of the disease. What is now needed is to harmonize the data and put them together into a large data set from which conclusions may be drawn. Disclosure: The author declared no conflict of interest.