BACKGROUND Type 2 diabetes (T2D) is a metabolic disease with significant medical complications. Roux-en-Y gastric bypass (RYGB) surgery is one of the few interventions that remit T2D in ~60% of patients. However, there is no accurate method for predicting preoperatively the probability for T2D remission. METHODS A retrospective cohort of 2,300 RYGB patients at Geisinger Clinic was used to identify 690 patients with T2D and complete electronic data. Two additional T2D cohorts (N=276, and N=113) were used for replication at 14 months following RYGB. Kaplan-Meier analysis was used in the primary cohort to create survival curves until remission. A Cox proportional hazards model was used to estimate the hazard ratios on T2D remission. FINDINGS Using 259 preoperative clinical variables, four (use of insulin, age, HbA1c, and type of antidiabetic medication) were sufficient to develop an algorithm that produces a type 2 diabetes remission (DiaRem) score over five years. The DiaRem score spans from 0 to 22 and was divided into five groups corresponding to five probability-ranges for T2D remission: 0–2 (88%–99%), 3–7 (64%–88%), 8–12 (23%–49%), 13–17 (11%–33%), 18–22 (2%–16%). The DiaRem scores in the replication cohorts, as well as under various definitions of diabetes remission, conformed to the DiaRem score of the primary cohort. INTERPRETATION The DiaRem score is a novel preoperative method for predicting the probability (from 2% to 99%) for T2D remission following RYGB surgery. FUNDING This research was supported by the Geisinger Health System and the National Institutes of Health.

No abstract

Study Objectives: Obstructive sleep apnea (OSA) is an extremely common sleep disorder. A potential association between OSA and coronavirus disease 2019 (COVID-19) severity has been proposed on the basis of similar comorbid medical conditions associated with both OSA and COVID-19. Methods: We performed a retrospective review of 1,738 patients who were hospitalized with COVID-19 between March and October of 2020. Patients were classified based on the presence or absence of OSA diagnosis based upon the International Classification of Diseases (ICD codes; G47.33 and U07.1 for OSA and COVID-19, respectively). Other data collected, including demographics, body mass index (BMI), and comorbid conditions. COVID-19 severity was compared between groups using the quick COVID-19 severity index. Results: Quick COVID-19 severity index scores were higher in patients with OSA compared to without OSA. However, the prevalence rates of type 2 DM (p<0.0001), coronary artery disease (p<0.0001), congestive heart failure (p<0.0001), and chronic obstructive pulmonary diseases (p<0.0001) were also significantly greater in the OSA group. Unadjusted models revealed higher risk of ICU admission in patients with COVID-19 and OSA. However, such an association attenuated and became non-significant after adjusting for age, sex, BMI, and comorbid disease. Conclusions: In our study, OSA does not appear to be an independent risk factor for worse COVID-19 outcomes in hospitalized patients. Further studies with larger sample sizes are needed to delineate the potential role of OSA in determining outcomes in hospitalized patients with COVID-19.

No abstract