Background: The association between Body Mass Index (BMI) and clinical outcomes following sepsis continues to be debated. We aimed to investigate the relationship between BMI and in-hospital clinical course and mortality in patients hospitalized with bacteremic sepsis using real-world data. Methods: A sampled cohort of patients hospitalized with bacteremic sepsis between October 2015 and December 2016 was identified in the National Inpatient Sample (NIS) database. In-hospital mortality and length of stay were defined as the relevant outcomes. Patients were divided into 6 BMI (kg/m²) subgroups; (1) underweight ≤ 19, (2) normal-weight 20–25, (3) over-weight 26–30, (4) obese I 31–35, (5) obese II 36–39, and (6) obese stage III ≥ 40. A multivariable logistic regression model was used to find predictors of mortality, and a linear regression model was used to find predictors of an extended length of stay (LOS). Results: An estimated total of 90,760 hospitalizations for bacteremic sepsis across the U.S. were analyzed. The data showed a reverse-J-shaped relationship between BMI and study population outcomes, with the underweight patients (BMI ≤ 19 kg/m²) suffering from higher mortality and longer LOS as did the normal-weight patients (BMI 20–25 kg/m²) when compared to the higher BMI groups. The seemingly protective effect of a higher BMI diminished in the highest BMI group (BMI ≥ 40 kg/m²). In the multivariable regression model, BMI subgroups of ≤19 kg/m² and ≥40 kg/m² were found to be independent predictors of mortality. Conclusions: A reverse-J-shaped relationship between BMI and mortality was documented, confirming the “obesity paradox” in the real-world setting in patients hospitalized for sepsis and bacteremia.

Background: Atrial fibrillation (AF) is a common diagnosis in patients presenting to urgent care centers (UCCs), yet there is scant research regarding treatment in these centers. While some of these patients are managed within UCCs, some are referred for further care in an emergency department (ED). Objectives: We aimed to identify the rate of patients referred to an ED and define predictors for this outcome. We analyzed the rates of AF diagnosis and hospital referral over the years. Finally, we described trends in patient anticoagulation (AC) medication use. Methods: This retrospective study included 5873 visits of patients over age 18 visiting the TEREM UCC network with a diagnosis of AF over 11 years. Multivariate analysis was used to identify predictors for ED referral. Results: In a multivariate model, predictors of referral to an ED included vascular disease (OR 1.88 (95% CI 1.43–2.45), p < 0.001), evening or night shifts (OR 1.31 (95% CI 1.11–1.55), p < 0.001; OR 1.68 (95% CI 1.32–2.15), p < 0.001; respectively), previously diagnosed AF (OR 0.31 (95% CI 0.26–0.37), p < 0.001), prior treatment with AC (OR 0.56 (95% CI 0.46–0.67), p < 0.001), beta blockers (OR 0.63 (95% CI 0.52–0.76), p < 0.001), and antiarrhythmic medication (OR 0.58 (95% CI 0.48–0.69), p < 0.001). Visits diagnosed with AF increased over the years (p = 0.030), while referrals to an ED decreased over the years (p = 0.050). The rate of novel oral anticoagulant prescriptions increased over the years. Conclusions: The rate of referral to an ED from a UCC over the years is declining but remains high. Referrals may be predicted using simple clinical variables. This knowledge may help to reduce the burden of hospitalizations.