COVID-19 Risk Prediction for Diabetic Patients Using Fuzzy Inference System and Machine Learning Approaches.

Individuals with pre-existing diabetes seem to be vulnerable to the COVID-19 due to changes in blood sugar levels and diabetes complications. As observed globally, around 20-50% of individuals affected by coronavirus had diabetes. However, there is no recent finding that diabetic patients are more prone to contract COVID-19 than nondiabetic patients. However, a few recent findings have observed that it could be at least twice as likely to die from complications of diabetes. Considering the multifold mortality rate of COVID-19 in diabetic patients, this study proposes a COVID-19 risk prediction model for diabetic patients using a fuzzy inference system and machine learning approaches. This study aimed to estimate the risk level of COVID-19 in diabetic patients without a medical practitioner's advice for timely action and overcoming the multifold mortality rate of COVID-19 in diabetic patients. The proposed model takes eight input parameters, which were found as the most influential symptoms in diabetic patients. With the help of the various state-of-the-art machine learning techniques, fifteen models were built over the rule base. CatBoost classifier gives the best accuracy, recall, precision, F1 score, and kappa score. After hyper-parameter optimization, CatBoost classifier showed 76% accuracy and improvements in the recall, precision, F1 score, and kappa score, followed by logistic regression and XGBoost with 75.1% and 74.7% accuracy. Stratified k-fold cross-validation is used for validation purposes.

Gastrointestinal Symptoms and Outcomes in Hospitalized Coronavirus Disease 2019 Patients.

INTRODUCTION: Gastrointestinal (GI) symptoms are increasingly being recognized in coronavirus disease 2019 (COVID-19). It is unclear if the presence of GI symptoms is associated with poor outcomes in COVID-19. We aim to assess if GI symptoms could be used for prognostication in hospitalized patients with COVID-19. METHODS: We retrospectively analyzed patients admitted to a tertiary medical center in Brooklyn, NY, from March 18, 2020, to March 31, 2020, with COVID-19. The patients' medical charts were reviewed for the presence of GI symptoms at admission, including nausea, vomiting, diarrhea, and abdominal pain. COVID-19 patients with GI symptoms (cases) were compared with COVID-19 patients without GI symptoms (control). RESULTS: A total of 150 hospitalized COVID-19 patients were included, of which 31 (20.6%) patients had at least 1 or more of the GI symptoms (cases). They were compared with the 119 COVID-19 patients without GI symptoms (controls). The average age among cases was 57.6 years (SD 17.2) and control was 63.3 years (SD 14.6). No statistically significant difference was noted in comorbidities and laboratory findings. The primary outcome was mortality, which did not differ between cases and controls (41.9 vs. 37.8%, p = 0.68). No statistically significant differences were noted in secondary outcomes, including the length of stay (LOS, 7.8 vs. 7.9 days, p = 0.87) and need for mechanical ventilation (29 vs. 26.9%, p = 0.82). DISCUSSION: In our study, the presence of GI manifestations in COVID-19 at the time of admission was not associated with increased mortality, LOS, or mechanical ventilation.