The return visit, outcome and predicting factors of return visit among suspected COVID-19 outpatients.

Rate of return visit, predicting factors of return visit and occurrence of adverse events in suspected to be or likely cases of COVID-19 patients who received outpatient treatment. This is a retrospective observational cohort study on patients (> 16 years), suspected to be or likely cases of COVID-19 who were visited in a respiratory emergency department and subsequently discharged home. Patients' baseline characteristics were extracted from medical charts. All patients were followed-up for 7 days after their first visit. Patients' outcomes during the7-day follow-up, as well as the severity of pulmonary involvement based on imaging were recorded. A total number of 601 patients (350 men and 251 women) were recruited. The rate of return visit was 27.74% (144 patients) with 6.74% (34 patients) experiencing a poor outcome. Six factors with a significant odds ratio were predictors of poor outcome in patients who received outpatient treatment, namely, older age [odds ratio = 3.278, 95% confidence interval: 1.115-9.632], days from onset of symptoms [1.068, 1.003-1.137], and history of diabetes [6.373, 2.271-17.883]). Predictors of favorable outcome were female gender [0.376, 0.158-0.894], oxygen saturation > 93% [0.862, 0.733-1.014], smoking habit [0.204, 0.045-0.934]. The findings of this study demonstrate that the rate of return visit with poor outcome in patients who received outpatient treatment was reasonably low. Age, male sex, diabetes mellitus and pulmonary disease are predicting factors of poor outcome in these COVID-19 patients who received outpatient management.

Clinical features, risk factors and a prediction model for in-hospital mortality among diabetic patients infected with COVID-19: data from a referral centre in Iran.

OBJECTIVES: The aim of this study was to identify risk factors of in-hospital mortality among diabetic patients infected with COVID-19. STUDY DESIGN: This is a retrospective cohort study. METHODS: Using logistic regression analysis, the independent association of potential prognostic factors and COVID-19 in-hospital mortality was investigated in three models. Model 1 included demographic data and patient history; model 2 consisted of model 1, plus vital signs and pulse oximetry measurements at hospital admission; and model 3 included model 2, plus laboratory test results at hospital admission. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were reported for each predictor in the different models. Moreover, to examine the discriminatory powers of the models, a corrected area under the receiver-operating characteristic curve (AUC) was calculated. RESULTS: Among 560 patients with diabetes (men = 291) who were hospitalised for COVID-19, the mean age of the study population was 61.8 (standard deviation [SD] 13.4) years. During a median length of hospitalisation of 6 days, 165 deaths (men = 93) were recorded. In model 1, age and a history of cognitive impairment were associated with higher mortality; however, taking statins, oral antidiabetic drugs and beta-blockers was associated with a lower risk of mortality (AUC = 0.76). In model 2, adding the data for respiratory rate (OR 1.07 [95% CI 1.00-1.14]) and oxygen saturation (OR 0.95 [95% CI 0.92-0.98]) slightly increased the AUC to 0.80. In model 3, the data for platelet count (OR 0.99 [95% CI 0.99-1.00]), lactate dehydrogenase (OR 1.002 [95% CI 1.001-1.003]), potassium (OR 2.02 [95% CI 1.33-3.08]) and fasting plasma glucose (OR 1.04 [95% CI 1.02-1.07]) significantly improved the discriminatory power of the model to AUC 0.86 (95% CI 0.83-0.90). CONCLUSIONS: Among patients with type 2 diabetes, a combination of past medical and drug history and pulse oximetry data, with four non-expensive laboratory measures, was significantly associated with in-hospital COVID-19 mortality.