The Incidence and Factors Affecting the 28-day Hospital Admission Among Adult Ambulatory COVID-19 Patients

Objective: This study aimed to determine the 28-day hospital admission incidence and risk factors related to the hospitalization of COVID-19 patients who were followed as outpatients in a university hospital. Methods: A retrospective cohort study was designed in which the sociodemographic characteristics, symptoms on the first visit, presence of comorbidities, and viral load predictor cycle threshold (Ct) value were defined as independent variables and hospital admission in the first 28 days after the first visit was defined as dependent variable. Factors related to hospital admission were evaluated with univariate and multivariate analyses. Cox regression analysis was used for multivariate analyses, and the effect size was determined with a hazard ratio (HR). Statistical significance was defined as p<0.05. Results: 368 patients were included in this study. The median (25-75th percentile) age was 36 (28-45) years, and 46.1% of the patients were female. Sixty-five patients (17.7%) were hospitalized in the first 28 days. When age ≤29 referenced, age≥50 (HR=4.1, 95% confidence interval [CI]=1.7-9.6), 40-49 (HR=3.0, 95% CI=1.3-6.6) and 30-39 (HR=1.6, 95% CI=0.6-3.6), fever or chills, (HR=2.3, 95% CI=1.3-4.1), dyspnea (HR=2.0, 95% CI=1.1-3.4), fatigue (HR=1.9, 95% CI=1.0-3.5), vomiting (HR=3.0, 95% CI=1.5-5.8), and sore throat (HR=0.4, 95% CI=0.2-0.8) were defined as independent risk factors according to multivariable analysis. Hypertension was the only comorbidity independently predicting hospital admission (HR=2.2, 95% CI=1.0-4.4). Conclusion: Advanced age, systemic and lower respiratory tract infection signs, and hypertension independently increased the 28-day hospital admission. The presence of a sore throat was not a factor for hospital admission. A lower risk of hospital admission in patients with sore throats may indicate that the patient will have a mild upper respiratory tract infection and will not progress to severe disease. Due to missing data, this study could not fully evaluate the hospital admission risk factors. Studies that include clinical, laboratory, and radiological findings are needed to generate a more accurate model predicting hospital admission risk.