Aim: To assess the feasibility of a remote care model for high-risk COVID-19 patients, identify risk factors for hospital admission, and propose modifications to the tested model.
Methods: We conducted a multicenter observational study of 225 patients (55.1% male) treated at three primary care centers between October 2020 and February 2022. Patients were enrolled into a telemonitoring program if they had a mild-moderate course of COVID-19 confirmed by polymerase chain reaction testing and were classified as high-risk for COVID-19 deterioration. Patients measured their vital signs three times daily, consulted their primary care physician every other day, and were followed up for 14 days. At inclusion, data were collected with a semi-structured questionnaire, and blood was drawn for laboratory analysis. A multivariable Cox regression model was used to determine predictors of hospital admission.
Results: The median age was 62 years (range 24-94). The hospital admission rate was 24.4%, and the mean time from inclusion to hospital admission was 2.7±2.9 days. A total of 90.9% of patients were hospitalized within the first five days. A Cox regression model, adjusted for age, sex, and the presence of hypertension, revealed that the main predictors of hospital admission were type-2 diabetes (hazard ratio [HR] 2.38, 95% confidence interval [CI] 1.19-4.77, P=0.015) and thrombocytopenia (HR 2.46, 95% CI 1.33-4.53, P=0.004).
Conclusion: Telemonitoring of vital signs is a feasible method of remote care that helps identify patients requiring immediate hospital admission. For further scale-up, we suggest shortening call intervals in the first five days, when the risk of hospital admission is highest, and giving special attention to patients with type-2 diabetes and thrombocytopenia at inclusion.