A HOME-TREATMENT ALGORITHM BASED ON ANTI-INFLAMMATORY DRUGS TO PREVENT HOSPITALIZATION OF PATIENTS WITH EARLY COVID-19: A MATCHED-COHORT STUDY (COVER 2)

A bstract Background and Aim While considerable success has been achieved in the management of patients hospitalized with severe coronavirus disease 2019 (COVID-19), far less progress has been made with early outpatient treatment. We assessed whether the implementation of a home treatment algorithm – designed based upon on a pathophysiologic and pharmacologic rationale - during the initial, mild phase of COVID-19, could effectively reduce hospital admissions. Methods This fully academic, matched-cohort study evaluated outcomes in 108 consecutive consenting patients with mild COVID-19 managed at home by their family doctors from January 2021 to May 2021, according to the proposed treatment algorithm and in 108 age-, sex-, and comorbidities-matched patients who were given other therapeutic schedules ( ClinicalTrials.gov NCT04854824 ). The primary outcome was COVID-19-related hospitalization. Analyses were by intention-to-treat. Results One (0.9%) patient in the ‘recommended’ cohort and 12 (11.1%) in the ‘control’ cohort were admitted to hospital (P=0.0136). The proposed algorithm reduced, by 85%, the cumulative length of hospital stays (from 141 to 19 days) and related costs (from € 60.316 to € 9.058). Only 9.8 patients needed to be treated with the recommended algorithm to prevent one hospitalization event. The rate of resolution of major symptoms was numerically, but not significantly, higher in the ‘recommended’ compared to the ‘control’ cohort (97.2% versus 93.5%, respectively; P=0.322). Other symptoms lingered in a lower proportion of patients in the ‘recommended’ than in the‘control’ cohort (20.4% versus 63.9%, respectively; P<0.001), and for a shorter period. Conclusion The adoption of the proposed outpatient treatment algorithm during the early, mild phase of COVID-19 reduced the incidence of subsequent hospitalization and related costs.