A Home-Treatment Algorithm Based on Anti-inflammatory Drugs to Prevent Hospitalization of Patients With Early COVID-19: A Matched-Cohort Study (COVER 2)

Abstract

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 on a pathophysiologic and pharmacologic rationale-and including non-steroidal anti-inflammatory drugs, especially relatively selective cyclooxygenase-2 inhibitors and, when needed, corticosteroids, anticoagulants, oxygen therapy and antibiotics-at the very onset of mild COVID-19 symptoms 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 between January 2021 and May 2021, according to the proposed treatment algorithm and in 108 age-, sex-, and comorbidities-matched patients on 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 the cumulative length of hospital stays by 85% (from 141 to 19 days) as well as 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" than in the "control" cohort (97.2 vs. 93.5%, respectively; P = 0.322). Other symptoms lingered in a smaller proportion of patients in the "recommended" than in the "control" cohort (20.4 vs. 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.

Keywords: COVID-19; SARS-CoV-2; at home management; hospitalization; outpatients.

Figure 1

Kaplan–Meier curves for the primary endpoint of hospital admission. Kaplan–Meier curves show the proportion of patients who required hospitalization in the two treatment cohorts. Gray line, “recommended algorithm” treatment cohort; black line, “control” cohort. P-value for treatment comparison was assessed by survival analysis for clustered data.

Figure 2

Cumulative length of hospital stays and related costs in the two study cohorts. Cumulative days of hospitalization (A) and cumulative costs for hospital stays (B) in the “recommended” treatment cohort and in the “control” cohort. Gray columns, “recommended” treatment cohort; white columns, “control cohort”.