Public Health Benefits of Applying Evidence-Based Best Practices in Managing Patients Hospitalized for COVID-19

Andre C Kalil; Aastha Chandak; Luke S P Moore; Neera Ahuja; Martin Kolditz; Roman Casciano; Ananth Kadambi; Mohsen Yaghoubi; Sotirios Tsiodras; Jakob J Malin; Essy Mozaffari; Michele Bartoletti

doi:10.1093/cid/ciae517

Public Health Benefits of Applying Evidence-Based Best Practices in Managing Patients Hospitalized for COVID-19

Clin Infect Dis. 2024 Oct 25:ciae517. doi: 10.1093/cid/ciae517. Online ahead of print.

Authors

Affiliations

¹ University of Nebraska Medical Center, Omaha, Nebraska, USA.
² Certara, New York, New York, USA.
³ Imperial College, London, United Kingdom.
⁴ Stanford University School of Medicine, Stanford, California, USA.
⁵ Medical Department I, Division of Pulmonology, University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.
⁶ Professor of Medicine and Infectious Diseases; National & Kapodistrian University of Athens Medical School; Chair, 4th Department of Internal Medicine, Attikon University Hospital, Athens, Greece.
⁷ Department I of Internal Medicine, Division of Infectious Diseases, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
⁸ Gilead Sciences, Foster City, California, USA.
⁹ Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20072 Pieve Emanuele, Milan, Italy.
¹⁰ Infectious Disease Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy.

PMID: 39449663
DOI: 10.1093/cid/ciae517

Abstract

Background: As COVID-19-related mortality remains a concern, optimal management of patients hospitalized for COVID-19 continues to evolve. We developed a population model based on real-world evidence to quantify the clinical impact of increased utilization of remdesivir, the effectiveness of which has been well established in hospitalized patients with COVID-19.

Methods: The PINC AI healthcare database records for patients hospitalized for COVID-19 from January to December 2023 were stratified by those treated with or without remdesivir ("RDV" and "No RDV") and by supplemental oxygen requirements: no supplemental oxygen charges (NSOc), low-flow oxygen (LFO), and high-flow oxygen/non-invasive ventilation (HFO/NIV). Key vulnerable subgroups such as elderly and immunocompromised patients were also evaluated. The model applied previously published hazard ratios (HRs) to 28-day in-hospital mortality incidence to determine the number of potential lives saved if additional "No RDV" patients had been treated with remdesivir upon hospital admission.

Results: Of 84,810 hospitalizations for COVID-19 in 2023, 13,233 "No RDV" patients were similar in terms of characteristics and clinical presentation to the "RDV" patients. The model predicted that initiation of remdesivir in these patients could have saved 231 lives. Projected nationally, this translates to >800 potential lives saved (95% CI: 469-1,126). Eighty-nine percent of potential lives saved were elderly and 19% were immunocompromised individuals. Seventy-one percent were among NSOc or LFO patients.

Conclusions: This public health model underscores the value of initiating remdesivir upon admission in patients hospitalized for COVID-19, in accordance with evidence-based best practices, to minimize lives lost due to SARS-CoV-2 infection.

Keywords: COVID-19; SARS-CoV-2; data science; mortality; real world data; remdesivir.