Safety and Efficacy of Outpatient Treatments for COVID-19: Real-Life Data from a Regionwide Cohort of High-Risk Patients in Tuscany, Italy (the FEDERATE Cohort)

Author:

Manciulli Tommaso1,Spinicci Michele12ORCID,Rossetti Barbara3,Antonello Roberta Maria1ORCID,Lagi Filippo12,Barbiero Anna1,Chechi Flavia14,Formica Giuseppe1,Francalanci Emanuela15,Alesi Mirco15,Gaggioli Samuele1,Modi Giulia16ORCID,Modica Sara7,Paggi Riccardo14ORCID,Costa Cecilia6,Morea Alessandra8,Paglicci Lorenzo9,Rancan Ilaria110,Amadori Francesco11,Tamborrino Agnese12,Tilli Marta16ORCID,Bandini Giulia1,Pignone Alberto Moggi1,Valoriani Beatrice9,Montagnani Francesca1013ORCID,Tumbarello Mario1013ORCID,Blanc Pierluigi4,Di Pietro Massimo6,Galli Luisa1214ORCID,Aquilini Donatella5,Vincenti Antonella11,Sani Spartaco8,Nencioni Cesira3,Luchi Sauro7,Tacconi Danilo9,Zammarchi Lorenzo12ORCID,Bartoloni Alessandro12ORCID

Affiliation:

1. Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi di Firenze, 50121 Firenze, Italy

2. SOD Malattie Infettive e Tropicali, Azienda Ospedaliero-Universitaria Careggi, 50134 Firenze, Italy

3. UOC Malattie Infettive, Ospedale Misericordia, 58100 Grosseto, Italy

4. SOC Malattie Infettive, Ospedale San Jacopo, 51100 Pistoia, Italy

5. UO Malattie Infettive, Ospedale Santo Stefano, 59100 Prato, Italy

6. UO Malattie Infettive, Ospedale Santa Maria Annunziata, 50012 Firenze, Italy

7. SOC Malattie Infettive ed Epatologia, Ospedale San Luca, 55100 Lucca, Italy

8. UO Malattie Infettive, Ospedali Riuniti di Livorno, 57124 Livorno, Italy

9. UO Malattie Infettive, Ospedale San Donato, 52100 Arezzo, Italy

10. Dipartimento di Biotecnologie Mediche, Università degli Studi di Siena, 53100 Siena, Italy

11. UO Malattie Infettive, Ospedale Apuane, 54100 Massa, Italy

12. Dipartimento Scienze della Salute, Università degli Studi di Firenze, 50139 Firenze, Italy

13. UOC Malattie Infettive e Tropicali, Azienda Ospedaliero Universitaria Senese, 53100 Siena, Italy

14. UO Malattie Infettive, Azienda Ospedaliero-Universitaria “Meyer”, 50139 Firenze, Italy

Abstract

Early COVID-19 treatments can prevent progression to severe disease. However, real-life data are still limited, and studies are warranted to monitor the efficacy and tolerability of these drugs. We retrospectively enrolled outpatients receiving early treatment for COVID-19 in 11 infectious diseases units in the Tuscany region of Italy between 1 January and 31 March 2022, when Omicron sublineages BA.1 and BA.2 were circulating. Eligible COVID-19 patients were treated with sotrovimab (SOT), remdesivir (RMD), nirmatrelvir/ritonavir (NRM/r), or molnupiravir (MOL). We gathered demographic and clinical features, 28-day outcomes (hospitalization or death), and drugs tolerability. A total of 781 patients (median age 69.9, 66% boosted for SARS-CoV-2) met the inclusion criteria, of whom 314 were treated with SOT (40.2%), 205 with MOL (26.3%), 142 with RMD (18.2%), and 120 with NRM/r (15.4%). Overall, 28-day hospitalization and death occurred in 18/781 (2.3%) and 3/781 (0.3%), respectively. Multivariable Cox regression showed that patients receiving SOT had a reduced risk of meeting the composite outcome (28-day hospitalization and/or death) in comparison to the RMD cohort, while no significant differences were evidenced for the MOL and NRM/r groups in comparison to the RMD group. Other predictors of negative outcomes included cancer, chronic kidney disease, and a time between symptoms onset and treatment administration > 3 days. All treatments showed good safety and tolerability, with only eight patients (1%) whose treatment was interrupted due to intolerance. In the first Italian multicenter study presenting real-life data on COVID-19 early treatments, all regimens demonstrated good safety and efficacy. SOT showed a reduced risk of progression versus RMD. No significant differences of outcome were observed in preventing 28-day hospitalization and death among patients treated with RMD, MOL, and NRM/r.

Publisher

MDPI AG

Subject

Virology,Infectious Diseases

Reference38 articles.

1. (2023, January 23). NIH NIH COVID Treatment Guidelines, Available online: https://www.covid19treatmentguidelines.nih.gov/.

2. Outpatient Therapies for COVID-19: How Do We Choose?;Lee;Open Forum Infect. Dis.,2022

3. Bhimraj, A., Morgan, R.L., Shumaker, A.H., Lavergne, V., Cheng, V.C., Edwards, K.M., Gandhi, R., Gallagher, J., Muller, W.J., and Horo, J.C.O. (2023, January 25). Infectious Diseases Society of America Guidelines on the Treatment and Management of Patients with COVID-19. Available online: https://www.idsociety.org/globalassets/idsa/practice-guidelines/covid-19/treatment/idsa-covid-19-gl-tx-and-mgmt-v10.2.0.pdf.

4. Early Treatment for COVID-19 with SARS-CoV-2 Neutralizing Antibody Sotrovimab;Gupta;N. Engl. J. Med.,2021

5. Early Remdesivir to Prevent Progression to Severe COVID-19 in Outpatients;Gottlieb;N. Engl. J. Med.,2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3