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1.
Can J Hosp Pharm ; 77(1): e3398, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38204505

RESUMO

Background: Little is known about coinfections in patients with COVID-19, with antibiotics often initiated empirically. Objectives: To determine the rates and characteristics of early and late coinfections in COVID-19 patients and to characterize the use of anti-infective agents, especially antibiotics. Methods: This retrospective chart review involved patients with COVID-19 who were admitted to Lions Gate Hospital (Vancouver, British Columbia) between January 1 and June 30, 2020. Data were extracted from electronic medical records, and descriptive statistics were used to analyze the data. Results: Of the 48 patients admitted during the study period, 10 (21%) were determined to have coinfections: 3 (6%) had early coinfections and 7 (15%) had late coinfections. Early empiric use of antibiotics was observed in 32 (67%) patients; for 29 (91%) of these 32 patients, the therapy was deemed inappropriate. Patients with coinfections had longer hospital stays and more complications. Conclusions: Despite low rates of early coinfection, empiric antibiotics were started for a majority of the patients. Most late coinfections occurred in patients in the intensive care unit who required mechanical ventilation. Patients with coinfections had poorer outcomes than those without coinfections.


Contexte: On sait peu de choses sur les co-infections chez les patients atteints de COVID-19, les médicaments antibiotiques étant souvent initiés de manière empirique. Objectifs: Déterminer les taux et les caractéristiques des co-infections précoces et tardives chez les patients atteints de COVID-19 et caractériser l'utilisation d'anti-infectieux, en particulier les antibiotiques. Méthodes: Cet examen rétrospectif des dossiers portait sur des patients atteints de COVID-19 qui ont été admis à l'hôpital Lions Gate, à Vancouver (Colombie-Britannique), entre le 1er janvier et le 30 juin 2020. Les données ont été extraites des dossiers médicaux électroniques et des statistiques descriptives ont été utilisées pour analyser les données. Résultats: Sur les 48 patients admis au cours de la période d'étude, 10 patients (21 %) présentaient des co-infections: 3 patients (6 %) avaient des co-infections précoces et 7 (15 %), des co-infections tardives. Une utilisation empirique précoce d'antibiotiques a été observée chez 32 patients (67 %); pour 29 de ces 32 patients (91 %), le traitement a été jugé inapproprié. Les séjours à l'hôpital des patients co-infectés étaient plus longs et ils présentaient davantage de complications. Conclusions: Malgré de faibles taux de co-infection précoce, des antibiotiques empiriques ont été instaurés pour la majorité des patients. La plupart des co-infections tardives sont survenues chez des patients de l'unité de soins intensifs nécessitant une ventilation mécanique. Les résultats des patients avec co-infections étaient moins bons que ceux sans co-infections.

2.
Elife ; 112022 10 05.
Artigo em Inglês | MEDLINE | ID: mdl-36197074

RESUMO

Background: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings. Methods: Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. Results: Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61-0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population. Conclusions: Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome. Funding: Bronner P. Gonçalves, Peter Horby, Gail Carson, Piero L. Olliaro, Valeria Balan, Barbara Wanjiru Citarella, and research costs were supported by the UK Foreign, Commonwealth and Development Office (FCDO) and Wellcome [215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z]; and Janice Caoili and Madiha Hashmi were supported by the UK FCDO and Wellcome [222048/Z/20/Z]. Peter Horby, Gail Carson, Piero L. Olliaro, Kalynn Kennon and Joaquin Baruch were supported by the Bill & Melinda Gates Foundation [OPP1209135]; Laura Merson was supported by University of Oxford's COVID-19 Research Response Fund - with thanks to its donors for their philanthropic support. Matthew Hall was supported by a Li Ka Shing Foundation award to Christophe Fraser. Moritz U.G. Kraemer was supported by the Branco Weiss Fellowship, Google.org, the Oxford Martin School, the Rockefeller Foundation, and the European Union Horizon 2020 project MOOD (#874850). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Contributions from Srinivas Murthy, Asgar Rishu, Rob Fowler, James Joshua Douglas, François Martin Carrier were supported by CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and coordinated out of Sunnybrook Research Institute. Contributions from Evert-Jan Wils and David S.Y. Ong were supported by a grant from foundation Bevordering Onderzoek Franciscus; and Andrea Angheben by the Italian Ministry of Health "Fondi Ricerca corrente-L1P6" to IRCCS Ospedale Sacro Cuore-Don Calabria. The data contributions of J.Kenneth Baillie, Malcolm G. Semple, and Ewen M. Harrison were supported by grants from the National Institute for Health Research (NIHR; award CO-CIN-01), the Medical Research Council (MRC; grant MC_PC_19059), and by the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE) (award 200907), NIHR HPRU in Respiratory Infections at Imperial College London with PHE (award 200927), Liverpool Experimental Cancer Medicine Centre (grant C18616/A25153), NIHR Biomedical Research Centre at Imperial College London (award IS-BRC-1215-20013), and NIHR Clinical Research Network providing infrastructure support. All funders of the ISARIC Clinical Characterisation Group are listed in the appendix.


Assuntos
COVID-19 , SARS-CoV-2 , COVID-19/epidemiologia , COVID-19/virologia , Humanos , SARS-CoV-2/genética
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