Antimicrobial resistance (AMR) in COVID-19 patients: a systematic review and meta-analysis (November 2019–June 2021)

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Abstract

Background

Pneumonia from SARS-CoV-2 is difficult to distinguish from other viral and bacterial etiologies. Broad-spectrum antimicrobials are frequently prescribed to patients hospitalized with COVID-19 which potentially acts as a catalyst for the development of antimicrobial resistance (AMR).

Objectives

We conducted a systematic review and meta-analysis during the first 18 months of the pandemic to quantify the prevalence and types of resistant co-infecting organisms in patients with COVID-19 and explore differences across hospital and geographic settings.

Methods

We searched MEDLINE, Embase, Web of Science (BioSIS), and Scopus from November 1, 2019 to May 28, 2021 to identify relevant articles pertaining to resistant co-infections in patients with laboratory confirmed SARS-CoV-2. Patient- and study-level analyses were conducted. We calculated pooled prevalence estimates of co-infection with resistant bacterial or fungal organisms using random effects models. Stratified meta-analysis by hospital and geographic setting was also performed to elucidate any differences.

Results

Of 1331 articles identified, 38 met inclusion criteria. A total of 1959 unique isolates were identified with 29% (569) resistant organisms identified. Co-infection with resistant bacterial or fungal organisms ranged from 0.2 to 100% among included studies. Pooled prevalence of co-infection with resistant bacterial and fungal organisms was 24% (95% CI 8–40%; n = 25 studies: I ² = 99%) and 0.3% (95% CI 0.1–0.6%; n = 8 studies: I ² = 78%), respectively. Among multi-drug resistant organisms, methicillin-resistant Staphylococcus aureus, carbapenem-resistant Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and multi-drug resistant Candida auris were most commonly reported. Stratified analyses found higher proportions of AMR outside of Europe and in ICU settings, though these results were not statistically significant. Patient-level analysis demonstrated > 50% (n = 58) mortality, whereby all but 6 patients were infected with a resistant organism.

Conclusions

During the first 18 months of the pandemic, AMR prevalence was high in COVID-19 patients and varied by hospital and geography although there was substantial heterogeneity. Given the variation in patient populations within these studies, clinical settings, practice patterns, and definitions of AMR, further research is warranted to quantify AMR in COVID-19 patients to improve surveillance programs, infection prevention and control practices and antimicrobial stewardship programs globally.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13756-022-01085-z.

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Most cited references 67

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QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

Penny F Whiting, Anne Rutjes, Marie E Westwood … (2011)

In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Signalling questions are included to help judge risk of bias. The QUADAS-2 tool is applied in 4 phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability. This tool will allow for more transparent rating of bias and applicability of primary diagnostic accuracy studies.

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Co-infections in people with COVID-19: a systematic review and meta-analysis

Louise Lansbury, Benjamin W.H. Lim, Vadsala Baskaran … (2020)

Highlights • SARS-CoV-2, the cause of COVID19 disease, has spread globally since late 2019 • Bacterial coinfections associated with mortality in previous influenza pandemics • Proportion of COVID19 patients with bacterial coinfection less than in flu pandemics • Higher proportion of critically-ill with bacterial coinfections than in mixed setting • Bacterial co-pathogen profiles different to those in influenza co-infections • Fungal coinfection diagnosis difficult so high level suspicion in critically-ill

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Bacterial co-infection and secondary infection in patients with COVID-19: a living rapid review and meta-analysis

Bradley Langford, Miranda So, Sumit Raybardhan … (2020)

Background Bacterial co-pathogens are commonly identified in viral respiratory infections and are important causes of morbidity and mortality. The prevalence of bacterial infection in patients infected with SARS-CoV-2 is not well understood. Aims To determine the prevalence of bacterial co-infection (at presentation) and secondary infection (after presentation) in patients with COVID-19. Sources We performed a systematic search of MEDLINE, OVID Epub and EMBASE databases for English language literature from 2019 to April 16, 2020. Studies were included if they (a) evaluated patients with confirmed COVID-19 and (b) reported the prevalence of acute bacterial infection. Content Data were extracted by a single reviewer and cross-checked by a second reviewer. The main outcome was the proportion of COVID-19 patients with an acute bacterial infection. Any bacteria detected from non-respiratory-tract or non-bloodstream sources were excluded. Of 1308 studies screened, 24 were eligible and included in the rapid review representing 3338 patients with COVID-19 evaluated for acute bacterial infection. In the meta-analysis, bacterial co-infection (estimated on presentation) was identified in 3.5% of patients (95%CI 0.4–6.7%) and secondary bacterial infection in 14.3% of patients (95%CI 9.6–18.9%). The overall proportion of COVID-19 patients with bacterial infection was 6.9% (95%CI 4.3–9.5%). Bacterial infection was more common in critically ill patients (8.1%, 95%CI 2.3–13.8%). The majority of patients with COVID-19 received antibiotics (71.9%, 95%CI 56.1 to 87.7%). Implications Bacterial co-infection is relatively infrequent in hospitalized patients with COVID-19. The majority of these patients may not require empirical antibacterial treatment.

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Author and article information

Contributors

Herman W. Barkema:

ORCID: http://orcid.org/0000-0002-9678-8378

barkema@ucalgary.ca

Journal

Journal ID (nlm-ta): Antimicrob Resist Infect Control

Journal ID (iso-abbrev): Antimicrob Resist Infect Control

Title: Antimicrobial Resistance and Infection Control

Publisher: BioMed Central (London )

ISSN (Electronic): 2047-2994

Publication date (Electronic): 7 March 2022

Publication date PMC-release: 7 March 2022

Publication date Collection: 2022

Volume: 11

Electronic Location Identifier: 45

Affiliations

[1 ]Antimicrobial Resistance - One Health Consortium, Calgary, AB Canada

[2 ]GRID grid.17089.37, ISNI 0000 0001 2190 316X, Division of Diagnostic and Applied Microbiology, Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, , University of Alberta, ; Edmonton, AB Canada

[3 ]Alberta Precision Laboratories - Public Health Laboratory (ProvLab), Edmonton, AB Canada

[4 ]GRID grid.22072.35, ISNI 0000 0004 1936 7697, Departments of Medicine, Microbiology, Immunology and Infectious Diseases, and Community Health Sciences, O’Brien Institute for Public Health and Snyder Institute for Chronic Diseases, , University of Calgary, ; Calgary, AB Canada

[5 ]GRID grid.22072.35, ISNI 0000 0004 1936 7697, Departments of Medicine, Pathology and Laboratory Medicine, Microbiology, Immunology and Infectious Diseases, O’Brien Institute for Public Health, Snyder Institute for Chronic Diseases, , University of Calgary and Alberta Health Services, ; Calgary, AB Canada

[6 ]GRID grid.17089.37, ISNI 0000 0001 2190 316X, Division of Infectious Diseases, Department of Medicine, Faculty of Medicine and Dentistry, , University of Alberta, ; Edmonton, AB Canada

[7 ]GRID grid.22072.35, ISNI 0000 0004 1936 7697, Department of Community Health Sciences, O’Brien Institute for Public Health, , University of Calgary, ; Calgary, AB Canada

[8 ]GRID grid.22072.35, ISNI 0000 0004 1936 7697, Departments of Production Animal Health and Community Health Sciences,, , One Health at UCalgary, University of Calgary, ; 3330 Hospital Drive NW, Calgary, T2N 4N1 Canada

Author information

Herman W. Barkema http://orcid.org/0000-0002-9678-8378

Article

Publisher ID: 1085

DOI: 10.1186/s13756-022-01085-z

PMC ID: 8899460

PubMed ID: 35255988

SO-VID: 3155da97-dbc4-433a-bc2c-032e6f2588da

License:

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