Cited by 102Antibiotic Use and ResistanceAntibiotic Resistance in BacteriaPharmaceutical and Antibiotic Environmental Impacts

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

PRO: The COVID-19 pandemic will result in increased antimicrobial resistance rates

Open access
Clancy, Cornelius J, Buehrle, Deanna J, Nguyen, M Hong·2020·JAC-Antimicrobial Resistance

Abstract

We argue that the COVID-19 pandemic will result in increased antimicrobial resistance (AMR). Broad-spectrum antibiotic use is common among hospitalized COVID-19 patients and in excess of reported secondary infection rates, suggesting unnecessary prescribing. Selection pressure is likely to be particularly intense in COVID-19 epicentres and within non-epicentre hospital units dedicated to COVID-19 care. Risk factors that increase the likelihood of hospitalization or poor outcomes among COVID-19 patients, such as advanced age, nursing home residence, debilitation, diabetes and cardiopulmonary or other underlying systemic diseases, also predispose to AMR infections. Worry for AMR emergence is heightened since first-wave COVID-19 epicentres were also AMR epicentres. Disruptive direct and indirect effects of COVID-19 globally on economic systems, governance and public health expenditure and infrastructure may fuel AMR spread. We anticipate that the impact of COVID-19 on AMR will vary between epicentres and non-epicentres, by geographic region, hospital to hospital within regions and within specific hospital units.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/jacamr/dlaa049

Cites

17 of 17 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1. Weekly in-hospital antibiotic use and BDOC in a healthcare system outside of a COVID-19 epicentre, 1 March to 2 May 2020. Data are presented as 3 week rolling averages of numbers of in-hospital antibiotic DOT, BDOC and DOT/1000 BDOC (y-axis) each week (x-axis; dates represent the first day of a given week). In-hospital antibiotic DOT and BDOC per week decreased significantly from 1 March to 2 May 2020. Note the increase in DOT/1000 BDOC. The week-to-week difference in DOT/1000 BDOC over the time period was not statistically significant. However, since antibiotic use is likely concentrated in patients with COVID-19, the data suggest that selection pressure may be markedly increased within hospital units devoted to COVID-19 care, even at centres outside a disease epicentre.
Figure 1. Weekly in-hospital antibiotic use and BDOC in a healthcare system outside of a COVID-19 epicentre, 1 March to 2 May 2020. Data are presented as 3 week rolling averages of numbers of in-hospital antibiotic DOT, BDOC and DOT/1000 BDOC (y-axis) each week (x-axis; dates represent the first day of a given week). In-hospital antibiotic DOT and BDOC per week decreased significantly from 1 March to 2 May 2020. Note the increase in DOT/1000 BDOC. The week-to-week difference in DOT/1000 BDOC over the time period was not statistically significant. However, since antibiotic use is likely concentrated in patients with COVID-19, the data suggest that selection pressure may be markedly increased within hospital units devoted to COVID-19 care, even at centres outside a disease epicentre.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 1

  1. Clancy, 2020, COVID–19, superinfections and antimicrobial development: what can we expect?, Clin Infect Dis

Cited by

Sorted by citations

See all 102

Metadata

Authors
Clancy, C. J., Buehrle, D. J., & Nguyen, M. H.
Affiliations
  • University of Pittsburgh (US)
  • VA Pittsburgh Healthcare System (US)
Corresponding author
Clancy, Cornelius J
Venue
JAC-Antimicrobial Resistance
Published
2020-07-17
Volume
2
Issue
3
Pages
dlaa049-dlaa049
ISSN
2632-1823 (ISSN-L)
OpenAlex
W3044722900
Cited by
102
References
17
Citations by year
2026: 3 · 2025: 9 · 2024: 9 · 2023: 18 · 2022: 27 · 2021: 31 · 2020: 5
FWCI
12.05
Type
journal article
Language
en
Open access
Locations
  • JAC-Antimicrobial Resistance (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Infectious Diseases › Antibiotic Use and Resistance
  • Health Sciences › Medicine › Microbiology (medical) › Antibiotic Resistance in Bacteria
  • Physical Sciences › Environmental Science › Pollution › Pharmaceutical and Antibiotic Environmental Impacts
Keywords
COVID-19 pandemic, antimicrobial resistance, broad-spectrum antibiotic use, secondary infection, selection pressure, nosocomial infections, antibiotic prescribing

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review