Evidence map›Paper›PMID 33341485›Full record

ReviewJournal of infection and public health2021

The interrelationships between antimicrobial resistance, COVID-19, past, and future pandemics.

Hyacinth O Ukuhor

Abstract readReview
In one paragraph

Review in Journal of infection and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  18. Treatment and Management ofInfection and drug resistance · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Hyacinth O UkuhorSaudi Electronic University, Department of Public Health, P. O. Box 93499, Riyadh 11673, Saudi Arabia. Electronic address: hyacoo2000@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 was first reported in Wuhan, China in December 2019 and is associated with high levels of morbidity and mortality. Various types of bacterial and fungal infections occur in patients with COVID-19 with some resistant to antimicrobials that are associated with significantly worse outcomes and deaths. Besides, antimicrobial-resistant (AMR) co-infections are responsible for clinically significant mortality in past pandemics. There is evidence to suggest that factors such as the proliferation of adulterated antimicrobials in some developing countries, international travels, issues with healthcare financing, use/misuse by humans, and in agricultural production and climate change are determinants of AMR at various levels of society. These complex interrelated determinants intersect with AMR in current and past pandemics and could amplify the potential of a future antimicrobial resistance pandemic. Therefore, global concerted interventions targeted at all levels of society to reduce the use/misuse of antimicrobials and disrupt these multifaceted, interrelated, and interdependent factors are urgently needed. This paper leverages prior research to describe complex major determinants of antimicrobial resistance and provides fresh insights into possible intervention strategies to tackle antimicrobial resistance including in the current and future pandemics.

Indexed as

Anti-Bacterial AgentsAntimicrobial StewardshipCOVID-19Drug Resistance, BacterialSARS-CoV-2Global HealthHumansAnti-Bacterial AgentsAntibioticsAntimicrobial resistanceDeterminantsInfectionsPandemics

Identifiers

PMID33341485
PMCPMC7831651

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.