Evidence map›Paper›PMID 34900756›Full record

ReviewFrontiers in cellular and infection microbiology2021

Antibiotic Resistance: One Health One World Outlook.

Bilal Aslam, Mohsin Khurshid, Muhammad Imran Arshad, Saima Muzammil, Maria Rasool, Nafeesa Yasmeen, Taif Shah, Tamoor Hamid Chaudhry, Muhammad Hidayat Rasool, Aqsa Shahid and 2 more

Erratum issued Registry-linked trialAbstract readReview
In one paragraph

Review in Frontiers in cellular and infection microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT07167173 (Predictive Model for Multidrug Resistance in Patients Admitted to the Emergency Department With Sepsis), which is not on this map. Cited by 315 papers.

0numbers the graph read from it
0cells of the map it votes in
315citing papers in PubMed
–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.

NCT07167173 not yet recruitingnot on this mapstarted 2025, after this paper: background citation

Predictive Model for Multidrug Resistance in Patients Admitted to the Emergency Department With Sepsis

TypeobservationalSponsorHospital Italiano de Buenos AiresRan2025 to 2025Enrolled10,000ConditionsSepsis, Septic Shock
3 · Its place in the literature

Who cites it

315 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Sales of antimicrobials for veterinary use, Bangladesh, 2023.Bulletin of the World Health Organization · 2026
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Pacin, a novel bacteriocin fromMicrobiology spectrum · 2026
    Article
  13. Review
  14. Article
  15. Article
  16. Genomic Characterization, Antimicrobial Resistance Profiles, andAnimals : an open access journal from MDPI · 2026
    Article
  17. Review
  18. Review
  19. One health (Amsterdam, Netherlands) · 2026
    Article
  20. Review

255 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Bilal AslamDepartment of Microbiology, Government College University Faisalabad, Faisalabad, Pakistan.
Mohsin KhurshidDepartment of Microbiology, Government College University Faisalabad, Faisalabad, Pakistan.
Muhammad Imran ArshadInstitute of Microbiology, University of Agriculture, Faisalabad, Pakistan.
Saima MuzammilDepartment of Microbiology, Government College University Faisalabad, Faisalabad, Pakistan.
Maria RasoolDepartment of Microbiology, Government College University Faisalabad, Faisalabad, Pakistan.
Nafeesa YasmeenCollege of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Taif ShahFaculty of Life Science and Technology, Kunming University of Life Science and Technology, Kunming, China.
Tamoor Hamid ChaudhryDepartment of Microbiology, Government College University Faisalabad, Faisalabad, Pakistan.
Muhammad Hidayat RasoolDepartment of Microbiology, Government College University Faisalabad, Faisalabad, Pakistan.
Aqsa ShahidFaculty of Rehabilitation and Allied Health Sciences, Riphah International University, Faisalabad, Pakistan.
Xia XueshanFaculty of Life Science and Technology, Kunming University of Life Science and Technology, Kunming, China.
Zulqarnain BalochFaculty of Life Science and Technology, Kunming University of Life Science and Technology, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic resistance (ABR) is a growing public health concern worldwide, and it is now regarded as a critical One Health issue. One Health's interconnected domains contribute to the emergence, evolution, and spread of antibiotic-resistant microorganisms on a local and global scale, which is a significant risk factor for global health. The persistence and spread of resistant microbial species, and the association of determinants at the human-animal-environment interface can alter microbial genomes, resulting in resistant superbugs in various niches. ABR is motivated by a well-established link between three domains: human, animal, and environmental health. As a result, addressing ABR through the One Health approach makes sense. Several countries have implemented national action plans based on the One Health approach to combat antibiotic-resistant microbes, following the Tripartite's Commitment Food and Agriculture Organization (FAO)-World Organization for Animal Health (OIE)-World Health Organization (WHO) guidelines. The ABR has been identified as a global health concern, and efforts are being made to mitigate this global health threat. To summarize, global interdisciplinary and unified approaches based on One Health principles are required to limit the ABR dissemination cycle, raise awareness and education about antibiotic use, and promote policy, advocacy, and antimicrobial stewardship.

Indexed as

One HealthAnimalsAnti-Bacterial AgentsDrug Resistance, MicrobialGlobal HealthHumansPublic HealthAnti-Bacterial Agentsanimalantibiotic resistanceenvironmenthumanOne Health

Identifiers

PMID34900756
PMCPMC8656695

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.