Evidence map›Paper›PMID 39843577›Full record

Reviewnpj antimicrobials and resistance2024

Limitations of current techniques in clinical antimicrobial resistance diagnosis: examples and future prospects.

Jack Hassall, Carmen Coxon, Vishal C Patel, Simon D Goldenberg, Chrysi Sergaki

Abstract readReview
In one paragraph

Review in npj antimicrobials and resistance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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.

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

46 citing papers in PubMed.

  1. Trial
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  10. Low-Abundance and FragmentaryBiomolecules · 2026
    Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Polymyxin heteroresistance inJournal of medical microbiology · 2026
    Article
  16. Review
  17. Article
  18. Review
  19. Metallo-β-lactamase-producingFrontiers in microbiology · 2026
    Review
  20. Review
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

5 authors.

Jack HassallScience Research and Innovation, Medicines and Healthcare products Regulatory Agency, Blanche Lane, South Mimms, Potters Bar, Hertfordshire, EN6 3QG, UK.
Carmen CoxonScience Research and Innovation, Medicines and Healthcare products Regulatory Agency, Blanche Lane, South Mimms, Potters Bar, Hertfordshire, EN6 3QG, UK.
Vishal C PatelThe Roger Williams Institute of Hepatology London, Foundation for Liver Research, 111 Coldharbour Lane, London, SE5 9NT, UK.
Simon D GoldenbergCentre for Clinical Infection and Diagnostics Research, Guy's and St Thomas' NHS Foundation Trust and King's College, London, UK.
Chrysi SergakiScience Research and Innovation, Medicines and Healthcare products Regulatory Agency, Blanche Lane, South Mimms, Potters Bar, Hertfordshire, EN6 3QG, UK. chrysi.sergaki@mhra.gov.uk.ORCID http://orcid.org/0000-0003-0477-8680

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance is a global threat to public health. Without proactive intervention, common infections may become untreatable, restricting the types of clinical intervention that can be undertaken and reversing improvements in mortality rates. Effective antimicrobial stewardship represents one approach to restrict the spread of antimicrobial resistance but relies on rapid and accurate diagnostics that minimise the unnecessary use of antibiotics. This is increasingly a key unmet clinical need. In this paper, we describe existing techniques for the detection of antimicrobial resistance, while examining their drawbacks and limitations. We also discuss emerging diagnostic technologies in the field, and the need for standardisation to allow for swifter and more widespread clinical adoption.

Identifiers

PMID39843577
PMCPMC11721362

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Registered trials

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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.