Evidence map›Paper›PMID 28615273›Full record

ArticleBMJ open2017

Analysis of the potential for point-of-care test to enable individualised treatment of infections caused by antimicrobial-resistant and susceptible strains of

Katy Me Turner, Hannah Christensen, Elisabeth J Adams, David McAdams, Helen Fifer, Anthony McDonnell, Neil Woodford

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 3 pooled it
5.2field-weighted citation impact, top 4% of its field
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

33 citing papers in PubMed, 3 syntheses or guidelines pooled it, 45 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Rapid Cas13a-basedmSphere · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Molecular detection of fluoroquinolone-resistantFrontiers in cellular and infection microbiology · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  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

7 authors at 5 institutions in 3 countries.

Katy Me TurnerSchool of Veterinary Sciences, University of Bristol, Langford House, Bristol, UK.ORCID 0000-0002-8152-6017
Hannah ChristensenSchool of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
Elisabeth J AdamsAquarius Population Health, London, UK.
David McAdamsDuke Fuqua School of Business, Durham, USA.
Helen FiferBacteriology Reference Department, National Infection Service, Public Health England, London, UK.
Anthony McDonnellThe O'Neill Review on Antimicrobial Resistance, Wellcome Trust, London, UK.
Neil WoodfordBacteriology Reference Department, National Infection Service, Public Health England, London, UK.
Public Health England · GBUniversity of Bristol · GBAquarius Population Health · GBCNR de la Résistance aux Antibiotiques · FRDuke University · US

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectiveTo create a mathematical model to investigate the treatment impact and economic implications of introducing an antimicrobial resistance point-of-care test (AMR POCT) for gonorrhoea as a way of extending the life of current last-line treatments.

designModelling study.

settingEngland. POPULATION: Patients accessing sexual health services.

interventionsIncremental impact of introducing a hypothetical AMR POCT that could detect susceptibility to previous first-line antibiotics, for example, ciprofloxacin or penicillin, so that patients are given more tailored treatment, compared with the current situation where all patients are given therapy with ceftriaxone and azithromycin. The hypothetical intervention was assessed using a mathematical model developed in Excel. The model included initial and follow-up attendances, loss to follow-up, use of standard or tailored treatment, time taken to treatment and the costs of testing and treatment.

main outcome measuresNumber of doses of ceftriaxone saved, mean time to most appropriate treatment, mean number of visits per (infected) patient, number of patients lost to follow-up and total cost of testing.

resultsIn the current situation, an estimated 33 431 ceftriaxone treatments are administered annually and 792 gonococcal infections remain untreated due to loss to follow-up. The use of an AMR POCT for ciprofloxacin could reduce these ceftriaxone treatments by 66%, and for an AMR POCT for penicillin by 79%. The mean time for patients receiving an antibiotic treatment is reduced by 2 days in scenarios including POCT and no positive patients remain untreated through eliminating loss to follow-up. Such POCTs are estimated to add £34 million to testing costs, but this does not take into account reductions in costs of repeat attendances and the reuse of older, cheaper antimicrobials.

conclusionsThe introduction of AMR POCT could allow clinicians to discern between the majority of gonorrhoea-positive patients with strains that could be treated with older, previously abandoned first-line treatments, and those requiring our current last-line dual therapy. Such tests could extend the useful life of dual ceftriaxone and azithromycin therapy, thus pushing back the time when gonorrhoea may become untreatable.

Indexed as

Drug Resistance, BacterialAnti-Bacterial AgentsAzithromycinCeftriaxoneCiprofloxacinCost-Benefit AnalysisEnglandFemaleGonorrheaHumansLost to Follow-UpMaleMicrobial Sensitivity TestsModels, TheoreticalNeisseria gonorrhoeaePenicillinsAnti-Bacterial AgentsAzithromycinCeftriaxoneCiprofloxacinPenicillinsantimicrobial-resistanceneisseria gonorrhoeaepoint-of-care test

Identifiers

PMID28615273
PMCPMC5734280
OpenAlexW2616096059

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.