Evidence map›Paper›PMID 34124266›Full record

ArticleBioMed research international2021

Trends of Antibacterial Resistance at the National Reference Laboratory in Cameroon: Comparison of the Situation between 2010 and 2017.

M Massongo, L Ngando, E W Pefura Yone, Ariane NZouankeu, W Mbanzouen, M C Fonkoua, A Ngandjio, J Tchatchueng, D Barger, M C Tejiokem

Abstract read
In one paragraph

Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Antimicrobial resistance trends in clinicalAfrican journal of laboratory medicine · 2024
    Article
  9. Article
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

10 authors.

M MassongoFaculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Yaoundé, Cameroon.ORCID https://orcid.org/0000-0002-7531-4755
L NgandoFaculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Yaoundé, Cameroon.
E W Pefura YoneFaculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Yaoundé, Cameroon.
Ariane NZouankeuJamot Hospital, Yaoundé, Cameroon.
W MbanzouenBacteriology Unit, Cameroon Pasteur Centre, Member of Institut Pasteur International Network, Yaoundé, Cameroon.
M C FonkouaEpidemiology and Public Health Unit, Cameroon Pasteur Centre, Member of Institut Pasteur International Network, Yaoundé, Cameroon.
A NgandjioEpidemiology and Public Health Unit, Cameroon Pasteur Centre, Member of Institut Pasteur International Network, Yaoundé, Cameroon.
J TchatchuengEpidemiology and Public Health Unit, Cameroon Pasteur Centre, Member of Institut Pasteur International Network, Yaoundé, Cameroon.
D BargerBordeaux School of Public Health (ISPED), University of Bordeaux, Inserm 1219 Bordeaux Population Health, Bordeaux, France.
M C TejiokemEpidemiology and Public Health Unit, Cameroon Pasteur Centre, Member of Institut Pasteur International Network, Yaoundé, Cameroon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAntimicrobial resistance represents a growing public health threat. One of the World Health Organization's strategic objectives is "strengthening knowledge through surveillance and research." Sub-Saharan African countries are still far from achieving this objective. We aimed to estimate and compare the prevalence of antibacterial resistance in 2010 and 2017 in Cameroon.

methodsWe conducted a retrospective study on all clinical specimens cultured in Centre Pasteur du Cameroun (CPC) in 2010 and 2017. Data were extracted from the CPC's laboratory data information system software and then managed and analyzed using R. Bacterial resistance rates were calculated in each year and compared using chi-square or Fisher's tests, and relative changes were calculated. Outcomes included acquired resistance (AR), WHO priority resistant pathogens, some specific resistances of clinical interest, and resistance patterns (multi, extensively, and pan drug resistances) for five selected pathogens.

resultsA total of 10,218 isolates were analyzed. The overall AR rate was 96.0% (95% CI: 95.4-96.6). Most of WHO priority bacterial resistance rates increased from 2010 to 2017. The most marked increases expressed as relative changes concerned imipenem-resistant

conclusionBacterial resistance to antibiotics of clinical relevance in Cameroon was high and appeared to increase between 2010 and 2017. There is a need for regular surveillance of antibacterial resistance to inform public health strategies and empirically inform prescription practices.

Indexed as

BacteriaBacterial InfectionsDrug Resistance, BacterialAdolescentAdultAnti-Bacterial AgentsCameroonChildChild, PreschoolFemaleHumansInfantMaleMicrobial Sensitivity TestsMiddle AgedRetrospective StudiesAnti-Bacterial Agents

Identifiers

PMID34124266
PMCPMC8166466

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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.