Evidence map›Paper›PMID 27647271›Full record

ArticleAnnals of clinical microbiology and antimicrobials2016

Molecular characterization of Staphylococcus aureus isolates from various healthcare institutions in Nairobi, Kenya: a cross sectional study.

Geoffrey Omuse, Kristien Nel Van Zyl, Kim Hoek, Shima Abdulgader, Samuel Kariuki, Andrew Whitelaw, Gunturu Revathi

Open access · goldAbstract read
In one paragraph

Article in Annals of clinical microbiology and antimicrobials, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.8field-weighted citation impact, top 7% 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

21 citing papers in PubMed, 38 citations in OpenAlex.

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  8. Genetic Diversity ofMicroorganisms · 2021
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  9. Methicillin-Resistant Coagulase-NegativeThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2021
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  10. Review
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  15. Article
  16. Review
  17. Article
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  19. Article
  20. Distribution of the Most PrevalentFrontiers in microbiology · 2018
    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 2 countries.

Geoffrey OmuseDepartment of Pathology, Aga Khan University Hospital Nairobi, P.O. Box 30270-00100, Nairobi, Kenya. g_omuse@yahoo.com.
Kristien Nel Van ZylDivision of Medical Microbiology, Department of Pathology, Stellenbosch University, P. O. Box 19063, Western Cape, South Africa.
Kim HoekDivision of Medical Microbiology, Department of Pathology, Stellenbosch University, P. O. Box 19063, Western Cape, South Africa.
Shima AbdulgaderDivision of Medical Microbiology, Department of Pathology, Faculty of Health Sciences, University of Cape Town, South Africa, P.O. Box 7925, Cape Town, South Africa.
Samuel KariukiCenter of Microbiology Research, Kenya Medical Research Institute, P.O. Box 54840-00200, Nairobi, Kenya.
Andrew WhitelawDivision of Medical Microbiology, Department of Pathology, Stellenbosch University, P. O. Box 19063, Western Cape, South Africa.
Gunturu RevathiDepartment of Pathology, Aga Khan University Hospital Nairobi, P.O. Box 30270-00100, Nairobi, Kenya.
Stellenbosch University · ZAAga Khan University Hospital Nairobi · KEAga Khan University Nairobi · KEKenya Medical Research Institute · KEUniversity of Cape Town · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStaphylococcus aureus (S. aureus) has established itself over the years as a major cause of morbidity and mortality both within the community and in healthcare settings. Methicillin resistant S. aureus (MRSA) in particular has been a major cause of nosocomial infections resulting in significant increase in healthcare costs. In Africa, the MRSA prevalence has been shown to vary across different countries. In order to better understand the epidemiology of MRSA in a setting, it is important to define its population structure using molecular tools as different clones have been found to predominate in certain geographical locations.

methodsWe carried out PFGE, MLST, SCCmec and spa typing of selected S. aureus isolates from a private and public referral hospital in Nairobi, Kenya.

resultsA total of 93 S. aureus isolates were grouped into 19 PFGE clonal complexes (A-S) and 12 singletons. From these, 55 (32 MRSA and 23 MSSA) representative isolates from each PFGE clonal complex and all singletons were spa typed. There were 18 different MRSA spa types and 22 MSSA spa types. The predominant MRSA spa type was t037 comprising 40.6 % (13/32) of all MRSA. In contrast, the MSSA were quite heterogeneous, only 2 out of 23 MSSA shared the same spa type. Two new MRSA spa types (t13149 and t13150) and 3 new MSSA spa types (t13182, t13193 and t13194) were identified. The predominant clonal complex was CC 5 which included multi-locus sequence types 1, 8 and 241.

conclusionIn contrast to previous studies published from Kenya, there's marked genetic diversity amongst clinical MRSA isolates in Nairobi including the presence of well-known epidemic MRSA clones. Given that these clones are resident within our referral hospitals, adherence to strict infection control measures needs to be ensured to reduce morbidity and mortality associated with hospital acquired MRSA infections.

Indexed as

GenotypeAnti-Bacterial AgentsClone CellsCross InfectionCross-Sectional StudiesDNA, BacterialDrug Resistance, Multiple, BacterialHospitals, PrivateHospitals, PublicHumansKenyaMethicillin-Resistant Staphylococcus aureusMicrobial Sensitivity TestsMolecular EpidemiologyMultilocus Sequence TypingPhylogenyAnti-Bacterial AgentsDNA, BacterialKenyaMRSAMSSAStaphylococcus aureus

Identifiers

PMID27647271
PMCPMC5029008
OpenAlexW2521091734

What OpenQuestion holds

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LicenceCC BY
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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.