Evidence map›Paper›PMID 31670275›Full record

ArticleThe Indian journal of medical research2019

Detection of heterogeneous vancomycin-intermediate

Rajesh Amberpet, Sujatha Sistla, Madhan Sugumar, Niveditha Nagasundaram, Meerabai Manoharan, Subhash Chandra Parija

Open access · diamondAbstract read
In one paragraph

Article in The Indian journal of medical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 22% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Molecular and Clinical Features of Heterogeneous Vancomycin-IntermediateSultan Qaboos University medical journal · 2023
    Article
  9. Epidemiology ofAntibiotics (Basel, Switzerland) · 2023
    Review
  10. Article
  11. Methicillin- and Vancomycin-ResistantFrontiers in microbiology · 2021
    Article
  12. Article
  13. Prevalence and Therapies of Antibiotic-Resistance inFrontiers in cellular and infection microbiology · 2020
    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

6 authors at 1 institution in 1 country.

Rajesh AmberpetDepartment of Microbiology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, India.
Sujatha SistlaDepartment of Microbiology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, India.
Madhan SugumarDepartment of Microbiology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, India.
Niveditha NagasundaramDepartment of Microbiology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, India.
Meerabai ManoharanDepartment of Microbiology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, India.
Subhash Chandra ParijaDepartment of Microbiology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, India.
Jawaharlal Institute of Post Graduate Medical Education and Research · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background & objectives: Although there are reports of heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) across the globe, there is a lack of reliable data on hVISA in India. The present study was undertaken to determine the rate of hVISA among the methicillin-resistant Staphylococcus aureus (MRSA) isolates, and to compare the brain heart infusion agar with vancomycin 4 μg/ml (BHIV4) method with population analysis profile-area under the curve (PAP-AUC) method for the detection of hVISA and to study the distribution of mobile genetic element that carries methicillin-resistance gene SCCmec (Staphylococcal cassette chromosome mec) types among these isolates. Methods: BHIV4 and PAP-AUC methods were employed to detect hVISA among 500 clinical isolates of MRSA. SCCmec typing of these isolates was performed by multiplex polymerase chain reaction. The clinical presentation, treatment with vancomycin and outcome was documented for patients with hVISA. Results: The rate of hVISA was 12.4 per cent by PAP-AUC method. Sensitivity, specificity, PPV, NPV and kappa agreement of BHIV4 with PAP-AUC was 58.06, 93.15, 54.55, 94.01 per cent and 0.498, respectively. The isolation of hVISA was significantly (P<0.01) higher in patients admitted to intensive care units and wards than in patients attending the outpatient departments. Only 38 per cent of the patients received vancomycin as therapy. Majority of the hVISA isolates carried SCCmec type V or IV. Interpretation & conclusions: The rate of hVISA isolation in our study was 12.4 per cent. The sensitivity of the BHIV4 screening test was low, and was in moderate agreement with PAP-AUC test. SCCmec type V was the predominant type seen in half of the isolates. More studies need to be done in different parts of the country on a large number of isolates to confirm our findings.

Indexed as

Anti-Bacterial AgentsArea Under CurveBacterial ProteinsCulture MediaHumansIndiaInterspersed Repetitive SequencesMethicillin-Resistant Staphylococcus aureusMicrobial Sensitivity TestsPenicillin-Binding ProteinsStaphylococcal InfectionsVancomycinVancomycin ResistanceAnti-Bacterial AgentsBacterial ProteinsCulture MediamecA protein, Staphylococcus aureusPenicillin-Binding ProteinsVancomycinBHIV4hVISAmecAmethicillin-resistant Staphylococcus aureusPAP methodSCC mec typevancomycin

Identifiers

PMID31670275
PMCPMC6829776
OpenAlexW2980525920

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.