Evidence map›Paper›PMID 31871459›Full record

ArticleInternational journal of microbiology2019

Contamination of the Surfaces of a Health Care Environment by Multidrug-Resistant (MDR) Bacteria.

Laila Chaoui, RajaaAit Mhand, Fouad Mellouki, Naima Rhallabi

Abstract read
In one paragraph

Article in International journal of microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

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

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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

4 authors.

Laila ChaouiProvincial Diagnostic Laboratory Epidemiological and Environmental Health, Provincial Health Delegation, Mohammedia, Morocco.ORCID https://orcid.org/0000-0002-1269-0438
RajaaAit MhandResearch Unit Microbiology Hygiene Bioactives Molecules Laboratory Virology Microbiology Quality and Biotechnology/Ecotoxicology Biodiversity, University Hassan II Casablanca, FSTM, Mohammedia, Morocco.
Fouad MelloukiResearch Unit Microbiology Hygiene Bioactives Molecules Laboratory Virology Microbiology Quality and Biotechnology/Ecotoxicology Biodiversity, University Hassan II Casablanca, FSTM, Mohammedia, Morocco.
Naima RhallabiResearch Unit Microbiology Hygiene Bioactives Molecules Laboratory Virology Microbiology Quality and Biotechnology/Ecotoxicology Biodiversity, University Hassan II Casablanca, FSTM, Mohammedia, Morocco.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nosocomial infections (NIs) are known worldwide and remain a major problem despite scientific and technical advances in the field of health. The severity of the infection depends on the characteristics of the microorganisms involved and the high frequency of resistant pathogens in the hospital environment. The aim of this study is to determine the distribution of pathogenic bacteria (and their resistance to antibiotics) that spread on hospital surfaces, more specifically, on those of various departments in the Provincial Hospital Center (PHC) of Mohammedia, Morocco. A cross-sectional study was conducted from March 2017 to April 2018. Samples were collected by swabbing the hospital surfaces, and the isolated bacteria were checked for their susceptibility to antibiotics by the Kirby-Bauer disk diffusion method following the standards of the Clinical and Laboratory Standards Institute (CLSI). Among 200 swab samples, 176 (88%) showed bacterial growth. Gram-negative isolates were predominant at 51.5% (101/196), while the Gram-positives were at 48.5% (95/196). The main isolates are

Identifiers

PMID31871459
PMCPMC6906863

What OpenQuestion holds

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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.