Evidence map›Paper›PMID 38791788›Full record

ArticleInternational journal of environmental research and public health2024

Surveillance of Bacterial Load and Multidrug-Resistant Bacteria on Surfaces of Public Restrooms.

Khadega Ibrahim, Maisha Tahsin, Aninda Rahman, Shaikh Mizanoor Rahman, Md Mizanur Rahman

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

5 authors.

Khadega IbrahimFlow Cytometry Core, Research Department, Sidra Medicine, Doha, Qatar.ORCID 0000-0002-9238-5942
Maisha TahsinIndependent Researcher, Dhaka 1216, Bangladesh.
Aninda RahmanCommunicable Disease Control, Directorate General of Health Services, Ministry of Health & Family Welfare, Dhaka 1212, Bangladesh.
Shaikh Mizanoor RahmanNatural and Medical Sciences Research Center, University of Nizwa, Nizwa 616, Oman.ORCID 0000-0002-4879-2663
Md Mizanur RahmanBiological Science Program, Department of Biological and Environmental Sciences, Collage of Arts and Sciences, Qatar University, Doha 2713, Qatar.ORCID 0000-0002-7909-8375

Funding

Qatar University QUCG-CAS-21/22-2 and QUCG-CAS-23
6 · The paper itself

Abstract

Public restrooms are often a hub of microbial contamination and the examination of bacterial contamination in these facilities can serve as an important indicator of the transmission of infectious diseases. This study was conducted to determine the prevalence of bacterial contamination in public restrooms based on the economic class of the building. Samples were collected from various spots in 32 restrooms found in 10 shopping malls, classifying them into two categories: upper-end restrooms and lower-end restrooms. The findings showed that the level of contamination was higher in the lower-end restrooms, with the seat being the most contaminated area. The most dominant Gram-positive bacteria were of the coagulase-negative staphylococci species, making up 86% of the identified Gram-positive isolates. The most dominant Gram-negative bacteria identified were

Indexed as

Drug Resistance, Multiple, BacterialGram-Negative BacteriaGram-Positive BacteriaToilet FacilitiesAnti-Bacterial AgentsBacterial LoadHumansMicrobial Sensitivity TestsTanzaniaAnti-Bacterial Agentsantibiotic resistancebacteriaGram-positive/negativemultidrug-resistantpublic restrooms

Identifiers

PMID38791788
PMCPMC11120863

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.