Evidence map›Paper›PMID 36048838›Full record

ArticlePloS one2022

Bacteriological quality and antimicrobial susceptibility profiles of isolates of ready-to-eat raw minced meat from hotels and restaurants in Arba Minch, Ethiopia.

Tomas Tonjo, Aseer Manilal, Mohammed Seid

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. 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

3 authors.

Tomas TonjoDepartment of Medical Laboratory Science, College of Medicine and Health Sciences, Arba Minch University, Arba Minch, Ethiopia.
Aseer ManilalDepartment of Medical Laboratory Science, College of Medicine and Health Sciences, Arba Minch University, Arba Minch, Ethiopia.ORCID 0000-0002-1146-8093
Mohammed SeidDepartment of Medical Laboratory Science, College of Medicine and Health Sciences, Arba Minch University, Arba Minch, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Ethiopia, the bacteriological quality of ready-to-eat raw meat is of a great public health concern as it can serve as a source of meat-borne pathogens and worsen the transmission of antimicrobial resistant bacteria, and hence this cross-sectional study, done on 257 meat samples (ie., 169 beef, 50 mutton and 38 chevon) from randomly selected hotels and restaurants (n = 52). Approximately 25 gm of meat samples were taken bi-weekly and subjected to quantitative and qualitative analyses; antimicrobial susceptibility tests were done as per the Kirby-Bauer disk diffusion method. It was found that 13.2 (n = 34), 17.5 (n = 45) and 21.8% (n = 56) samples exceeded the permissible limit for total viable and coliform and S. aureus counts, respectively. At the same time, 24.9% (n = 64) surpassed the bacteriological limit permissible for consumption. Overall, 36.6% (n = 94) of samples were extrapolated as unsatisfactory for consumption due to high bacterial load and or the presence of pathogens. Five different bacterial spp. such as E. coli 65% (n = 167), S. aureus 59% (n = 152), Salmonella spp. 28.4% (n = 73), Campylobacter spp. 14.4% (n = 37) and Shigella spp. 4.3% (n = 11) were isolated in varied proportions. Alarmingly, 60% (n = 264) of the isolates were multi-drug resistant and 51% of S. aureus were found to be MRSA.

Indexed as

Escherichia coliRestaurantsAnimalsAnti-Bacterial AgentsCattleCross-Sectional StudiesEthiopiaMeatMicrobial Sensitivity TestsStaphylococcus aureusAnti-Bacterial Agents

Identifiers

PMID36048838
PMCPMC9436051

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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.