Evidence map›Paper›PMID 34339002›Full record

ArticleFolia microbiologica2021

Prevalence of antibiotic-resistant bacterial strains in wastewater streams: molecular characterization and relative abundance.

Marium Fiaz, Iftikhar Ahmed, Rabaila Riaz, Uzma Nawaz, Muhammad Arshad

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Article in Folia microbiologica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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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

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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

2 citing papers in PubMed.

  1. Article
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4 · The record

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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.

Marium FiazInstitute of Environmental Sciences and Engineering, School of Civil and Environmental Engineering, National University of Sciences and Technology (NUST), Islamabad, Pakistan.
Iftikhar AhmedMicrobial Genetic Resources Program, Bio-Resources Conservation Institute (BCI), National Agriculture Research Center (NARC), Islamabad, Pakistan.ORCID https://orcid.org/0000-0003-0969-7927
Rabaila RiazMicrobial Genetic Resources Program, Bio-Resources Conservation Institute (BCI), National Agriculture Research Center (NARC), Islamabad, Pakistan.
Uzma NawazDepartment of Statistics, Government Graduate College, Sahiwal, Pakistan.
Muhammad ArshadInstitute of Environmental Sciences and Engineering, School of Civil and Environmental Engineering, National University of Sciences and Technology (NUST), Islamabad, Pakistan. marshad@iese.nust.edu.pk.ORCID https://orcid.org/0000-0002-2343-822X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacteria from wastewater discharged to the sewerage near three hospitals of Islamabad, Rawalpindi, and Faisalabad were examined for resistance to the most commonly prescribed antibiotics in Pakistan. From the selected sites, a total of 109 isolates from 40 different species were identified based on 16S rRNA gene sequence and phylogeny. The isolates were tested for their resistance to ciprofloxacin, levofloxacin, ofloxacin, amoxicillin, and ampicillin. The results indicated that the isolates were resistant with the highest percentage to ampicillin and the lowest percentage to ciprofloxacin. Among the resistant isolates, 91.7% were found resistant to ampicillin, 83.5% to amoxicillin, 67.0% to ofloxacin, whereas only 27.5% to ciprofloxacin and 21.1% to levofloxacin. Among three sampled locations, the most of resistance was observed in Escherichia and Acinetobacter species. More than 30% isolated microorganisms were found resistant to more than three antibiotics. These findings concluded the presence of predominant microbial population resistant to antibiotics in wastewater channels near hospitals and its surroundings, which requires further investigation regarding their existence and spread in other environmental media having potential community health implications.

Indexed as

Anti-Bacterial AgentsWastewaterBacteriaLevofloxacinMicrobial Sensitivity TestsPrevalenceRNA, Ribosomal, 16SAnti-Bacterial AgentsLevofloxacinRNA, Ribosomal, 16SWastewater

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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.