Evidence map›Paper›PMID 38534659›Full record

ArticleAntibiotics (Basel, Switzerland)2024

Predictive Modeling of Phenotypic Antimicrobial Susceptibility of Selected Beta-Lactam Antimicrobials from Beta-Lactamase Resistance Genes.

Md Kaisar Rahman, Ryan B Williams, Samuel Ajulo, Gizem Levent, Guy H Loneragan, Babafela Awosile

Open access · goldAbstract read
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 61% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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.

Md Kaisar RahmanSchool of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.ORCID 0000-0001-7761-9846
Ryan B WilliamsSchool of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Samuel AjuloSchool of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.ORCID 0009-0002-3152-6518
Gizem LeventSchool of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.ORCID 0000-0001-9207-9999
Guy H LoneraganSchool of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Babafela AwosileSchool of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.ORCID 0000-0002-4779-6515
Texas Tech University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outcome of bacterial infection management relies on prompt diagnosis and effective treatment, but conventional antimicrobial susceptibility testing can be slow and labor-intensive. Therefore, this study aims to predict phenotypic antimicrobial susceptibility of selected beta-lactam antimicrobials in the bacteria of the family Enterobacteriaceae from different beta-lactamase resistance genotypes. Using human datasets extracted from the Antimicrobial Testing Leadership and Surveillance (ATLAS) program conducted by Pfizer and retail meat datasets from the National Antimicrobial Resistance Monitoring System for Enteric Bacteria (NARMS), we used a robust or weighted least square multivariable linear regression modeling framework to explore the relationship between antimicrobial susceptibility data of beta-lactam antimicrobials and different types of beta-lactamase resistance genes. In humans, in the presence of the

Indexed as

beta-lactamase geneEnterobacteriaceaeMICpredictive modeling

Identifiers

PMID38534659
PMCPMC10967287
OpenAlexW4392234083

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.