Evidence map›Paper›PMID 34204497›Full record

ArticleAntibiotics (Basel, Switzerland)2021

Evolution of the Gram-Negative Antibiotic Resistance Spiral over Time: A Time-Series Analysis.

Hajnalka Tóth, Gyula Buchholcz, Adina Fésüs, Bence Balázs, József Bálint Nagy, László Majoros, Krisztina Szarka, Gábor Kardos

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Antibiotics (Basel, Switzerland), 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
0.3field-weighted citation impact, top 41% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. The Effect of Decreased Antipseudomonal Drug Consumption onAntibiotics (Basel, Switzerland) · 2023
    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

8 authors at 2 institutions in 2 countries.

Hajnalka TóthDepartment of Medical Microbiology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
Gyula BuchholczCentral Clinical Pharmacy, Clinical Center, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
Adina FésüsDepartment of Medical Microbiology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
Bence BalázsDepartment of Medical Microbiology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
József Bálint NagyDepartment of Medical Microbiology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
László MajorosDepartment of Medical Microbiology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
Krisztina SzarkaDepartment of Medical Microbiology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
Gábor KardosDepartment of Medical Microbiology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
University of Debrecen · HUOstalb-Klinikum Aalen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We followed up the interplay between antibiotic use and resistance over time in a tertiary-care hospital in Hungary. Dynamic relationships between monthly time-series of antibiotic consumption data (defined daily doses per 100 bed-days) and of incidence densities of Gram-negative bacteria (

Indexed as

Acinetobacter baumanniiantibiotic consumptionantibiotic resistancecarbapenem resistancecephalosporin resistancecolistinEscherichia coliKlebsiella spp.Pseudomonas aeruginosavector autoregressive models

Identifiers

PMID34204497
PMCPMC8234935
OpenAlexW3165965912

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.