Evidence map›Paper›PMID 32156072›Full record

ArticleAntibiotics (Basel, Switzerland)2020

Impact of Strain Competition on Bacterial Resistance in Immunocompromised Populations.

Ashley A DeNegre, Kellen Myers, Nina H Fefferman

Open access · goldAbstract read
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 37% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Antibiotics and Environment.Antibiotics (Basel, Switzerland) · 2020
    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

3 authors at 2 institutions in 1 country.

Ashley A DeNegreDepartment of Ecology, Evolution and Natural Resources, Rutgers University, New Brunswick, NJ 08901, USA.
Kellen MyersDepartment of Ecology & Evolutionary Biology, University of Tennessee, Knoxville, TN 37996, USA.
Nina H FeffermanDepartment of Ecology, Evolution and Natural Resources, Rutgers University, New Brunswick, NJ 08901, USA.
Rutgers, The State University of New Jersey · USNational Institute for Mathematical and Biological Synthesis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the risk of emerging drug resistance that occurs with the frequent use of antimicrobial agents, targeted and prophylactic antibiotics have been considered crucial to opportunistic infection management among the HIV/AIDS-immunocompromised. As we recently demonstrated, the disrupted selective pressures that occur in AIDS-prevalent host populations increase the probability of novel emergence. This effect is concerning, given that bacterial strains unresponsive to first-line antibiotics can be particularly dangerous to hosts whose immune response is insufficient to fight infection in the absence of antibiotic support. While greater host susceptibility within a highly immunocompromised population may offer a fitness advantage to drug-resistant bacterial strains, this advantage could be mitigated by increased morbidity and mortality among the AIDS-immunocompromised. Using a Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiological model parameterized to reflect conditions in an AIDS-prevalent host population, we examine the evolutionary relationship between drug-sensitive and -resistant strains of

Indexed as

AIDS-related opportunistic infectionschemoprophylaxisemerging drug resistanceevolutionary epidemiologyglobal public healthmathematical modelsresistant opportunistic infections

Identifiers

PMID32156072
PMCPMC7148506
OpenAlexW3009595763

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.