Evidence map›Paper›PMID 33880565›Full record

ReviewThe Journal of infectious diseases2021

Signal Versus Noise: How to Analyze the Microbiome and Make Progress on Antimicrobial Resistance.

Jonathan L Golob, Krishna Rao

Abstract readReview
In one paragraph

Review in The Journal of infectious diseases, 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Jonathan L GolobDepartment of Internal Medicine, Division of Infectious Diseases, University of Michigan, Ann Arbor, Michigan, USA.
Krishna RaoDepartment of Internal Medicine, Division of Infectious Diseases, University of Michigan, Ann Arbor, Michigan, USA.

Funding

Systems biology of Clostridium difficile infectionU01AI124255 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SCHLOSS, PATRICK DAVID, YOUNG, VINCENT B · 2016 to 2020
$9.8M
Data-Driven Interventions for Reducing C. difficile IncidenceR01HS027431 · AHRQ · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI RAO, KRISHNA, WIENS, JENNA · 2020 to 2024
$2.4M
AHRQ HHS R01 HS027431NIAID NIH HHS U01 AI124255
6 · The paper itself

Abstract

Antimicrobial resistance has become a worldwide medical challenge [1], so impactful that vancomycin-resistant Enterococcus (VRE) and methicillin-resistant Staphylococcus aureus (MRSA) have entered the common vernacular. We have attempted to reduce the selective pressure through antimicrobial stewardship, curtail the spread by identifying and isolating carriers and individuals with symptomatic infection, and treat antibiotic-resistant organisms (AROs) by developing novel antimicrobials. Despite these extraordinary measures, the challenge of AROs continues to grow. The gut microbiome, the ecosystem of microbes (ie, the microbiota) and metabolites present upon and within all humans, is an emerging target for both the risk for colonization and defense against infection with AROs. Here, informed from experiences and successes with understanding the role of the microbiome in mediating risk of Clostridioides difficile infection (CDI), we (1) review our understanding of the risk from ARO acquisition; (2) review our current understanding of the gut microbiome's ability to resist colonization with AROs; (3) describe how experimental model systems can test these initial, global insights to arrive at more granular, mechanistic ones; and (4) suggest a path forward to make further progress in the field.

Indexed as

AnimalsAnti-Bacterial AgentsClostridioides difficileClostridium InfectionsDisease Models, AnimalDrug Resistance, MicrobialGastrointestinal MicrobiomeHigh-Throughput Nucleotide SequencingHost-Pathogen InteractionsHumansAnti-Bacterial Agentsantimicrobial resistancefecal microbiota transplantationmetagenomicsmicrobial ecologymicrobiomenext-generation sequencing

Identifiers

PMID33880565
PMCPMC8206798

What OpenQuestion holds

Textmetadata
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.