Evidence map›Paper›PMID 39116083›Full record

ArticlePloS one2024

Importance of underlying mechanisms for interpreting relative risk of Clostridioides difficile infection among antibiotic-exposed patients in healthcare facilities.

Christopher Mitchell, Lindsay T Keegan, Thuy T T Le, Karim Khader, Alexander Beams, Matthew H Samore, Damon J A Toth

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Christopher MitchellDepartment of Mathematics, Tarleton State University, Stephenville, Texas, United States of America.ORCID 0000-0001-8792-9370
Lindsay T KeeganDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States of America.
Thuy T T LeDepartment of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.
Karim KhaderDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States of America.
Alexander BeamsDepartment of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada.
Matthew H SamoreDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States of America.
Damon J A TothDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States of America.

Funding

CTSA UM1 Program at University of UtahUM1TR004409 · NCATS · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI RACHEL HESS, Jennifer Juhl Majersik · 2023 to 2026
$21.9M
A combined epidemiologic and genomic approach to identify and control transmission events of hospital associated infectionsK01AI159519 · NIAID · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI KEEGAN, LINDSAY T. · 2021 to 2025
$678k
NCATS NIH HHS UM1 TR004409NCEZID CDC HHS U01 CK000538NCEZID CDC HHS U01 CK000585NIAID NIH HHS K01 AI159519
6 · The paper itself

Abstract

Clostridioides difficile infection (CDI) is a significant public health threat, associated with antibiotic-induced disruption of the normally protective gastrointestinal microbiota. CDI is thought to occur in two stages: acquisition of asymptomatic colonization from ingesting C. difficile bacteria followed by progression to symptomatic CDI caused by toxins produced during C. difficile overgrowth. The degree to which disruptive antibiotic exposure increases susceptibility at each stage is uncertain, which might contribute to divergent published projections of the impact of hospital antibiotic stewardship interventions on CDI. Here, we model C. difficile transmission and CDI among hospital inpatients, including exposure to high-CDI-risk antibiotics and their effects on each stage of CDI epidemiology. We derive the mathematical relationship, using a deterministic model, between those parameters and observed equilibrium levels of colonization, CDI, and risk ratio of CDI among certain antibiotic-exposed patients relative to patients with no recent antibiotic exposure. We then quantify the sensitivity of projected antibiotic stewardship intervention impacts to alternate assumptions. We find that two key parameters, the antibiotic effects on susceptibility to colonization and to CDI progression, are not identifiable given the data frequently available. Furthermore, the effects of antibiotic stewardship interventions are sensitive to their assumed values. Thus, discrepancies between different projections of antibiotic stewardship interventions may be largely due to model assumptions. Data supporting improved quantification of mechanistic antibiotic effects on CDI epidemiology are needed to understand stewardship effects better.

Indexed as

Anti-Bacterial AgentsAntimicrobial StewardshipClostridioides difficileClostridium InfectionsCross InfectionGastrointestinal MicrobiomeDisease SusceptibilityEpidemiological ModelsHospitalsHumansProtective FactorsAnti-Bacterial Agents

Identifiers

PMID39116083
PMCPMC11309424

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Registered trials

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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.