Evidence map›Paper›PMID 40395945›Full record

ArticleAntimicrobial stewardship & healthcare epidemiology : ASHE2025

Impact of a multi-step testing algorithm on hospital-onset

Matthew A Moffa, Dustin R Carr, Nathan R Shively, Adriana Betancourth, Nitin Bhanot, Zaw Min, Charmaine Abalos, Arshpal Gill, Salman Bangash, Thomas L Walsh

Abstract read
In one paragraph

Article in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2025. 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
–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

1 citing paper in PubMed.

  1. The Patients' Voice inmedRxiv : the preprint server for health sciences · 2026
    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

10 authors.

Matthew A MoffaMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.ORCID https://orcid.org/0000-0002-6253-7490
Dustin R CarrDepartment of Pharmacy, Allegheny Health Network, Pittsburgh, PA, USA.ORCID https://orcid.org/0000-0001-8543-4972
Nathan R ShivelyMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.ORCID https://orcid.org/0000-0001-6163-438X
Adriana BetancourthMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.
Nitin BhanotMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.
Zaw MinMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.ORCID https://orcid.org/0000-0002-5708-954X
Charmaine AbalosMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.
Arshpal GillMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.
Salman BangashMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.
Thomas L WalshMedicine Institute and Division of Infectious Diseases, Allegheny Health Network, Pittsburgh, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate the impact of implementing a multi-step Design: Retrospective pre-intervention/post-intervention study. Setting: Two academic hospitals in Pittsburgh, Pennsylvania. Methods: In the pre-intervention period, a standalone polymerase chain reaction (PCR) assay was used for diagnosing CDI. In the post-intervention period, positive PCR assays were reflexed to a glutamate dehydrogenase antigen test and an enzyme immunoassay for toxin A/B. Results: The implementation of a multi-step testing algorithm resulted in a significant reduction in HO-CDI cases per 10,000 patient days from 5.92 to 2.36 ( Conclusions: The multi-step testing algorithm significantly reduced HO-CDI rates without compromising clinical outcomes. The study supports the use of a multi-step CDI testing algorithm to assist healthcare providers with CDI management decisions and potentially to reduce financial penalties burdened on healthcare systems.

Identifiers

PMID40395945
PMCPMC12089735

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.