Evidence map›Paper›PMID 42057808›Full record

ReviewOpen forum infectious diseases2026

Methicillin-Resistant

Thomas Kalinoski, Michael Kalinoski, Susan Kline, Ann Brearley, Anmol Nigam, James Harmon

Abstract readReview
In one paragraph

Review in Open forum infectious diseases, 2026. 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

6 authors.

Thomas KalinoskiDepartment of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0008-4244-6402
Michael KalinoskiDepartment of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Susan KlineDepartment of Medicine, Division of Infectious Disease and International Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Ann BrearleyDepartment of Biostatistics and Health Data Science, University of Minnesota School of Public Health, and Biostatistical Design and Analysis Center, University of Minnesota Clinical and Translational Science Institute, Minneapolis, Minnesota, USA.
Anmol NigamDepartment of Surgery, University of Minnesota Medical School, Minneapolis, Minnesota, USA.ORCID https://orcid.org/0009-0004-8182-1333
James HarmonDepartment of Surgery, University of Minnesota Medical School, Minneapolis, Minnesota, USA.ORCID https://orcid.org/0000-0003-4914-6062

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UM1TR004405 · NCATS · UNIVERSITY OF MINNESOTA · PI Bruce R Blazar, Damien A Fair · 2023 to 2026
$30.8M
NCATS NIH HHS UM1 TR004405
6 · The paper itself

Abstract

Background: Methicillin-resistant Method: Electronic databases were systematically searched. Selected studies were combined and data extracted and analyzed to calculate diagnostic performance characteristics. Results: Twenty-five studies were included. The overall positive predictive value was 70% and negative predictive value 87%. The positive and negative predictive values were 77% and 87% for a mixed composite of SSTIs, 71% and 91% for purulent infections, 63% and 87% for diabetic foot infections, and 48% and 79% for surgical site infections, respectively. Conclusions: Nasal screening as a predictor for MRSA SSTIs has a high negative predictive value in areas where MRSA prevalence is low.

Indexed as

diabetic foot infectionmethicillin-resistant Staphylococcus aureusnasal swabskin and soft tissue infectionssurgical site infection

Identifiers

PMID42057808
PMCPMC13123859

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.