Evidence map›Paper›PMID 35916520›Full record

ReviewJournal of clinical microbiology2022

What's New in Antibiograms? Updating CLSI M39 Guidance with Current Trends.

Patricia J Simner, Janet A Hindler, Tanaya Bhowmick, Sanchita Das, J Kristie Johnson, Brian V Lubers, Mark A Redell, John Stelling, Sharon M Erdman

Open access · greenAbstract readReview
In one paragraph

Review in Journal of clinical microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
7.4field-weighted citation impact, top 2% 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

35 citing papers in PubMed, 61 citations in OpenAlex.

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  3. Persistent Non-Journal of fungi (Basel, Switzerland) · 2026
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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

9 authors at 9 institutions in 1 country.

Patricia J SimnerDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0001-6134-151X
Janet A HindlerLos Angeles County Department of Public Health, Los Angeles, California, USA.
Tanaya BhowmickRutgers Robert Wood Johnson Medical School, Department of Medicine, New Brunswick, New Jersey, USA.
Sanchita DasDepartment of Laboratory Medicine, National Institutes of Healthgrid.94365.3d, Clinical Center, Bethesda, Maryland, USA.ORCID 0000-0002-2246-7942
J Kristie JohnsonDepartment of Pathology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Brian V LubersDepartment of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, USA.
Mark A RedellMedical Affairs, Melinta Therapeutics, Morristown, New Jersey, USA.
John StellingMicrobiology Laboratory, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Sharon M ErdmanPurdue University College of Pharmacy, West Lafayette, Indiana, USA.
Brigham and Women's Hospital · USJohns Hopkins University · USKansas State University · USLos Angeles County Department of Public Health · USMelinta Therapeutics (United States) · USNational Institutes of Health Clinical Center · USPurdue University West Lafayette · USRutgers, The State University of New Jersey · USUniversity of Maryland, Baltimore · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A vast amount of antimicrobial susceptibility test (AST) data is generated from routine testing in diagnostic laboratories for the primary purpose of guiding clinicians in antimicrobial therapy decisions for their patients. However, there is additional value for these data when they are compiled at the local, regional, national, and global levels. Cumulative AST data can be used to prepare antibiograms at the individual health care facility level. These reports can be used to gain insight into appropriate empirical therapy options prior to the availability of AST results on an individual patient's isolate. Different types of cumulative AST data reports can also be compiled at the regional, national, and global levels to estimate susceptibility rates in geographic regions, document trends in evolving microbial populations, and recognize the appearance and spread of emerging antimicrobial resistance threats. The first CLSI M39 Guideline for Analysis and Presentation of Cumulative AST Data was published in 2000. Since that time, there have been changes to AST and reporting recommendations as well as the introduction of advanced informatics technologies to analyze and present data. The 5th edition of M39 has taken into consideration these changes to assist those who analyze, present, and utilize routine antibiograms and other types of cumulative AST data reports as well as those who design information systems for the capturing and analyzing of AST data. Furthermore, antimicrobial stewardship programs (ASPs) have expanded considerably, and uses of the antibiogram by ASPs have been addressed. This minireview will remind users of the basic recommendations for analysis and presentation of antibiograms and provide new suggestions to enhance these reports.

Indexed as

Anti-Bacterial AgentsLaboratoriesHealth FacilitiesHumansMicrobial Sensitivity TestsAnti-Bacterial Agentsantibiogramantimicrobial susceptibility testcumulative antimicrobial susceptibility testing reportM39

Identifiers

PMID35916520
PMCPMC9580356
OpenAlexW4289521685

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.