Evidence map›Paper›PMID 38054730›Full record

ArticleJournal of clinical microbiology2024

Comparison of three rapid diagnostic tests for bloodstream infections using Benefit-risk Evaluation Framework (BED-FRAME).

Richard D Smith, Min Zhan, Shanshan Zhang, Surbhi Leekha, Anthony Harris, Yohei Doi, Scott Evans, J Kristie Johnson, Robert K Ernst

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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.

Richard D SmithDepartment of Pathology, University of Maryland School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0002-1908-3083
Min ZhanDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Shanshan ZhangBiostatistics Center and the Department of Biostatistics and Bioinformatics, The George Washington University, Washington, D.C., USA.
Surbhi LeekhaDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Anthony HarrisDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Yohei DoiDivision of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.ORCID 0000-0002-9620-2525
Scott EvansBiostatistics Center and the Department of Biostatistics and Bioinformatics, The George Washington University, Washington, D.C., USA.
J Kristie JohnsonDepartment of Pathology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Robert K ErnstDepartment of Microbial Pathogenesis, University of Maryland School of Dentistry, Baltimore, Maryland, USA.ORCID 0000-0001-5016-8694

Funding

Colistin-resistant Acinetobacter baumanniiR01AI104895 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DOI, YOHEI, ERNST, ROBERT K · 2014 to 2024
$4.2M
MS Diagnostic Bacterial Identification LibraryR01AI147314 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI ERNST, ROBERT K, GOODLETT, DAVID ROBINSON · 2020 to 2024
$2.3M
NIAID NIH HHS R01 AI104895NIAID NIH HHS R01 AI147314
6 · The paper itself

Abstract

Rapid diagnostic tests (RDTs) for bloodstream infections have the potential to reduce time to appropriate antimicrobial therapy and improve patient outcomes. Previously, an in-house, lipid-based, matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) method, Fast Lipid Analysis Technique (FLAT MS), has shown promise as a rapid pathogen identification method. In this study, FLAT MS for direct from blood culture identification was evaluated and compared to FDA-cleared identification methods using the Benefit-risk Evaluation Framework (BED-FRAME) analysis. FLAT MS was evaluated and compared to Bruker Sepsityper and bioMérieux BioFire FilmArray BCID2 using results from a previous study. For this study, 301 positive blood cultures were collected from the University of Maryland Medical Center. The RDTs were compared by their sensitivities, time-to-results, hands-on time, and BED-FRAME analysis. The overall sensitivity of all platforms compared to culture results from monomicrobial-positive blood cultures was 88.3%. However, the three RDTs differed in their accuracy for identifying Gram-positive bacteria, Gram-negative bacteria, and yeast. Time-to-results for FLAT MS, Sepsityper, and BioFire BCID2 were all approximately one hour. Hands-on times for FLAT MS, Sepsityper, and BioFire BCID2 were 10 (±1.3), 40 (±2.8), and 5 (±0.25) minutes, respectively. BED-FRAME demonstrated that each RDT had utility at different pathogen prevalence and relative importance. BED-FRAME is a useful tool that can used to determine which RDT is best for a healthcare center.

Indexed as

BacteremiaSepsisBacteriological TechniquesBlood CultureHumansLipidsRapid Diagnostic TestsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationLipidsBED-FRAMEblood culturebloodstream infectionsrapid diagnostic testing

Identifiers

PMID38054730
PMCPMC10793330

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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.