Evidence map›Paper›PMID 38654117›Full record

ArticleCommunications medicine2024

Rapid diagnosis of bloodstream infections using a culture-free phenotypic platform.

Xuyang Shi, Shivani Sharma, Richard A Chmielewski, Mario J Markovic, J Scott VanEpps, Siu-Tung Yau

Open access · goldAbstract read
In one paragraph

Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Article
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  4. UnmaskingPathogens (Basel, Switzerland) · 2026
    Article
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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

6 authors at 3 institutions in 1 country.

Xuyang ShiDepartment of Electrical and Computer Engineering, Cleveland State University, Cleveland, OH, USA.ORCID http://orcid.org/0000-0002-9473-8692
Shivani SharmaRapidect Inc., Solon, OH, USA.
Richard A ChmielewskiSaint Vincent Charity Medical Center, Cleveland, OH, USA.
Mario J MarkovicDepartment of Laboratory Medicine, Saint Vincent Charity Medical Center, Cleveland, OH, USA.
J Scott VanEppsDepartment of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA. jvane@med.umich.edu.ORCID http://orcid.org/0000-0002-0805-0913
Siu-Tung YauDepartment of Electrical and Computer Engineering, Cleveland State University, Cleveland, OH, USA. s.yau@csuohio.edu.ORCID http://orcid.org/0000-0002-6566-4305
Cleveland State University · USSt. Vincent Charity Hospital · USUniversity of Michigan · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBloodstream infections (BSIs) are a life-threatening acute medical condition and current diagnostics for BSIs suffer from long turnaround time (TAT). Here we show the validation of a rapid detection-analysis platform (RDAP) for the diagnosis of BSIs performed on clinical blood samples

methodsThe validation was performed on a cohort of 59 clinical blood samples, including positive culture samples, which indicated confirmed bloodstream infections, and negative culture samples. The bacteria in the positive culture samples included Gram-positive and Gram-negative pathogenic species. RDAP is based on an electrochemical sandwich immunoassay with voltage-controlled signal amplification, which provides an ultra-low limit of detection (4 CFU/mL), allowing the platform to detect and identify bacteria without requiring culture and perform phenotypic antibiotic susceptibility testing (AST) with only 1-2 h of antibiotic exposure. The preliminary diagnostic performance of RDAP was compared with that of standard commercial diagnostic technologies.

resultsUsing a typical clinical microbiology laboratory diagnostic workflow that involved sample culture, agar plating, bacteria identification using matrix-assisted laser desorption ionization time-of-flight (MALDI TOF) mass spectrometry, and AST using MicroScan as a clinical diagnostic reference, RDAP showed diagnostic accuracy of 93.3% and 95.4% for detection-identification and AST, respectively. However, RDAP provided results at least 15 h faster.

conclusionsThis study shows the preliminary feasibility of using RDAP to rapidly diagnose BSIs, including AST. Limitations and potential mitigation strategies for clinical translation of the present RDAP prototype are discussed. The results of this clinical feasibility study indicate an approach to provide near real-time diagnostic information for clinicians to significantly enhance the treatment outcome of BSIs.

Identifiers

PMID38654117
PMCPMC11039749
OpenAlexW4395030584

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LicenceCC BY
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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.