Evidence map›Paper›PMID 39443495›Full record

ArticleScientific reports2024

Application of a metatranscriptomics technology, CSI-Dx, for the detection of pathogens associated with prosthetic joint infections.

Justin R Wright, Jeremy R Chen See, Truc T Ly, Vasily Tokarev, Jordan Pellegrino, Logan Peachey, Samantha L C Anderson, Christine Y Walls, Maxwell Hosler, Alexander J Shope and 3 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

13 authors.

Justin R WrightContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Jeremy R Chen SeeContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Truc T LyContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Vasily TokarevContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Jordan PellegrinoContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Logan PeacheyContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Samantha L C AndersonContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Christine Y WallsContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Maxwell HoslerContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Alexander J ShopeContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA.
Simmi GulatiCD Laboratories, Zimmer Biomet, Towson, MD, 21286, USA.
Krista O TolerDepartment of Diagnostics Research and Development, Zimmer Biomet, Claymont, DE, 19703, USA.
Regina LamendellaContamination Source Identification, 419 14th St., Huntingdon, PA, 16652, USA. reginalamendella@csidx.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preoperative identification of causal organism(s) is crucial for effective prosthetic joint infection treatment. Herein, we explore the clinical application of a novel metatranscriptomic (MT) workflow, CSI-Dx, to detect pathogens associated with prosthetic joint infection. MT provides insight into transcriptionally active microbes, overcoming limitations of culture-based and available molecular methods. This study included 340 human synovial fluid specimens subjected to CSI-Dx and traditional culture-based methods. Exploratory analyses were conducted to determine sensitivity and specificity of CSI-Dx for detecting clinically-relevant taxa. Our findings provide insights into the active microbial community composition of synovial fluid from arthroplasty patients and demonstrate the potential clinical utility of CSI-Dx for aiding prosthetic joint infection diagnosis. This approach offers potential for improved sensitivity and acceptable specificity compared to synovial fluid culture, enabling detection of culturable and non-culturable microorganisms. Furthermore, CSI-Dx provides valuable information on antimicrobial resistance gene expression. While further optimization is needed, integrating metatranscriptomic technologies like CSI-Dx into routine clinical practice can revolutionize prosthetic joint infection diagnosis by offering a comprehensive and active snapshot of associated pathogens.

Indexed as

Prosthesis-Related InfectionsSynovial FluidAgedBacteriaFemaleGene Expression ProfilingHumansMaleMetagenomicsMicrobiotaMiddle AgedSensitivity and SpecificityTranscriptome

Identifiers

PMID39443495
PMCPMC11500344

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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.