Evidence map›Paper›PMID 41365864›Full record

Trial reportNature communications2025

Multiplexed detection of febrile infections using CARMEN.

M Kamariza, K McMahon, L Kim, N L Welch, L Stenson, L T Allan-Blitz, G Sanders, P Eromon, A Muhammad, A E Sijuwola and 11 more

Abstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. 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

21 authors.

M KamarizaBroad Institute of MIT and Harvard, Cambridge, MA, USA. mkamariz@broadinstitute.org.
K McMahonBroad Institute of MIT and Harvard, Cambridge, MA, USA.
L KimBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0001-9844-247X
N L WelchBroad Institute of MIT and Harvard, Cambridge, MA, USA.
L StensonBroad Institute of MIT and Harvard, Cambridge, MA, USA.
L T Allan-BlitzBroad Institute of MIT and Harvard, Cambridge, MA, USA.
G SandersDivision of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
P EromonInstitute of Genomics and Global Health (IGH), Redeemer's University, Ede, Osun State, Nigeria.
A MuhammadInstitute of Genomics and Global Health (IGH), Redeemer's University, Ede, Osun State, Nigeria.ORCID 0000-0002-7679-5052
A E SijuwolaInstitute of Genomics and Global Health (IGH), Redeemer's University, Ede, Osun State, Nigeria.ORCID 0000-0002-4539-9727
O O Ope-EweInstitute of Genomics and Global Health (IGH), Redeemer's University, Ede, Osun State, Nigeria.
A O AyinlaInstitute of Genomics and Global Health (IGH), Redeemer's University, Ede, Osun State, Nigeria.
C l'AnsonBroad Institute of MIT and Harvard, Cambridge, MA, USA.
I BaudiBroad Institute of MIT and Harvard, Cambridge, MA, USA.
M F PayeBroad Institute of MIT and Harvard, Cambridge, MA, USA.
C WilkasonBroad Institute of MIT and Harvard, Cambridge, MA, USA.
J LemieuxBroad Institute of MIT and Harvard, Cambridge, MA, USA.
A OzonoffBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-4233-5899
E StachlerBroad Institute of MIT and Harvard, Cambridge, MA, USA.
C T HappiInstitute of Genomics and Global Health (IGH), Redeemer's University, Ede, Osun State, Nigeria.ORCID 0000-0002-3056-6705
P C SabetiBroad Institute of MIT and Harvard, Cambridge, MA, USA. pardis@broadinstitute.org.ORCID 0000-0002-9843-1890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detection and diagnosis of bloodborne pathogens are critical for patients and for preventing outbreaks, yet challenging due to these diseases' nonspecific initial symptoms. We previously advanced CRISPR-based Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN) technology for simultaneous detection of pathogens on numerous samples. Here, we develop three CARMEN panels that target viral hemorrhagic fevers, mosquito-borne viruses, and sexually transmitted infections, collectively identifying 23 pathogens. We use deep learning to design CARMEN assays with enhanced sensitivity and specificity, validating them and evaluating their performance on synthetic targets, spiked healthy normal serum samples, and patient samples for Neisseria gonorrhoeae in the United States and for Lassa and mpox virus in Nigeria. Our results show multiplexed CARMEN assays match or outperform individual assay RT-qPCR in sensitivity, with matched specificity. These findings underscore CARMEN's potential as a highly effective tool for accurate pathogen detection for clinical diagnosis and public health surveillance.

Indexed as

FeverMultiplex Polymerase Chain ReactionGonorrheaHumansNeisseria gonorrhoeaeNigeriaSensitivity and SpecificitySexually Transmitted Diseases

Identifiers

PMID41365864
PMCPMC12764852

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.