Evidence map›Paper›PMID 38395408›Full record

ArticleThe Journal of molecular diagnostics : JMD2024

Universal Digital High-Resolution Melt Analysis for the Diagnosis of Bacteremia.

April Aralar, Tyler Goshia, Nanda Ramchandar, Shelley M Lawrence, Aparajita Karmakar, Ankit Sharma, Mridu Sinha, David T Pride, Peiting Kuo, Khrissa Lecrone and 8 more

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 4 institutions in 1 country.

April AralarDepartment of Bioengineering, University of California, San Diego, La Jolla, California.
Tyler GoshiaDepartment of Bioengineering, University of California, San Diego, La Jolla, California.
Nanda RamchandarDepartment of Pediatrics, Naval Medical Center San Diego, San Diego, California; Division of Infectious Diseases, Department of Pediatrics, University of California, San Diego, La Jolla, California.
Shelley M LawrenceDivision of Neonatology, Department of Pediatrics, The University of Utah, Salt Lake City, Utah.
Aparajita KarmakarMelioLabs, Inc., Santa Clara, California.
Ankit SharmaMelioLabs, Inc., Santa Clara, California.
Mridu SinhaMelioLabs, Inc., Santa Clara, California.
David T PrideDepartment of Pathology, University of California, San Diego, La Jolla, California.
Peiting KuoDepartment of Pathology, University of California, San Diego, La Jolla, California.
Khrissa LecroneDepartment of Pathology, University of California, San Diego, La Jolla, California.
Megan ChiuDepartment of Pathology, University of California, San Diego, La Jolla, California.
Karen K MestanDivision of Neonatology, Department of Pediatrics, University of California, San Diego, La Jolla, California.
Eniko SajtiDivision of Neonatology, Department of Pediatrics, University of California, San Diego, La Jolla, California.
Michelle VanderpoolDepartment of Pathology and Laboratory Medicine, Rady Children's Hospital-San Diego, San Diego, California.
Sarah LazarDivision of Neonatology, Department of Pediatrics, University of California, San Diego, La Jolla, California.
Melanie CrabtreeDivision of Neonatology, Department of Pediatrics, University of California, San Diego, La Jolla, California.
Yordanos TesfaiDivision of Neonatology, Department of Pediatrics, University of California, San Diego, La Jolla, California.
Stephanie I FraleyDepartment of Bioengineering, University of California, San Diego, La Jolla, California. Electronic address: sifraley@ucsd.edu.
University of California San Diego · USNaval Medical Center San Diego · USRady Children's Hospital-San Diego · USUniversity of Utah · US

Funding

RESEARCH IN INFECTIOUS DISEASEST32AI007036 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI NIZET, VICTOR · 1985 to 2025
$9.2M
NeoChip for specific and rapid identification of congenital CMV and neonatal HSV infections on minimal sample volumeR01HD099250 · NICHD · UNIVERSITY OF UTAH · PI LAWRENCE, SHELLEY M · 2020 to 2024
$2.9M
Digital High Resolution Melt and Machine Learning for Rapid and Specific Diagnosis in Neonatal SepsisR01AI134982 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FRALEY, STEPHANIE IRENE · 2018 to 2022
$2.3M
NIAID NIH HHS R01 AI134982NIAID NIH HHS T32 AI007036NICHD NIH HHS R01 HD099250
6 · The paper itself

Abstract

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires approximately 15 hours to detect the presence of a pathogen. We, therefore, assessed the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 17 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 88% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1-mL sample input and sample-to-answer time of 6 hours. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection.

Indexed as

BacteremiaCommunicable DiseasesSepsisBacteriaChildHumansPilot Projects

Identifiers

PMID38395408
PMCPMC11090205
OpenAlexW4391989660

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.