ArticleJournal of clinical microbiology2024
Multicenter evaluation of BioCode GPP for syndromic molecular detection of gastrointestinal pathogens from stool specimens.
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 5 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 6 citations in OpenAlex.
- Systematic review of point-of-need molecular diagnostics for rotavirus and enteric adenoviruses F40/F41.BMC infectious diseases · 2026Pooled it
- Diagnostic Accuracy of Multiplex NAAT/PCR and Culture AgainstPathogens (Basel, Switzerland) · 2025Pooled it
- Multiplex Polymerase Chain Reaction Panels for Gastrointestinal Infections: Current Evidence, Regulatory Hurdles, and the Way Forward.Open forum infectious diseases · 2025Article
- Emerging Diagnostics inInternational journal of molecular sciences · 2024Review
- Prevalence of Enteric Pathogens and Antibiotic Resistance: Results of a Six-Year Active Surveillance Study on Patients Admitted to a Teaching Hospital.Antibiotics (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute gastroenteritis (AGE) is a leading cause of morbidity and mortality worldwide across all age groups that disproportionally affects young children in low- and middle-income countries and immunocompromised patients in high-income countries. Regional outbreaks of AGE are typically detected by traditional microbiological detection methods that target limited organisms and are associated with low sensitivity and lengthy time-to-results. Combined, these may result in repeat testing, imprecise or delayed treatment, and delayed recognition of outbreaks. We conducted a multi-site prospective study comparing the BioCode Gastrointestinal Pathogen Panel (BioCode GPP) for the detection of 17 common bacterial, viral, and protozoan causes of gastroenteritis with reference methods, including stool culture, enzyme immunoassays, pathogen-specific PCR assays, and sequencing. One thousand five hundred fifty-eight residual, de-identified stool samples (unpreserved stool and stool in Cary-Blair transport medium) were enrolled and tested for 11 bacterial, 3 viral, and 3 protozoan pathogens. BioCode GPP and reference methods were positive for 392 (25.2%) and 283 (18.2%) samples, respectively ( IMPORTANCE: This study highlights performance of a novel technology for timely and accurate detection and differentiation of 17 common bacterial, viral, and protozoan causes of gastroenteritis. Utilizing molecular tests such as the BioCode Gastrointestinal Pathogen Panel may improve the detection of gastrointestinal pathogens and provide actionable results, particularly for patient populations at most risk.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.