ReviewAntibiotics (Basel, Switzerland)2024
Rapid Molecular Diagnostics of Pneumonia Caused by Gram-Negative Bacteria: A Clinician's Review.
Review in Antibiotics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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
7 citing papers in PubMed.
- DecipheringMicroorganisms · 2026Review
- Protocolized antimicrobial stewardship following filmarray pneumonia plus panel testing in mechanically ventilated patients with severe lower respiratory tract infection.Scientific reports · 2026Article
- How to identify respiratory pathogens in primary health care - a review on the benefits, prospects and pitfalls in using point of care tests.Infection · 2025Review
- A Novel PCR Panel for Bacterial Detection in Lower Respiratory Tract Infections: A Comparative Study with Culture Results.Pathogens (Basel, Switzerland) · 2025Article
- Development and diagnostic performance of a sensitive multiplex pneumonia pathogen identification assay for emergency department patients with pneumonia.Microbiology spectrum · 2025Article
- Beyond Culture: Real-Time PCR Performance in Detecting Causative Pathogens and Key Antibiotic Resistance Genes in Hospital-Acquired Pneumonia.Antibiotics (Basel, Switzerland) · 2025Article
- Characteristics and trends of antibiotic resistance in several gram-negative bacteria responsible for pneumonia in intensive care patients in Northern Vietnam, 2022-2024.IJID regions · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With approximately half a billion events per year, lower respiratory tract infections (LRTIs) represent a major challenge for the global public health. Among LRTI cases, those caused by Gram-negative bacteria (GNB) are associated with a poorer prognostic. Standard-of-care etiologic diagnostics is lengthy and difficult to establish, with more than half of cases remaining microbiologically undocumented. Recently, syndromic molecular diagnostic panels became available, enabling simultaneous detection of tens of pathogen-related and antimicrobial-resistance genetic markers within a few hours. In this narrative review, we summarize the available data on the performance of molecular diagnostics in GNB pneumonia, highlighting the main strengths and limitations of these assays, as well as the main factors influencing their clinical utility. We searched MEDLINE and Web of Science databases for relevant English-language articles. Molecular assays have higher analytical sensitivity than cultural methods, and show good agreement with standard-of-care diagnostics regarding detection of respiratory pathogens, including GNB, and identification of frequent patterns of resistance to antibiotics. Clinical trials reported encouraging results on the usefulness of molecular assays in antibiotic stewardship. By providing early information on the presence of pathogens and their probable resistance phenotypes, these assays assist in the choice of targeted therapy, in shortening the time from sample collection to appropriate antimicrobial treatment, and in reducing unnecessary antibiotic use.
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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.