ArticleJournal of clinical microbiology2024
Evaluation of an expanded antibiotic resistance gene panel on prediction of antimicrobial susceptibility results for Gram-negative bacteria in blood cultures.
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 1 paper.
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
1 citing paper in PubMed.
- Impact of a Rapid Change in Beta-lactam Resistance Epidemiology on the Management of Patients With Bloodstream Infections.Open forum infectious diseases · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The QIAstat-Dx BCID Panels (RUO) ("QIAstat," QIAGEN, Hilden, Germany) for identification of 13 Gram-negative bacteria and 18 antimicrobial resistance (AMR) gene groups was evaluated. The study was conducted in two phases; in phase 1, analytical performance was evaluated against 154 challenge isolates against whole genome sequencing data. In this phase, sensitivity and specificity of organism identification calls were 153/154 (99.3%) and 1,748/1,749 (99.8%), respectively. For AMR genes, sensitivity was 434/435 (99.8%) and specificity was 2,334/2,337 (99.9%). One false-negative IMPORTANCE: Prediction of Gram-negative bacteria resistance through detection of resistance genes is complex. This study evaluated a novel, direct-from-blood or bacterial isolate multiplexed PCR for the detection of 17 resistance genes, and evaluated the prediction of antimicrobial susceptibility.
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