Evidence map›Paper›PMID 24364823›Full record

ArticleBMC microbiology2013

A novel, multiplex, real-time PCR-based approach for the detection of the commonly occurring pathogenic fungi and bacteria.

Ádám Horváth, Zoltán Pető, Edit Urbán, Csaba Vágvölgyi, Ferenc Somogyvári

Abstract readEvaluation Study
In one paragraph

Article in BMC microbiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

5 authors.

Ádám HorváthDepartment of Medical Microbiology and Immunobiology, Faculty of Medicine, University of Szeged, Dóm tér 10, Szeged H-6720, Hungary. horvath.adam.1@med.u-szeged.hu.
Zoltán Pető
Edit Urbán
Csaba Vágvölgyi
Ferenc Somogyvári

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPolymerase chain reaction (PCR)-based techniques are widely used to identify fungal and bacterial infections. There have been numerous reports of different, new, real-time PCR-based pathogen identification methods although the clinical practicability of such techniques is not yet fully clarified.The present study focuses on a novel, multiplex, real-time PCR-based pathogen identification system developed for rapid differentiation of the commonly occurring bacterial and fungal causative pathogens of bloodstream infections.

resultsA multiplex, real-time PCR approach is introduced for the detection and differentiation of fungi, Gram-positive (G+) and Gram-negative (G-) bacteria. The Gram classification is performed with the specific fluorescence resonance energy transfer (FRET) probes recommended for LightCycler capillary real-time PCR. The novelty of our system is the use of a non-specific SYBR Green dye instead of labelled anchor probes or primers, to excite the acceptor dyes on the FRET probes. In conjunction with this, the use of an intercalating dye allows the detection of fungal amplicons.With the novel pathogen detection system, fungi, G + and G- bacteria in the same reaction tube can be differentiated within an hour after the DNA preparation via the melting temperatures of the amplicons and probes in the same tube.

conclusionsThis modified FRET technique is specific and more rapid than the gold-standard culture-based methods. The fact that fungi, G + and G- bacteria were successfully identified in the same tube within an hour after the DNA preparation permits rapid and early evidence-based management of bloodstream infections in clinical practice.

Indexed as

BacteriaBacterial InfectionsFluorescence Resonance Energy TransferFungiHumansMicrobiological TechniquesMolecular Diagnostic TechniquesMultiplex Polymerase Chain ReactionMycosesReal-Time Polymerase Chain ReactionSensitivity and SpecificitySepsisTime FactorsTransition Temperature

Identifiers

PMID24364823
PMCPMC3879189

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Registered trials

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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.