Evidence map›Paper›PMID 24031310›Full record

ArticleBrazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]2009

Principles and applications of polymerase chain reaction in medical diagnostic fields: a review.

Marcela Agne Alves Valones, Rafael Lima Guimarães, Lucas André Cavalcanti Brandão, Paulo Roberto Eleutério de Souza, Alessandra de Albuquerque Tavares Carvalho, Sergio Crovela

Abstract read
In one paragraph

Article in Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology], 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
–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

48 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Article
  9. Veterinary application of LAMP: a simple and visual detection tool for feline sporotrichosis.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2025
    Article
  10. Article
  11. Review
  12. Article
  13. Machine learning assisted identification of antibiotic-resistantMicrochemical journal : devoted to the application of microtechniques in all branches of science · 2024
    Article
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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

6 authors.

Marcela Agne Alves ValonesUniversidade Federal de Pernambuco , Recife, PE , Brasil.
Rafael Lima Guimarães
Lucas André Cavalcanti Brandão
Paulo Roberto Eleutério de Souza
Alessandra de Albuquerque Tavares Carvalho
Sergio Crovela

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent developments in molecular methods have revolutionized the detection and characterization of microorganisms in a broad range of medical diagnostic fields, including virology, mycology, parasitology, microbiology and dentistry. Among these methods, Polymerase Chain Reaction (PCR) has generated great benefits and allowed scientific advancements. PCR is an excellent technique for the rapid detection of pathogens, including those difficult to culture. Along with conventional PCR techniques, Real-Time PCR has emerged as a technological innovation and is playing an ever-increasing role in clinical diagnostics and research laboratories. Due to its capacity to generate both qualitative and quantitative results, Real-Time PCR is considered a fast and accurate platform. The aim of the present literature review is to explore the clinical usefulness and potential of both conventional PCR and Real-Time PCR assays in diverse medical fields, addressing its main uses and advances.

Indexed as

Conventional PCRMethods of molecular detectionMolecular BiologyReal-Time PCR

Identifiers

PMID24031310
PMCPMC3768498

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.