Evidence map›Paper›PMID 30602148›Full record

ArticleBlood purification2019

The Application Analysis of Multiplex Real-Time Polymerase Chain Reaction Assays for Detection of Pathogenic Bacterium in Peritoneal Dialysis-Associated Peritonitis.

Jing Yang, Xiang-Ming Qi, Yong-Gui Wu

Open access · hybridAbstract read
In one paragraph

Article in Blood purification, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 39% of its field
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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
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

3 authors at 2 institutions in 1 country.

Jing YangDepartment of Nephropathy, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Xiang-Ming QiDepartment of Nephropathy, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Yong-Gui WuDepartment of Nephropathy, The First Affiliated Hospital of Anhui Medical University, Hefei, China, wuyonggui@medmail.com.cn.
First Affiliated Hospital of Anhui Medical University · CNAnhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimsTo estimate the clinical value of bacterial detection in peritoneal dialysis-associated peritonitis (PDAP) by multiplex real-time polymerase chain reaction (RT-PCR). This study was undertaken to evaluate multiplex RT-PCR for identifying clinically significant bacteria in PDAP.

methodsSeventy peritoneal dialysate specimens were collected and traditional bacterial culture and universal primer RT-PCR detection of the bacterial were used.

resultsThe positive rate of traditional culture method was 65.71% (46/70) and that of universal primer RT-PCR was 81.42% (57/70). For 6 clinical commonly pathogenic bacteria, multiplex, and monoplex RT-PCR all detected 38 positive ones within the 57 specimens that were detected positive by universal primer RT-PCR. The results of the 2 methods were completely identical. Detecting bacteria by universal primer PCR and Monoplex RT-PCR needs 4-5 and 6-9 h, respectively, while multiplex RT-PCR needs less than 3 h.

conclusionOur results demonstrated that the multiplex RT-PCR can detect several kinds of bacteria simultaneously and it is also more practical and convenient than monoplex RT-PCR.

Indexed as

AdolescentAdultAgedBacteriaBacterial InfectionsFemaleHumansMaleMiddle AgedMultiplex Polymerase Chain ReactionPeritoneal DialysisPeritonitisReal-Time Polymerase Chain ReactionYoung AdultBacteria culturesPathogenic bacteriaPeritoneal dialysis-associated peritonitisReal-time polymerase chain reaction

Identifiers

PMID30602148
PMCPMC6549452
OpenAlexW2907909459

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.