Evidence map›Paper›PMID 26345636›Full record

ArticleDrug design, development and therapy2015

High-throughput sequencing of 16S rDNA amplicons characterizes bacterial composition in bronchoalveolar lavage fluid in patients with ventilator-associated pneumonia.

Xiao-Jun Yang, Yan-Bo Wang, Zhi-Wei Zhou, Guo-Wei Wang, Xiao-Hong Wang, Qing-Fu Liu, Shu-Feng Zhou, Zhen-Hai Wang

Open access · goldAbstract read
In one paragraph

Article in Drug design, development and therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Extensive microbiological respiratory tract specimen characterization in critically ill COVID-19 patients.APMIS : acta pathologica, microbiologica, et immunologica Scandinavica · 2021
    Observational
  6. 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

8 authors at 1 institution in 1 country.

Xiao-Jun YangDepartment of Intensive Care Unit, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Yan-Bo WangNeurology Center, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China ; Key Laboratory of Brain Diseases of Ningxia, Yinchuan, Ningxia, People's Republic of China.
Zhi-Wei ZhouDepartment of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA.
Guo-Wei WangNeurology Center, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Xiao-Hong WangDepartment of Intensive Care Unit, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Qing-Fu LiuDepartment of Intensive Care Unit, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Shu-Feng ZhouDepartment of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA.
Zhen-Hai WangNeurology Center, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China ; Key Laboratory of Brain Diseases of Ningxia, Yinchuan, Ningxia, People's Republic of China.
University of South Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ventilator-associated pneumonia (VAP) is a life-threatening disease that is associated with high rates of morbidity and likely mortality, placing a heavy burden on an individual and society. Currently available diagnostic and therapeutic approaches for VAP treatment are limited, and the prognosis of VAP is poor. The present study aimed to reveal and discriminate the identification of the full spectrum of the pathogens in patients with VAP using high-throughput sequencing approach and analyze the species richness and complexity via alpha and beta diversity analysis. The bronchoalveolar lavage fluid samples were collected from 27 patients with VAP in intensive care unit. The polymerase chain reaction products of the hypervariable regions of 16S rDNA gene in these 27 samples of VAP were sequenced using the 454 GS FLX system. A total of 103,856 pyrosequencing reads and 638 operational taxonomic units were obtained from these 27 samples. There were four dominant phyla, including Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes. There were 90 different genera, of which 12 genera occurred in over ten different samples. The top five dominant genera were Streptococcus, Acinetobacter, Limnohabitans, Neisseria, and Corynebacterium, and the most widely distributed genera were Streptococcus, Limnohabitans, and Acinetobacter in these 27 samples. Of note, the mixed profile of causative pathogens was observed. Taken together, the results show that the high-throughput sequencing approach facilitates the characterization of the pathogens in bronchoalveolar lavage fluid samples and the determination of the profile for bacteria in the bronchoalveolar lavage fluid samples of the patients with VAP. This study can provide useful information of pathogens in VAP and assist clinicians to make rational and effective therapeutic decisions.

Indexed as

High-Throughput Nucleotide SequencingAdultAgedAged, 80 and overAnti-Bacterial AgentsBronchoalveolar Lavage FluidComputational BiologyDNA, BacterialDrug Resistance, BacterialFemaleGenotypeHumansMaleMiddle AgedPhylogenyPneumonia, Ventilator-AssociatedAnti-Bacterial AgentsDNA, BacterialRNA, Ribosomal, 16SbioinformaticsDNA sequencingdrug resistanceOTUPCR

Identifiers

PMID26345636
PMCPMC4554422
OpenAlexW1555265423

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.