Evidence map›Paper›PMID 32850904›Full record

ArticleFrontiers in medicine2020

Vital Members in the More Dysbiotic Oropharyngeal Microbiotas in H7N9-Infected Patients.

Hua Zha, Haifeng Lu, Jieyun Wu, Kevin Chang, Qiangqiang Wang, Hua Zhang, Jinyou Li, Qixia Luo, Yanmeng Lu, Lanjuan Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 37% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

10 authors at 4 institutions in 2 countries.

Hua ZhaState Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Haifeng LuState Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Jieyun WuSchool of Biological Sciences, The University of Auckland, Auckland, New Zealand.
Kevin ChangDepartment of Statistics, The University of Auckland, Auckland, New Zealand.
Qiangqiang WangState Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Hua ZhangState Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Jinyou LiDepartment of Geriatrics, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Qixia LuoState Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Yanmeng LuState Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Lanjuan LiState Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
State Key Laboratory of Diagnosis and Treatment of Infectious DiseasesZhejiang University · CNUniversity of Auckland · NZMinistry for Primary Industries · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dysbiosis of oropharyngeal (OP) microbiota is associated with multiple diseases, including H7N9 infection. Different OP microbial colonization states may reflect different severities or stages of disease and affect the effectiveness of the treatments. Current study aims to determine the vital bacteria that could possibly drive the OP microbiota in the H7N9 patients to more severe microbial dysbiosis state. The OP microbiotas of 42 H7N9 patients and 30 healthy subjects were analyzed by a series of bioinformatics and statistical analyses. Two clusters of OP microbiotas in H7N9 patients, i.e., Cluster_1_Diseased and Cluster_2_Diseased, were determined at two microbial colonization states by Partition Around Medoids (PAM) clustering analysis, each characterized by distinct operational taxonomic units (OTUs) and functional metabolites. Cluster_1_Diseased was determined at more severe dysbiosis status compared with Cluster_2_Diseased, while OTU143_

Indexed as

dysbiosis statusH7N9illumina sequencingmicrobial colonization statesoropharyngeal microbiotasecondary bacterial lung infection

Identifiers

PMID32850904
PMCPMC7433009
OpenAlexW3048925744

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.