Evidence map›Paper›PMID 33607294›Full record

ArticleGenomics, proteomics & bioinformatics2020

Classification of the Gut Microbiota of Patients in Intensive Care Units During Development of Sepsis and Septic Shock.

Wanglin Liu, Mingyue Cheng, Jinman Li, Peng Zhang, Hang Fan, Qinghe Hu, Maozhen Han, Longxiang Su, Huaiwu He, Yigang Tong and 2 more

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

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  11. Host-Microbiome Interaction in the Intensive Care Unit.Diseases (Basel, Switzerland) · 2025
    Review
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  15. Frontiers in microbiology · 2025
    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

12 authors.

Wanglin LiuDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Beijing 100730, China.
Mingyue ChengKey Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Jinman LiState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Peng ZhangKey Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Hang FanState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Qinghe HuDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Beijing 100730, China.
Maozhen HanKey Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Longxiang SuDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Beijing 100730, China.
Huaiwu HeDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Beijing 100730, China.
Yigang TongBeijing Advanced Innovation Center for Soft Matter Science and Engineering (BAIC-SM), College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China. Electronic address: tong.yigang@gmail.com.
Kang NingKey Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: ningkang@hust.edu.cn.
Yun LongDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Beijing 100730, China. Electronic address: longy@pumch.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The gut microbiota of intensive care unit (ICU) patients displays extreme dysbiosis associated with increased susceptibility to organ failure, sepsis, and septic shock. However, such dysbiosis is difficult to characterize owing to the high dimensional complexity of the gut microbiota. We tested whether the concept of enterotype can be applied to the gut microbiota of ICU patients to describe the dysbiosis. We collected 131 fecal samples from 64 ICU patients diagnosed with sepsis or septic shock and performed 16S rRNA gene sequencing to dissect their gut microbiota compositions. During the development of sepsis or septic shock and during various medical treatments, the ICU patients always exhibited two dysbiotic microbiota patterns, or ICU-enterotypes, which could not be explained by host properties such as age, sex, and body mass index, or external stressors such as infection site and antibiotic use. ICU-enterotype I (ICU E1) comprised predominantly Bacteroides and an unclassified genus of Enterobacteriaceae, while ICU-enterotype II (ICU E2) comprised predominantly Enterococcus. Among more critically ill patients with Acute Physiology and Chronic Health Evaluation II (APACHE II) scores > 18, septic shock was more likely to occur with ICU E1 (P = 0.041). Additionally, ICU E1 was correlated with high serum lactate levels (P = 0.007). Therefore, different patterns of dysbiosis were correlated with different clinical outcomes, suggesting that ICU-enterotypes should be diagnosed as independent clinical indices. Thus, the microbial-based human index classifier we propose is precise and effective for timely monitoring of ICU-enterotypes of individual patients. This work is a first step toward precision medicine for septic patients based on their gut microbiota profiles.

Indexed as

Gastrointestinal MicrobiomeSepsisShock, SepticHumansIntensive Care UnitsRNA, Ribosomal, 16SRNA, Ribosomal, 16SEnterotypeGut microbiotaPrecision medicineSepsisSeptic shock

Identifiers

PMID33607294
PMCPMC8377022

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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.