Evidence map›Paper›PMID 27837233›Full record

ArticleIntensive care medicine2017

Critically ill patients demonstrate large interpersonal variation in intestinal microbiota dysregulation: a pilot study.

Jacqueline M Lankelma, Lonneke A van Vught, Clara Belzer, Marcus J Schultz, Tom van der Poll, Willem M de Vos, W Joost Wiersinga

Abstract readComparative Study
In one paragraph

Article in Intensive care medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 161 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
161citing papers in PubMed, 3 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

161 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
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  7. [Mechanisms of live combinedZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2026
    Article
  8. Review
  9. Article
  10. Can We Identify Severe Dysbiosis at the Bedside?Critical care explorations · 2026
    Article
  11. Article
  12. Article
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  15. Sepsis and the diverse organ-gastrointestinal tract axis.World journal of critical care medicine · 2025
    Review
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  17. Review
  18. The gastrointestinal microbiome in critical illness: A Clinician's guide to mechanisms, emerging tools, and therapeutic questions.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2025
    Review
  19. Review
  20. Article

101 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Jacqueline M LankelmaCenter for Experimental and Molecular Medicine, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Room G2-130, 1105 AZ, Amsterdam, The Netherlands. j.m.lankelma@amc.uva.nl.ORCID http://orcid.org/0000-0001-9815-0231
Lonneke A van VughtCenter for Experimental and Molecular Medicine, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Room G2-130, 1105 AZ, Amsterdam, The Netherlands.
Clara BelzerLaboratory of Microbiology, Wageningen University, Wageningen, The Netherlands.
Marcus J SchultzDepartment of Intensive Care, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Tom van der PollCenter for Experimental and Molecular Medicine, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Room G2-130, 1105 AZ, Amsterdam, The Netherlands.
Willem M de VosLaboratory of Microbiology, Wageningen University, Wageningen, The Netherlands.
W Joost WiersingaCenter for Experimental and Molecular Medicine, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Room G2-130, 1105 AZ, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe intestinal microbiota has emerged as a virtual organ with essential functions in human physiology. Antibiotic-induced disruption of the microbiota in critically ill patients may have a negative influence on key energy resources and immunity. We set out to characterize the fecal microbiota composition in critically ill patients both with and without sepsis and to explore the use of microbiota-derived markers for clinical outcome measurements in this setting.

methodsIn this prospective observational cohort study we analyzed the fecal microbiota of 34 patients admitted to the intensive care unit. Fifteen healthy subjects served as controls. The fecal microbiota was phylogenetically characterized by 16S rRNA gene sequencing, and associations with clinical outcome parameters were evaluated.

resultsA marked shift in fecal bacterial composition was seen in all septic and non-septic critically ill patients compared with controls, with extreme interindividual differences. In 13 of the 34 patients, a single bacterial genus made up >50% of the gut microbiota; in 4 patients this was even >75%. A significant decrease in bacterial diversity was observed in half of the patients. No associations were found between microbiota diversity, Firmicutes/Bacteroidetes ratio, or Gram-positive/Gram-negative ratio and outcome measurements such as complications and survival.

conclusionsWe observed highly heterogeneous patterns of intestinal microbiota in both septic and non-septic critically ill patients. Nevertheless, some general patterns were observed, including disappearance of bacterial genera with important functions in host metabolism. More detailed knowledge of the short- and long-term health consequences of these major shifts in intestinal bacterial communities is needed.

Indexed as

AgedAged, 80 and overAnti-Bacterial AgentsBiomarkersCritical IllnessFecesFemaleGastrointestinal MicrobiomeHumansMaleMiddle AgedNetherlandsPilot ProjectsProspective StudiesSepsisAnti-Bacterial AgentsBiomarkersAntibioticsCritically illGut microbiotaIntensive care unitSepsis

Identifiers

PMID27837233
PMCPMC5203863

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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.