Evidence map›Paper›PMID 37548476›Full record

ArticlemSystems2023

The intestinal microbiota predicts COVID-19 severity and fatality regardless of hospital feeding method.

Vanni Bucci, Doyle V Ward, Shakti Bhattarai, Mayra Rojas-Correa, Ayan Purkayastha, Devon Holler, Ming Da Qu, William G Mitchell, Jason Yang, Samuel Fountain and 8 more

Open access · goldAbstract read
In one paragraph

Article in mSystems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
1.7field-weighted citation impact, top 16% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Inhibition of SARS-CoV-2 infection byMicrobiology spectrum · 2024
    Article
  10. 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

18 authors at 1 institution in 1 country.

Vanni BucciDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.ORCID 0000-0002-3257-2922
Doyle V WardDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Shakti BhattaraiDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Mayra Rojas-CorreaDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Ayan PurkayasthaDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Devon HollerDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Ming Da QuDivision of Infectious Diseases and Immunology, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
William G MitchellDepartment of Internal Medicine/Pediatrics, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Jason YangDepartment of Medicine - Internal Medicine, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Samuel FountainDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Abigail ZeamerDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Catherine S ForconiDepartment of Medicine - Division of Infectious Diseases and Immunology, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.ORCID 0000-0001-7358-5546
Gavin FujimoriDepartment of Medicine - Division of Infectious Diseases and Immunology, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Boaz OdwarDepartment of Medicine - Division of Infectious Diseases and Immunology, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Caitlin CawleyDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Ann M MoormannDepartment of Medicine - Division of Infectious Diseases and Immunology, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.ORCID 0000-0003-1113-2829
Mireya WessolosskyDepartment of Medicine - Division of Infectious Diseases and Immunology, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.
Ana Maldonado-ContrerasDepartment of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School , Worcester, Massachusetts, USA.ORCID 0000-0002-5967-9623
University of Massachusetts Chan Medical School · US

Funding

Enhancing racial and ethnic diversity inCOVID-19 research participation through storytelling (COVIDstory)U01CA261276 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI MOORMANN, ANN M · 2020 to 2020
$2.0M
NCI NIH HHS U01 CA261276
6 · The paper itself

Abstract

SARS-CoV-2-positive patients exhibit gut and oral microbiome dysbiosis, which is associated with various aspects of COVID-19 disease (1-4). Here, we aim to identify gut and oral microbiome markers that predict COVID-19 severity in hospitalized patients, specifically severely ill patients compared to moderately ill ones. Moreover, we investigate whether hospital feeding (solid versus enteral), an important cofounder, influences the microbial composition of hospitalized COVID-19 patients. We used random forest classification machine learning models with interpretable secondary analyses. The gut, but not the oral microbiota, was a robust predictor of both COVID-19-related fatality and severity of hospitalized patients, with a higher predictive value than most clinical variables. In addition, perturbations of the gut microbiota due to enteral feeding did not associate with species that were predictive of COVID-19 severity. IMPORTANCE SARS-CoV-2 infection leads to wide-ranging, systemic symptoms with sometimes unpredictable morbidity and mortality. It is increasingly clear that the human microbiome plays an important role in how individuals respond to viral infections. Our study adds to important literature about the associations of gut microbiota and severe COVID-19 illness during the early phase of the pandemic before the availability of vaccines. Increased understanding of the interplay between microbiota and SARS-CoV-2 may lead to innovations in diagnostics, therapies, and clinical predictions.

Indexed as

COVID-19Gastrointestinal MicrobiomeFeeding MethodsHospitalsHumansSARS-CoV-2COVID-19dietenteral feedingfatalitymicrobiotapredictorsrandom forest classificationseverity

Identifiers

PMID37548476
PMCPMC10469851
OpenAlexW4385617043

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.