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Is it feasible to perform microbiota analysis without matching antibiotic usage?

Critical Care volume 27, Article number: 147 (2023) Cite this article

The Original Article was published on 28 March 2023


Dear Editor,


We read the article by Sun et al. published in Critical Care with great interest [1]. The authors conducted a retrospective cohort study to analyze the correlation between gut microbiota, metabolome, and clinical outcomes in patients with sepsis. However, it should be noted that this study may suffer from serious biases and errors.

As is well known, antibiotics, especially broad-spectrum antibiotics, can cause significant disruption to the gut microbiota, including a 10,000-fold decrease in bacterial load and a decrease in diversity [2, 3]. Different antibiotic treatments can lead to the depletion of different gut microbial populations, which is a classic modeling scheme for the difficile animal model. In this study, the authors included almost all sepsis patients who had received different antibiotic treatments before sample collection, including broad-spectrum carbapenem antibiotics. However, they did not seek to include ordinary ward patients who had received carbapenem antibiotic treatment as a control group. Instead, they used healthy individuals who had not received antibiotic treatment as controls. In fact, the impact of factors such as the use of broad-spectrum antibiotics, including carbapenem antibiotics, may have a greater impact on the gut microbiota than sepsis itself. Therefore, such confounding factors make the results of this study unreliable.

Furthermore, there are also flaws in the analysis methods used in this study. Firstly, the authors used outdated OTUs for gut microbiota analysis, and ASV analysis was not performed, which weakened the power of this study. Secondly, the authors only used Lefse for differential analysis of gut microbiota between the two groups, without using more robust methods such as DESeq2. Thirdly, in this study, only a small proportion of the analysis results were adjusted for p-values, which can lead to many false positive results.

Overall, this study has value of publication, but many issues still need to be addressed.

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References

  1. Sun S, Wang D, Dong D, et al. Altered intestinal microbiome and metabolome correspond to the clinical outcome of sepsis. Crit Care. 2023;27(1):127.

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  2. Hagan T, Cortese M, Rouphael N, et al. Antibiotics-driven gut microbiome perturbation alters immunity to vaccines in humans. Cell. 2019;178(6):1313-1328.e13.

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  3. van Werkhoven CH, Ducher A, Berkell M, et al. Incidence and predictive biomarkers of Clostridioides difficile infection in hospitalized patients receiving broad-spectrum antibiotics. Nat Commun. 2021;12(1):2240.

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

Open Access fee was provided by the National Key Research and Development Program (grant # 2020YFE0204300) and the National Science & Technology Major Project of China (grant #2017ZX10204401).

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Author notes

  1. Mingqiang Wang and Huijun Feng have contributed equally to this work

Authors and Affiliations

  1. Zhengzhou University People’s Hospital, Henan University People’s Hospital, Zhengzhou, China

    Mingqiang Wang

  2. Department of Critical Care Medicine, Henan Key Laboratory for Critical Care Medicine, Zhengzhou Key Laboratory for Critical Care Medicine, Henan Provincial People’s Hospital, Zhengzhou, China

    Mingqiang Wang

  3. Department of Neurology, The First People’s Hospital of Pinghu, Pinghu, China

    Mingqiang Wang & Huijun Feng

Authors
  1. Mingqiang Wang
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  2. Huijun Feng
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MQW and HJF participated in the discussion and wrote the manuscript. Both authors read and approved the final manuscript.

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Correspondence to Mingqiang Wang.

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The authors declare that they have no competing interests.

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Wang, M., Feng, H. Is it feasible to perform microbiota analysis without matching antibiotic usage?. Crit Care 27, 147 (2023). https://doi.org/10.1186/s13054-023-04435-4

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  • DOI: https://doi.org/10.1186/s13054-023-04435-4

Critical Care

ISSN: 1364-8535