Tarik J Salameh, Katharine Roth, Lisa Schultz, Zhexi Ma, Anthony S Bonavia, James R Broach, Bin Hu, Judie A Howrylak
{"title":"重症患者肠道微生物群的动态变化及其与死亡率的关系。","authors":"Tarik J Salameh, Katharine Roth, Lisa Schultz, Zhexi Ma, Anthony S Bonavia, James R Broach, Bin Hu, Judie A Howrylak","doi":"10.1186/s13099-023-00567-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Critical illness and care within the intensive care unit (ICU) leads to profound changes in the composition of the gut microbiome. The impact of such changes on the patients and their subsequent disease course remains uncertain. We hypothesized that specific changes in the gut microbiome would be more harmful than others, leading to increased mortality in critically ill patients.</p><p><strong>Methods: </strong>This was a prospective cohort study of critically ill adults in the ICU. We obtained rectal swabs from 52 patients and assessed the composition the gut microbiome using 16 S rRNA gene sequencing. We followed patients throughout their ICU course and evaluated their mortality rate at 28 days following admission to the ICU. We used selbal, a machine learning method, to identify the balance of microbial taxa most closely associated with 28-day mortality.</p><p><strong>Results: </strong>We found that a proportional ratio of four taxa could be used to distinguish patients with a higher risk of mortality from patients with a lower risk of mortality (p = .02). We named this binarized ratio our microbiome mortality index (MMI). Patients with a high MMI had a higher 28-day mortality compared to those with a low MMI (hazard ratio, 2.2, 95% confidence interval 1.1-4.3), and remained significant after adjustment for other ICU mortality predictors, including the presence of the acute respiratory distress syndrome (ARDS) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score (hazard ratio, 2.5, 95% confidence interval 1.4-4.7). High mortality was driven by taxa from the Anaerococcus (genus) and Enterobacteriaceae (family), while lower mortality was driven by Parasutterella and Campylobacter (genera).</p><p><strong>Conclusions: </strong>Dysbiosis in the gut of critically ill patients is an independent risk factor for increased mortality at 28 days after adjustment for clinically significant confounders. Gut dysbiosis may represent a potential therapeutic target for future ICU interventions.</p>","PeriodicalId":12833,"journal":{"name":"Gut Pathogens","volume":"15 1","pages":"66"},"PeriodicalIF":4.3000,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10731755/pdf/","citationCount":"0","resultStr":"{\"title\":\"Gut microbiome dynamics and associations with mortality in critically ill patients.\",\"authors\":\"Tarik J Salameh, Katharine Roth, Lisa Schultz, Zhexi Ma, Anthony S Bonavia, James R Broach, Bin Hu, Judie A Howrylak\",\"doi\":\"10.1186/s13099-023-00567-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Critical illness and care within the intensive care unit (ICU) leads to profound changes in the composition of the gut microbiome. The impact of such changes on the patients and their subsequent disease course remains uncertain. We hypothesized that specific changes in the gut microbiome would be more harmful than others, leading to increased mortality in critically ill patients.</p><p><strong>Methods: </strong>This was a prospective cohort study of critically ill adults in the ICU. We obtained rectal swabs from 52 patients and assessed the composition the gut microbiome using 16 S rRNA gene sequencing. We followed patients throughout their ICU course and evaluated their mortality rate at 28 days following admission to the ICU. We used selbal, a machine learning method, to identify the balance of microbial taxa most closely associated with 28-day mortality.</p><p><strong>Results: </strong>We found that a proportional ratio of four taxa could be used to distinguish patients with a higher risk of mortality from patients with a lower risk of mortality (p = .02). We named this binarized ratio our microbiome mortality index (MMI). Patients with a high MMI had a higher 28-day mortality compared to those with a low MMI (hazard ratio, 2.2, 95% confidence interval 1.1-4.3), and remained significant after adjustment for other ICU mortality predictors, including the presence of the acute respiratory distress syndrome (ARDS) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score (hazard ratio, 2.5, 95% confidence interval 1.4-4.7). High mortality was driven by taxa from the Anaerococcus (genus) and Enterobacteriaceae (family), while lower mortality was driven by Parasutterella and Campylobacter (genera).</p><p><strong>Conclusions: </strong>Dysbiosis in the gut of critically ill patients is an independent risk factor for increased mortality at 28 days after adjustment for clinically significant confounders. 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Gut microbiome dynamics and associations with mortality in critically ill patients.
Background: Critical illness and care within the intensive care unit (ICU) leads to profound changes in the composition of the gut microbiome. The impact of such changes on the patients and their subsequent disease course remains uncertain. We hypothesized that specific changes in the gut microbiome would be more harmful than others, leading to increased mortality in critically ill patients.
Methods: This was a prospective cohort study of critically ill adults in the ICU. We obtained rectal swabs from 52 patients and assessed the composition the gut microbiome using 16 S rRNA gene sequencing. We followed patients throughout their ICU course and evaluated their mortality rate at 28 days following admission to the ICU. We used selbal, a machine learning method, to identify the balance of microbial taxa most closely associated with 28-day mortality.
Results: We found that a proportional ratio of four taxa could be used to distinguish patients with a higher risk of mortality from patients with a lower risk of mortality (p = .02). We named this binarized ratio our microbiome mortality index (MMI). Patients with a high MMI had a higher 28-day mortality compared to those with a low MMI (hazard ratio, 2.2, 95% confidence interval 1.1-4.3), and remained significant after adjustment for other ICU mortality predictors, including the presence of the acute respiratory distress syndrome (ARDS) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score (hazard ratio, 2.5, 95% confidence interval 1.4-4.7). High mortality was driven by taxa from the Anaerococcus (genus) and Enterobacteriaceae (family), while lower mortality was driven by Parasutterella and Campylobacter (genera).
Conclusions: Dysbiosis in the gut of critically ill patients is an independent risk factor for increased mortality at 28 days after adjustment for clinically significant confounders. Gut dysbiosis may represent a potential therapeutic target for future ICU interventions.
Gut PathogensGASTROENTEROLOGY & HEPATOLOGY-MICROBIOLOGY
CiteScore
7.70
自引率
2.40%
发文量
43
期刊介绍:
Gut Pathogens is a fast publishing, inclusive and prominent international journal which recognizes the need for a publishing platform uniquely tailored to reflect the full breadth of research in the biology and medicine of pathogens, commensals and functional microbiota of the gut. The journal publishes basic, clinical and cutting-edge research on all aspects of the above mentioned organisms including probiotic bacteria and yeasts and their products. The scope also covers the related ecology, molecular genetics, physiology and epidemiology of these microbes. The journal actively invites timely reports on the novel aspects of genomics, metagenomics, microbiota profiling and systems biology.
Gut Pathogens will also consider, at the discretion of the editors, descriptive studies identifying a new genome sequence of a gut microbe or a series of related microbes (such as those obtained from new hosts, niches, settings, outbreaks and epidemics) and those obtained from single or multiple hosts at one or different time points (chronological evolution).