Currently, lung infections caused by multidrug-resistant organisms (MDROs) represent a significant global health burden. In the intensive care unit (ICU), the administration of antibiotics, opioids, proton pump inhibitors (PPIs), vasoconstrictors, and parenteral nutrition-combined with the underlying severity of critical illness-leads to profound disruption of the gut microbiota, which may concurrently impair pulmonary microecology and negatively influence long-term patient outcomes. Although pulmonary microecology has garnered increasing scientific attention, the potential causal link between gut dysbiosis and the development of pulmonary microbial imbalance remains poorly elucidated. As such, it is currently unclear whether gut dysbiosis in patients with MDRO-related pulmonary infection contributes to or exacerbates pulmonary microecological disturbances. This study aims to characterize differences in gut microbiota composition and pulmonary microecology between ICU patients with and without MDRO-associated pulmonary infection, and to investigate the association between alterations in gut microbiota and changes in the pulmonary microbial environment. Fecal microbiota transplantation (FMT) is a therapeutic intervention involving the transfer of functionally intact microbial communities from healthy donors to recipients, with the objective of restoring a disrupted gut microbiota and treating both gastrointestinal and systemic conditions. Evidence suggests that FMT effectively reduces intestinal colonization by MDROs and prevents secondary infections in non-ICU populations. Over the past decade, FMT has demonstrated transformative potential in managing refractory intestinal and extra-intestinal diseases, offering a novel, mechanism-driven strategy for modulating host microbial ecosystems. These findings indicate that FMT not only facilitates the restoration of a balanced gut microbiota but may also reduce recurrent infections by suppressing the proliferation of drug-resistant bacterial strains. Given that gut-resident microorganisms serve as a major reservoir for enterogenic infections, hospital-acquired bacteremia, and ventilator-associated pneumonia, this project will conduct a prospective, randomized controlled trial (RCT) in critically ill patients admitted to the ICU with pulmonary infection-specifically targeting those eligible for antibiotic de-escalation and exhibiting clinical features of food intolerance syndrome. FMT will be administered via a nasojejunal tube to correct gut dysbiosis induced by broad-spectrum antimicrobials and other iatrogenic factors. The primary objectives are to evaluate the efficacy and safety of FMT in promoting the restoration of pulmonary microbial homeostasis and to assess its impact on clinically relevant outcomes, including length of stay in the ICU, ICU mortality, in-hospital mortality, and 28-day all-cause mortality.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Enrollment
150
Prepare 300 ml of intestinal flora suspension from 100-150 g of feces. Subjects can eat and drink freely during preparation but must fast for at least 2 hours before FMT (water allowed). No food or water is permitted within 2 hours after FMT.
Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, China
RECRUITINGDynamic changes in the total SOFA score
Change in total SOFA score from randomization (baseline) to 168 hours post-intervention
Time frame: Within 24 hours before FMT intervention, and on days 12, 3, 4, 5, 6 and 7 after FMT initiation
Changes in pulmonary microbiota diversity
Metagenomics profiling of BALF was conducted to compare the pulmonary microbiota between the two groups. Metagenomic sequencing will be performed to analyze the dynamic changes in α-diversity (Shannon index), β-diversity, and the relative abundance of specific microbial taxa, including the Firmicutes-to-Bacteroidetes ratio, and potential pathogens.
Time frame: Within 24 hours before FMT intervention, and at 24, 72, 120 and 168 hours after FMT initiation
Changes in intestinal microbiota diversity
Metagenomics profiling of rectal swabs was conducted to compare the gut microbiota between the two groups. Metagenomic sequencing will be performed to analyze the dynamic changes in α-diversity (Shannon index), β-diversity, and the relative abundance of specific microbial taxa, including the Firmicutes-to-Bacteroidetes ratio, and potential pathogens.
Time frame: Within 24 hours before FMT intervention, and at 24, 72, 120 and 168 hours after FMT initiation
Alterations in serum metabolites
Serum samples were collected for metabolomics analysis to comprehensively examine the composition and changes of endogenous small molecule metabolites in the blood.
Time frame: Within 24 hours before FMT intervention, and at 24, 72, 120 and 168 hours after FMT initiation
Change in the respiratory subscore of SOFA
Change in the respiratory subscore of SOFA from randomization (baseline) to 168 hours post-intervention
Time frame: Within 24 hours before FMT intervention, and on days 12, 3, 4, 5, 6 and 7 after FMT initiation
Correlation between gut microbiota and pulmonary microecology
The results obtained from metagenomic and metabolomic analyses of rectal swabs and BALF were used to explore the relationship between the two
Time frame: Within 24 hours before FMT intervention, and at 24, 72, 120 and 168 hours after FMT initiation
Serum lipopolysaccharide (LPS)
The determination of serum LPS is used as an indicator for evaluating intestinal barrier function.
Time frame: Within 24 hours before FMT intervention, and on days 1-3, 5, and 7 after inclusion
Serum diamine oxidase (DAO)
The determination of serum DAO is used as an indicator for evaluating intestinal barrier function.
Time frame: Within 24 hours before FMT intervention, and on days 1-3, 5, and 7 after inclusion
Serum D-lactic acid
The determination of serum D-lactic acid is used as an indicator for evaluating intestinal barrier function.
Time frame: Within 24 hours before FMT intervention, and on days 1-3, 5, and 7 after inclusion
Serum Citrulline
The determination of serum Citrulline is used as an indicator for evaluating intestinal barrier function.
Time frame: Within 24 hours before FMT intervention, and on days 1-3, 5, and 7 after inclusion
Changes of APACHE Ⅱ score
The APACHE II scoring system serves as a critical tool for evaluating the clinical status and prognosis of ICU patients. This system comprises three components: the Acute Physiology Score (APS), the Age Score, and the Chronic Health Evaluation Score. The total score is derived by summing these three components. The theoretical maximum score is 71, with higher scores indicating more severe conditions. Notably, the APS encompasses 12 physiological parameters and introduces a formula for calculating the risk of death (R). By aggregating the R values of all patients and dividing by the total number of patients, the predicted mortality rate for the patient population can be estimated.
Time frame: Within 24 hours before FMT intervention, and on days 1-7 after inclusion
Length of stay in the ICU
Duration of ICU treatment for the patient
Time frame: From date of randomization until the date of discharge from the ICU or date of death from any cause during ICU stay, whichever came first, assessed up to 6 weeks
ICU mortality rate
Mortality rate in ICU
Time frame: From date of randomization until the date of discharge from the ICU or date of death from any cause during ICU stay, whichever came first, assessed up to 6 weeks
In-hospital mortality rate
Mortality rate during hospitalization
Time frame: From date of randomization until the date of discharge from the hospital or date of death from any cause during hospitalization, whichever came first, assessed up to 6 weeks
28-day all-cause mortality rate
The mortality rate within 28 days after inclusion in the study
Time frame: Within 28 days after inclusion
90-day all-cause mortality rate
The mortality rate within 90 days after inclusion in the study
Time frame: Within 90 days after inclusion
90-day post-discharge readmission rate
The proportion of patients readmitted within 90 days after discharge among those enrolled in the study
Time frame: Within 90 days after inclusion
Secondary pulmonary infection rate within 90 days of study enrollment
The incidence of secondary pulmonary infection within 90 days following study enrollment
Time frame: Within 90 days after inclusion
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