Effect of preoperative immunonutrition on fecal microbiota in colon cancer patients: a secondary analysis of a randomized controlled trial

BACKGROUND/OBJECTIVES

This study aimed to evaluate the effect of preoperative immunonutrition on the composition of fecal microbiota following a colon cancer surgery.

MATERIALS/METHODS

This study was a secondary analysis of a randomized controlled trial assessing the impact of preoperative immunonutrition on the postoperative outcomes of colon cancer surgery. Patients with primary colon cancer were enrolled and randomly assigned to receive additional preoperative immunonutrition or a normal diet alone. Oral nutritional supplementation (400 mL/day) with arginine and ω-3 fatty acids were administered to patients in the immunonutrition group for 7 days prior to surgery. Thirty-two fecal samples were collected from 16 patients in each group, and the composition of fecal microbiota was compared between the 2 groups.

RESULTS

At the phylum level, no significant difference was observed in the composition of microbiota between the 2 groups (Firmicutes, 69.1% vs. 67.5%, P = 0.624; Bacteroidetes, 19.3% vs. 18.1%, P = 0.663; Actinobacteria, 6.7% vs. 10.6%, P = 0.080). The Firmicutes/Bacteroidetes ratio (4.43 ± 2.32 vs. 4.55 ± 2.51, P = 0.897) was also similar between the 2 groups. At the genus level, the proportions of beneficial bacteria such as Faecalibacterium spp. (8.1% vs. 6.4%, P = 0.328) and Prevotella spp. (6.9% vs. 4.8%, P = 0.331) were higher, while that of Clostridium spp. was lower (0.5% vs. 1.2%, P = 0.121) in the immunonutrition group, but the difference was not significant.

CONCLUSIONS

Immunonutrition showed no significant association with the composition of fecal microbiota. The relationship between immunonutrition and the fecal microbiota should be investigated further in large-scale studies.

Anastomotic Leak is Increased With Clostridium difficile Infection After Colectomy: Machine Learning-Augmented Propensity Score Modified Analysis of 46 735 Patients

BACKGROUND

Clostridium difficile infection (CDI) is now the most common cause of healthcare-associated infections, with increasing prevalence, severity, and mortality of nosocomial and community-acquired CDI which makes up approximately one third of all CDI. There are also increased rates of asymptomatic colonization particularly in high-risk patients. C difficile is a known collagenase-producing bacteria which may contribute to anastomotic leak (AL).

METHODS

Machine learning-augmented multivariable regression and propensity score (PS)-modified analysis was performed in this nationally representative case-control study of CDI and anastomotic leak, mortality, and length of stay for colectomy patients using the ACS-NSQIP database.

RESULTS

Among 46 735 colectomy patients meeting study criteria, mean age was 61.7 years (SD 14.38), 52.2% were woman, 72.5% were Caucasian, 1.5% developed CDI, 3.1% developed anastomotic leak, and 1.6% died. In machine learning (backward propagation neural network)-augmented multivariable regression, CDI significantly increases anastomotic leak (OR 2.39, 95% CI 1.70-3.36; P < .001), which is similar to the neural network results. Having CDI increased the independent likelihood of anastomotic leak by 3.8% to 6.8% overall, and in dose-dependent fashion with increasing ASA class to 4.3%, 5.7%, 7.6%, and 10.0%, respectively, for ASA class I to IV. In doubly robust augmented inverse probability weighted PS analysis, CDI significantly increases the likelihood of AL by 4.58% (95% CI 2.10-7.06; P < .001).

CONCLUSIONS

This is the first known nationally representative study on CDI and AL, mortality, and length of stay among colectomy patients. Using advanced machine learning and PS analysis, we provide evidence that suggests CDI increases AL in a dose-dependent manner with increasing ASA Class.