The following is a summary of “Fecal microbiota composition is a better predictor of recurrent Clostridioides difficile infection than clinical factors in a prospective, multicentre cohort study,” published in the July 2024 issue of Infectious Disease by Rossen et al.

Clostridioides difficile infection (CDI), a common cause of antibiotic-related diarrhea, can be challenging to treat with expensive options like Fidaxomicin and fecal microbiota transplantation (FMT) for recurrent CDI (reCDI) cases.

Researchers conducted a retrospective study to develop a prediction model for recurrent CDI. The model used gut microbiota and clinical characteristics to identify patients who might benefit from early treatment with fidaxomicin or FMT.

They involved adult patients diagnosed with a primary episode of CDI. Fecal samples and clinical data were gathered before and after 5 days of CDI treatment. The follow-up period lasted 8 weeks. Microbiota composition was analyzed using IS-pro, which profiles bacteria based on differences in ribosomal DNA’s 16–23 S interspace regions. Prediction models for reCDI were developed using Bayesian additive regression trees (BART) and adaptive group-regularized logistic ridge regression (AGRR).

The results showed that out of 209 patients, 25% developed reCDI. Variables related to microbiota composition were more predictive of reCDI than clinical factors in combined models. Bacteroidetes abundance and diversity after CDI treatment start, along with increased Proteobacteria diversity compared to baseline, were the strongest predictors of reCDI. A BART model including these factors achieved 95% sensitivity and 78% specificity, which decreased to 67% and 62% in predictions outside the sample.

Investigators found early changes in gut bacteria after CDI treatment were better at predicting recurrent CDI than traditional clinical factors, but the accuracy wasn’t yet good enough for everyday use.

Source: bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-024-09506-7