Unexpected Origin of C. diff Infection in Hospital Patients

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Scanning electron micrograph of Clostridioides difficile bacteria from a stool sample. Credit: CDC

Key points: 

  • Clostridioides difficile, known as C. diff, is a common hospital-onset infection, but genomic analysis found that transmission between patients is actually uncommon.
  • Patient characteristics determine if in-hospital acquisition of C. diff leads to diarrhea and other complications.
  • New strategies such as employing A.I. models can be developed to identify triggers that lead to serious C. diff infection.

Hospital staff work hard to protect patients from acquiring infections, but hospital-onset infections including Clostridioides difficile, or C. diff, ­still occur. A new study, published in Nature Medicine, reports that C. diff infection may be the result of patient characteristics rather than hospital transmission.

Researchers used ongoing epidemiological studies focused on hospital-acquired infections to analyze daily fecal samples from over 1,100 patients within the intensive care unit at Rush University Medical Center over a 9-month period. They found that over 9% of patients were colonized with C. diff. Whole genome sequencing of the C. diff strains from nearly 4,000 fecal specimens found very little evidence that C. diff strains were the same from one patient to another. As there were only six cases of genomically supported transmission, it appeared that most cases were likely from in-hospital acquisition.

“By systematically culturing every patient, we thought we could understand how transmission was happening,” said study author Arianna Miles-Jay. “The surprise was that, based on genomics, there was very little transmission.”

It is not yet clear what causes the transition from C. diff being present in the gut to it causing diarrhea and other complications in certain patients. As a result, the researchers believe that more work is needed to identify patients who are colonized and to try to prevent infection in them. Using A.I. models to predict patient risk of C. diff infection may be a useful next step toward better and more focused interventions.

“A lot of resources are put into gaining further improvements in preventing the spread of infections,” said the study lead Evan Snitkin of University of Michigan. “There is increasing support to redirect some of these resources to optimize the use of antibiotics and identify other triggers that lead patients harboring C. diff and other healthcare pathogens to develop serious infections.”

 

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