A Simple Prediction Model for Clostridioides difficile Infection: A Hospital-Based Administrative Database Study.

Abstract

Background and aim: Few prediction scores for Clostridioides difficile infection (CDI), a potentially life-threatening nosocomial diarrhea, combine high accuracy with simplicity. A simple prediction score for routine clinical practice is needed.

Methods: We conducted a retrospective cohort study of all inpatients aged ≥ 18 at a secondary care hospital in Japan. The derivation and validation cohorts consisted of patients from January 2016 to December 2020 and January 2021 to September 2022, respectively. Demographic and clinical data were retrieved using electronic medical records and an administrative database. The primary outcome was to derive and validate an accurate, simple prediction score for primary hospital-onset CDI. A derived prediction score by logistic regression analysis was calibrated and validated.

Results: CDI developed in 102 of 25 517 and 25 of 6259 patients in the derived and validation cohorts (2.7 cases/10 000 patient-days). The derived model for predicting CDI, including antibiotic use, acid suppressant (proton pump inhibitors or vonoprazan) use, Charlson comorbidity index, and Barthel index, yielded c-statistics of 0.89 and 0.82 in the derivation and validation cohort. The model was well calibrated.

Conclusions: This simple prediction score enables early medical intervention and modification of treatment plans to reduce the risk of developing primary hospital-onset CDI.