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The Patients' Voice in Clostridioides difficile Infection: Large Language Model-Assisted Thematic Analysis of Patient
Medrxiv : the Preprint Server for Health Sciences
|July 17, 2026
Summary
Clostridioides difficile infection (CDI) patient experiences reveal a multidimensional burden that shifts with disease course, with psychological, financial, and caregiver needs often unaddressed by current guidelines.
Area of Science:
- Medical Informatics
- Patient Reported Outcomes
- Computational Linguistics
Background:
- Clostridioides difficile infection (CDI) presents a significant burden extending beyond the gastrointestinal tract.
- Current outcome measures inadequately capture the full patient experience of CDI.
- Understanding the evolving burden of CDI across its disease course is crucial for improving patient care.
Purpose of the Study:
- To utilize frontier large language models (LLMs) to analyze patient and caregiver narratives of CDI at scale.
- To describe how the burden of CDI shifts with different disease courses, including recurrence and fulminant severity.
- To identify gaps between patient priorities, clinical guidelines, and therapy access.
Main Methods:
- Analysis of 189 patient and caregiver testimonials from the Peggy Lillis Foundation corpus.
- Categorization of testimonials into four cohorts based on recurrence and fulminant severity (rfCDI, fCDI, rCDI, non-rfCDI).
- Application of two independent LLMs for coding thematic domains, fulminant flags, semantic fields, and narrative arcs, with clinician validation for inter-rater reliability.
Main Results:
- Treatment trajectory dominated recurrent CDI narratives, while death and near-death experiences were central to fulminant CDI narratives.
- Psychological burden was reported by over 97% of patients with fulminant CDI.
- Caregiver and bereavement content was prevalent in fulminant CDI (66.7%), and diagnostic failure was common in recurrent CDI (47.6-56.1%).
- Financial, mental-health, and caregiver burdens were prominent but largely unaddressed by existing guidelines.
Conclusions:
- Patient narratives highlight a multidimensional CDI burden that is dependent on disease course (recurrence, fulminant, bereavement).
- Significant discrepancies exist between patient-prioritized needs and current clinical guidelines and therapy access.
- Frontier-LLM coding, validated by clinicians, provides a reproducible method for translating patient priorities into research, care, and policy improvements.
