A clinical decision resource to assess patient risk for Clostridium Difficile (C. Diff.)

1. A clinical decision resource to assess patient
risk for Clostridium Difficile (C. Diff.)
Surendra Walter Singaram
CDiffense

2. ● Contagious bacteria that thrives in an ICU ward.
Leffler, D. and Lamont, T. Clostridium Difficile. New England Journal
of Medicine 2015
What’s C. Diff.?
● Leading cause of antibiotic-associated diarrhea worldwide.
● C. Diff. infections increase annual healthcare costs by $1.5B
and increase hospitalization costs by a factor of 4.

3. Doctor orders lab tests
Approach: Does the patient have C. Diff.?
Solution based on learning patterns
from electronic health records
ML
Model
High
Risk
Low
Risk

4. EDA shows challenges
● The MIMIC-III database contains information on 60,000 patients that visited the ICU at the
Beth Deaconess Hospital from 2001 to 2012.
○ thorough record of lab tests, clinician notes, medications, diagnoses, etc.
○ features: vitals, admission location/type,initial diagnosis, estimated length of stay

5. Imbalanced data: C. Diff is rare
● Under sample to balance data
● Use Area under ROC curve to
gauge model performance

6. Logistic Regression shows robust performance

7. Web application
My web application

8. Results
Built a clinical decision resource by using ML to learn C. Diff
positive/negative distributions; in the process, we also identified risk
factors for C. Diff.

9. Surendra Walter Singaram
B.S. Chemistry, Mathematics PhD. Physical Chemistry Post. Doc. Physics

10. Logistic Regression: Model Details

11. Logistic Regression: Model Details