Predicting the Risk for Hospital-onset Clostridium difficile Infection (HO-CDI) at the Time of Inpatient Admission: HO-CDI Risk Score

Details

• Alternative Title:
  Infect Control Hosp Epidemiol
• Personal Author:
  Tabak, Ying P. ; Johannes, Richard S. ; Sun, Xiaowu ; Nunez, Carlos M. ; McDonald, L. Clifford
• Description:
  Objective ; To predict the likelihood of hospital-onset Clostridium difficile infection (HO-CDI) based on patient clinical presentations at admission ; Design ; Retrospective data analysis ; Setting ; Six US acute care hospitals ; Patients ; Adult inpatients ; Methods ; We used clinical data present at the time of admission in electronic health record (EHR) systems to develop and validate a HO-CDI predictive model. The outcome measure was HO-CDI cases identified by a non-duplicate positive C. difficile toxin assay result with stool specimens collected >48 hours after inpatient admission. We fit a logistic regression model to predict the risk of HO-CDI. We validated the model using 1,000 bootstrap simulations. ; Results ; Among 78,080 adult admissions, 323 HO-CDI cases were identified (4.1/1,000 admissions). The logistic regression model yielded 14 independent predictors, including hospital community onset CDI pressure, patient age ≥65, previous healthcare exposures, CDI in previous admission, admission to the intensive care unit, albumin ≤3 g/dL, creatinine >2.0 mg/dL, bands > 32%, platelets ≤150 or >420 109/L, and WBC >11,000 mm3. The model had a c-statistic of 0.78 (95% CI: 0.76, 0.81) with good calibration. For 79% patients with risk score of 0-7, there were 19 HO-CDIs per 10,000 admissions; for patients with risk score of 20+, there were 623 HO-CDIs per 10, 000 admissions (P<0.0001). ; Conclusion ; Using clinical parameters available at the time of admission, this HO-CDI model displayed a good predictive ability. It may have utility as an early risk identification tool for HO-CDI preventive interventions and outcome comparisons.
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• Keywords:
  • Clostridium difficile Infection (CDI)
  • predictive model
  • CDI risk score
  • electronic health record (EHR)
  • electronic medical record (EMR)
  • laboratory data
  • risk adjustment
  • Adult
  • Aged
  • Anti-Bacterial Agents
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• Source:
  Infect Control Hosp Epidemiol. 36(6):695-701
• Pubmed ID:
  25753106
• Pubmed Central ID:
  PMC5768429
• Document Type:
  Journal Article
• Funding:
  CC999999/Intramural CDC HHSUnited States/
• Volume:
  36
• Issue:
  6
• Download URL:
  https://stacks.cdc.gov/view/cdc/50877/cdc_50877_DS1.pdf
• File Type:
  [PDF - 547.55 KB]
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:30e2fc9a8ace0cd7df2e11173e87d9d9939a263aed9b29c9d20cbfe4febad9e6