Predicting the risk for hospital-onset Clostridium difficile infection (HO-CDI) at the time of inpatient admission: HO-CDI risk score
- PMID: 25753106
- PMCID: PMC5768429
- DOI: 10.1017/ice.2015.37
Predicting the risk for hospital-onset Clostridium difficile infection (HO-CDI) at the time of inpatient admission: HO-CDI risk score
Abstract
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 collected 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 nonduplicate 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 (ie, a rate of 4.1 per 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 white blood cell count >11,000 mm3. The model had a c-statistic of 0.78 (95% confidence interval [CI], 0.76-0.81) with good calibration. Among 79% of patients with risk scores of 0-7, 19 HO-CDIs occurred per 10,000 admissions; for patients with risk scores >20, 623 HO-CDIs occurred per 10,000 admissions (P<.0001).
Conclusion: Using clinical parameters available at the time of admission, this HO-CDI model demonstrated good predictive ability, and it may have utility as an early risk identification tool for HO-CDI preventive interventions and outcome comparisons.
Conflict of interest statement
Dr. McDonald has no conflict of interest to disclose.
Drs. Tabak, Johannes, Sun, and Nunez are employees of CareFusion. No other conflict of interest to disclose.
Figures
Comment in
-
The Protective Role of Albumin in Clostridium difficile Infection: A Step Toward Solving the Puzzle.Infect Control Hosp Epidemiol. 2015 Dec;36(12):1478-9. doi: 10.1017/ice.2015.221. Epub 2015 Oct 12. Infect Control Hosp Epidemiol. 2015. PMID: 26456662 No abstract available.
References
-
- Lucado J, Gould C, Elixhauser A. HCUP Statistical Brief #124. Agency for Healthcare Research and Quality; Rockville, MD: Jan, 2012. Clostridium difficile Infections (CDI) in Hospital Stays, 2009. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb124.pdf. - PubMed
-
- Murphy SL, Xu J, Kochanek KD. Deaths: Final Data for 2010. National Vital Statistics Reports. 2013;61(4) http://www.cdc.gov/nchs/data/nvsr/nvsr61/nvsr61_04.pdf. Accessed January 9, 2014. - PubMed
-
- Dubberke ER, Wertheimer AI. Review of current literature on the economic burden of Clostridium difficile infection. Infect Control Hosp Epidemiol. 2009 Jan;30(1):57–66. - PubMed
-
- Tabak YP, Zilberberg MD, Johannes RS, Sun X, McDonald LC. Attributable burden of hospital-onset Clostridium difficile infection: a propensity score matching study. Infect Control Hosp Epidemiol. 2013 Jun;34(6):588–596. - PubMed
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
