Objective: Recurrent methicillin-resistant Staphylococcus aureus (MRSA) infections are a significant problem in the healthcare system. Our objective was to create a clinical prediction rule to identify Veterans at high-risk of recurrent MRSA infections.
Methods: A retrospective cohort study of Veterans with MRSA bacteremia was performed using patient data from 2003 to 2011. Recurrent MRSA infection was defined as a positive blood culture between two days and 180 days after discharge from the index hospitalization. Severity of illness was measured at the time of admission using a modified APACHE score. Patients were randomly split into a development or validation cohort. Using the development cohort, variables significant in predicting recurrence on univariate analysis were input into a logistic regression model. The final model, c-statistics, and receiver operating characteristic curves were compared in each cohort.
Results: Of 9,279 patients in the combined cohort, 1,127 (12.1%) had a recurrent MRSA infection within 180 days of the index infection. Using the development cohort, the risk factors identified and included in the logistic regression model were severity of illness, duration of bacteremia, distance to care, lack of MRSA-directed antibiotic therapy, renal failure, coagulopathy, cancer, and cardiac arrhythmia. The model had average discrimination (c-statistic, 0.657), with 68.9% sensitivity and 54.0% specificity. The validation cohort also had average discrimination (c-statistic, 0.625), with 66.8% sensitivity and 52.6% specificity.
Conclusions: Our results identify important risk factors for MRSA recurrence and may help to guide clinicians in targeting high-risk patients for treatment and aggressive follow-up.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-5077 |
| Date | 01 May 2014 |
| Creators | Albertson, Justin Paul |
| Contributors | Schweizer, Marin L. |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright 2014 Justin Albertson |
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