Karim Khader1,2, L Silvia Munoz-Price3, Ryan Hanson4, Vanessa Stevens1,2, Lindsay T Keegan1,2, Alun Thomas1,2, Liliana E Pezzin4,5, Ann Nattinger3,4, Siddhartha Singh3,4, Matthew H Samore1,2. 1. Informatics, Decision-Enhancement, and Analytic Sciences (IDEAS) Center of Innovation, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah, USA. 2. Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA. 3. Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin, USA. 4. Collaborative for Healthcare Delivery Science, Medical College of Wisconsin, Milwaukee, Wisconsin, USA. 5. Institute for Health and Equity, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Abstract
BACKGROUND: The key epidemiological drivers of Clostridioides difficile transmission are not well understood. We estimated epidemiological parameters to characterize variation in C. difficile transmission, while accounting for the imperfect nature of surveillance tests. METHODS: We conducted a retrospective analysis of C. difficile surveillance tests for patients admitted to a bone marrow transplant (BMT) unit or a solid tumor unit (STU) in a 565-bed tertiary hospital. We constructed a transmission model for estimating key parameters, including admission prevalence, transmission rate, and duration of colonization to understand the potential variation in C. difficile dynamics between these 2 units. RESULTS: A combined 2425 patients had 5491 admissions into 1 of the 2 units. A total of 3559 surveillance tests were collected from 1394 patients, with 11% of the surveillance tests being positive for C. difficile. We estimate that the transmission rate in the BMT unit was nearly 3-fold higher at 0.29 acquisitions per percentage colonized per 1000 days, compared to our estimate in the STU (0.10). Our model suggests that 20% of individuals admitted into either the STU or BMT unit were colonized with C. difficile at the time of admission. In contrast, the percentage of surveillance tests that were positive within 1 day of admission to either unit for C. difficile was 13.4%, with 15.4% in the STU and 11.6% in the BMT unit. CONCLUSIONS: Although prevalence was similar between the units, there were important differences in the rates of transmission and clearance. Influential factors may include antimicrobial exposure or other patient-care factors.
BACKGROUND: The key epidemiological drivers of Clostridioides difficile transmission are not well understood. We estimated epidemiological parameters to characterize variation in C. difficile transmission, while accounting for the imperfect nature of surveillance tests. METHODS: We conducted a retrospective analysis of C. difficile surveillance tests for patients admitted to a bone marrow transplant (BMT) unit or a solid tumor unit (STU) in a 565-bed tertiary hospital. We constructed a transmission model for estimating key parameters, including admission prevalence, transmission rate, and duration of colonization to understand the potential variation in C. difficile dynamics between these 2 units. RESULTS: A combined 2425 patients had 5491 admissions into 1 of the 2 units. A total of 3559 surveillance tests were collected from 1394 patients, with 11% of the surveillance tests being positive for C. difficile. We estimate that the transmission rate in the BMT unit was nearly 3-fold higher at 0.29 acquisitions per percentage colonized per 1000 days, compared to our estimate in the STU (0.10). Our model suggests that 20% of individuals admitted into either the STU or BMT unit were colonized with C. difficile at the time of admission. In contrast, the percentage of surveillance tests that were positive within 1 day of admission to either unit for C. difficile was 13.4%, with 15.4% in the STU and 11.6% in the BMT unit. CONCLUSIONS: Although prevalence was similar between the units, there were important differences in the rates of transmission and clearance. Influential factors may include antimicrobial exposure or other patient-care factors.
Authors: Preeta K Kutty; Susan E Beekmann; Ronda L Sinkowitz-Cochran; Erik R Dubberke; David T Kuhar; L Clifford McDonald; Philip M Polgreen Journal: Infect Control Hosp Epidemiol Date: 2019-05-20 Impact factor: 3.254
Authors: W Charles Huskins; Charmaine M Huckabee; Naomi P O'Grady; Patrick Murray; Heather Kopetskie; Louise Zimmer; Mary Ellen Walker; Ronda L Sinkowitz-Cochran; John A Jernigan; Matthew Samore; Dennis Wallace; Donald A Goldmann Journal: N Engl J Med Date: 2011-04-14 Impact factor: 91.245
Authors: Alun Thomas; Karim Khader; Andrew Redd; Molly Leecaster; Yue Zhang; Makoto Jones; Tom Greene; Matthew Samore Journal: Math Med Biol Date: 2018-03-16 Impact factor: 1.854
Authors: Manon R Haverkate; Lennie P G Derde; Christian Brun-Buisson; Marc J M Bonten; Martin C J Bootsma Journal: Intensive Care Med Date: 2014-02-13 Impact factor: 17.440