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Comparison of Control of Clostridium Difficile Infection in Six English Hospitals Using Whole-Genome Sequencing

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Journal Clin Infect Dis
Date 2017 Jun 3
PMID 28575285
Citations 26
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Abstract

Background: Variation in Clostridium difficile infection (CDI) rates between healthcare institutions suggests overall incidence could be reduced if the lowest rates could be achieved more widely.

Methods: We used whole-genome sequencing (WGS) of consecutive C. difficile isolates from 6 English hospitals over 1 year (2013-14) to compare infection control performance. Fecal samples with a positive initial screen for C. difficile were sequenced. Within each hospital, we estimated the proportion of cases plausibly acquired from previous cases.

Results: Overall, 851/971 (87.6%) sequenced samples contained toxin genes, and 451 (46.4%) were fecal-toxin-positive. Of 652 potentially toxigenic isolates >90-days after the study started, 128 (20%, 95% confidence interval [CI] 17-23%) were genetically linked (within ≤2 single nucleotide polymorphisms) to a prior patient's isolate from the previous 90 days. Hospital 2 had the fewest linked isolates, 7/105 (7%, 3-13%), hospital 1, 9/70 (13%, 6-23%), and hospitals 3-6 had similar proportions of linked isolates (22-26%) (P ≤ .002 comparing hospital-2 vs 3-6). Results were similar adjusting for locally circulating ribotypes. Adjusting for hospital, ribotype-027 had the highest proportion of linked isolates (57%, 95% CI 29-81%). Fecal-toxin-positive and toxin-negative patients were similarly likely to be a potential transmission donor, OR = 1.01 (0.68-1.49). There was no association between the estimated proportion of linked cases and testing rates.

Conclusions: WGS can be used as a novel surveillance tool to identify varying rates of C. difficile transmission between institutions and therefore to allow targeted efforts to reduce CDI incidence.

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References
1.
Martin J, Badeaux J . Interpreting Laboratory Tests in Infection: Making Sense of Biomarkers in Sepsis and Systemic Inflammatory Response Syndrome for Intensive Care Unit Patients. Crit Care Nurs Clin North Am. 2017; 29(1):119-130. DOI: 10.1016/j.cnc.2016.09.004. View

2.
Eyre D, Griffiths D, Vaughan A, Golubchik T, Acharya M, OConnor L . Asymptomatic Clostridium difficile colonisation and onward transmission. PLoS One. 2013; 8(11):e78445. PMC: 3827041. DOI: 10.1371/journal.pone.0078445. View

3.
Noren T, Akerlund T, Back E, Sjoberg L, Persson I, Alriksson I . Molecular epidemiology of hospital-associated and community-acquired Clostridium difficile infection in a Swedish county. J Clin Microbiol. 2004; 42(8):3635-43. PMC: 497655. DOI: 10.1128/JCM.42.8.3635-3643.2004. View

4.
Walker A, Eyre D, Wyllie D, Dingle K, Harding R, OConnor L . Characterisation of Clostridium difficile hospital ward-based transmission using extensive epidemiological data and molecular typing. PLoS Med. 2012; 9(2):e1001172. PMC: 3274560. DOI: 10.1371/journal.pmed.1001172. View

5.
Zerbino D, Birney E . Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008; 18(5):821-9. PMC: 2336801. DOI: 10.1101/gr.074492.107. View