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Oral Abstract Session:
181. Challenges in C. difficile Infection Surveillance
Saturday: 10:30 a.m. - 12:00 p.m.
Room: SDCC 29 ABCD ERIK DUBBERKE, MD, MSPH; Washington University School of Medicine KAREN CARROLL, MD, FIDSA; John Hopkins University School of Medicine 1312 10:30 a.m. Risk Adjustment for Healthcare Facility-Onset C. difficile Infection and MRSA
Bacteremia Reporting in NHSN
MAGGIE DUDECK, MPH, CPH1, PAUL MALPIEDI, MPH2, JONATHAN EDWARDS, MSTAT1,
SCOTT FRIDKIN, MD1, L. CLIFFORD MCDONALD, MD1 and DAWN SIEVERT, PHD1;
1Centers for Disease Control and Prevention, Division of Healthcare Quality Promotion(DHQP), Atlanta, GA, 2Centers for Disease Control and Prevention, Division of Healthcare Quality Promotion, Atlanta, GA 1313 10:45 a.m. Defining "Nosocomial" – Differences in MDRO and C. difficile Rates Using 2-
Day vs. 3-Day Definitions
ADRIJANA GOMBOSEV, BS1, SALAH FOUAD, MS2, ERIC CUI, BS3, LEAH TERPSTRA, BA1,
DIANE KIM, BS3, HILDY MEYERS, MD MPH4, MICHELE CHEUNG, MD MPH4 and SUSAN S.
HUANG, MD, MPH, FIDSA3; 1University of California Irvine, School of Medicine, Irvine, CA,
2Saddleback Memorial Medical Center, Laguna Hil s, CA, 3University of California Irvine,Irvine, CA, 4Orange County Health Care Agency (OCHCA), Santa Ana, CA 1314 11:00 a.m. Evaluation of Differences in Population-Based Incidence of Clostridium difficile
Infection across Diverse U.S. Geographic Locations, 2010
FERNANDA LESSA, MD1, YI MU, PHD2, JESSICA COHEN, MPH1, GHINWA DUMYATI, MD,
FSHEA3, MONICA M. FARLEY, MD4, LISA WINSTON, MD5, KELLY KAST, MPH6, STACY
HOLZBAUER, DVM7, JAMES MEEK, MPH8, ZINTARS G. BELDAVS, MS9, L. CLIFFORD
MCDONALD, MD1, SCOTT FRIDKIN, MD1 and EIP CDI SURVEILLANCE INVESTIGATORS;
1Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention,Atlanta, GA, 2Centers for Disease Control and Prevention, Division of Healthcare QualityPromotion, Atlanta, GA, 3University of Rochester, Rochester, NY, 4Emory University Schoolof Medicine, Atlanta, GA, 5University of California, San Francisco/San Francisco GeneralHospital, San Francisco, CA, 6Colorado Department of Public Health and Environment,Denver, CO, 7CDC CEFO assigned to the MN Dept. of Hlth, St. Paul, MN, 8CT EIP, NewHaven, CT, 9Oregon Health Authority, Portland, OR 1315 11:15 a.m. Effect of Nucleic Acid Amplification Testing on Population-based Incident
Rates of Clostridium difficile Infection (CDI)
CAROLYN GOULD, MD1, JONATHAN EDWARDS, MSTAT1, JESSICA COHEN, MPH1, L.
CLIFFORD MCDONALD, MD1, MONICA M. FARLEY, MD2, HELEN JOHNSTON, MPH3, LUCY
WILSON, MD4, SAMIR HANNA, MD5, LISA WINSTON, MD6, STACY HOLZBAUER, DVM7,
CAROL LYONS, MPH8, ERIN PHIPPS, DVM9, GARY HOLLICK, PHD10, ZINTARS G. BELDAVS,
MS11, DALE GERDING, MD, FIDSA12, FERNANDA LESSA, MD1 and CDC'S CLOSTRIDIUM
DIFFICILE INFECTION SURVEILLANCE INVESTIGATORS; 1Centers for Disease Control and
Prevention, Atlanta, GA, 2Atlanta Veterans Medical Center, Atlanta, GA, 3Colorado
Department of Public Health and Environment, Denver, CO, 4Maryland Department of
Health and Mental Hygiene, Baltimore, MD, 5Tennessee Department of Health, Nashvil e,
TN, 6University of California, San Francisco/San Francisco General Hospital, San Francisco,
TN, University of California, San Francisco/San Francisco General Hospital, San Francisco,CA, 7CDC CEFO assigned to the Minnesota Department of Health, St. Paul, MN, 8Connecticut Emerging Infections Program, New Haven, CT, 9New Mexico EmergingInfections Program, Albuquerque, NM, 10University of Rochester Medical Center, Rochester,NY, 11Oregon Health Authority, Portland, OR, 12Edward Hines, Jr. Veterans Affairs Hospital, 1316 11:30 a.m. The Biology and Epidemiology of Clostridium difficile in Oxfordshire Hospitals
2007-2010
MADELEINE CULE, PHD1, RORY BOWDEN, PHD2, DAVID EYRE, BM, BCH3, A. SARAH
WALKER, PHD1, DAVID GRIFFITHS, BSC4, JOHN FINNEY1, DAVID WYLLIE, PHD1, DERRICK
CROOK, MB, BCH2, TIM PETO, MB BS, DPHIL2, PETER DONNELLY2 and INFECTIONS IN
OXFORDSHIRE RESEARCH DATABASE; 1NIHR Oxford Biomedical Research Centre, Oxford,
United Kingdom, 2University of Oxford, Oxford, United Kingdom, 3Nihr Oxford Biomedical
Research Centre, Oxford, United Kingdom, 4National Institute for Health Research Oxford
Biomedical Research Centre, Oxford, United Kingdom 1317 11:45 a.m. Prevalence and Risk Factors for Asymptomatic Clostridium difficile Carriage
ERIK DUBBERKE, MD, MSPH1, FAISAL ALASMARI, MD2, SONDRA SEILER, BA1, TIFFANY
HINK, BS3 and CAREY-ANN BURNHAM, PHD4; 1Washington University School of Medicine,
St. Louis, MO, 2Washington University School of Medicine, St.Louis, MO, 3Washington
University Schoold of Medicine, St Louis, MO, 4Washington University School of Medicine, St
Session #181 Presentations:
1312. Risk Adjustment for Healthcare Facility-Onset C. difficile Infection and
MRSA Bacteremia Reporting in NHSN
Part of Session: 181. Chal enges in C. difficile Infection Surveil ance MAGGIE DUDECK, MPH, CPH1, PAUL MALPIEDI, MPH2, JONATHAN EDWARDS, MSTAT1, SCOTT FRIDKIN, MD1, L. CLIFFORD
MCDONALD, MD1 and DAWN SIEVERT, PHD1; 1Centers for Dis eas e Control and Prevention, Divis ion of Healthcare Quality
Promotion (DHQP), Atlanta, GA, 2Centers for Dis eas e Control and Prevention, Divis ion of Healthcare Quality Promotion,
Atlanta, GA
Background: The Multidrug-Res is tant Organis m and Clos tridium difficile Infection (MDRO/CDI) Module was implemented in
the National Healthcare Safety Network (NHSN) in March 2009 to allow reporting of CDI, methicillin-res is tant Staphylococcus
aureus (MRSA), and other MDROs. State mandated reporting drove initial participation, but the Centers for Medicare andMedicaid Services will incentivize reporting of thes e two infections from acute care hos pitals beginning in 2013. The us e ofthes e data for inter-facility comparis ons and public reporting highlight the immediate need for adequate ris k adjus tmentmethods .
Methods: During 2010-2011, participating facilities reported all unique pos itive s pecimens (collected >14 days after a
previous pos itive s pecimen) for CDI and MRSA bacteremia (blood s pecimens ) to NHSN. Events were categorized as
community-ons et (CO, collected ≤3 days after admis s ion) or healthcare facility-ons et (HO, collected >3 days after
admis s ion). HO CDI and HO MRSA bacteremia incidence rates (per 10,000 and 1,000 patient-days , res pectively) were
calculated and compared by facility characteris tics to identify potential ris k adjus tment variables us ing negative binomial
tes ting.
Results: In 2010, 715 facilities from 28 s tates monitored CDI events in NHSN. A total of 20,803 HO CDI events were
reported from 5,757,846 admis s ions and 28,279,284 patient-days . CDI incidence rates differed s ignificantly by facility
teaching type, beds ize, tes t type, and CO prevalence (Table). MRSA bacteremia was monitored in 548 facilities from 29
s tates . A total of 1,078 HO MRSA bacteremia events were reported from 3,807,920 admis s ions and 17,427,005 patient-
days . MRSA bacteremia incidence rates differed s ignificantly by teaching type and beds ize.
Conclusion: Thes e facility characteris tics will be as s es s ed us ing multivariable analys is to determine ris k adjus tment for
the HO CDI and HO MRSA bacteremia Standardized Infection Ratios (SIRs ).
Findings in the abstracts are embargoed until 12:01 a.m. PST, Oct. 17th with the exception of research findings presented at the IDWeek press conferences.
1313. Defining "Nosocomial" – Differences in MDRO and C. difficile Rates Using
2-Day vs. 3-Day Definitions
Part of Session: 181. Chal enges in C. difficile Infection Surveil ance ADRIJANA GOMBOSEV, BS1, SALAH FOUAD, MS2, ERIC CUI, BS3, LEAH TERPSTRA, BA1, DIANE KIM, BS3, HILDY MEYERS, MD
MPH4, MICHELE CHEUNG, MD MPH4 and SUSAN S. HUANG, MD, MPH, FIDSA3; 1Univers ity of California Irvine, School of
Medicine, Irvine, CA, 2Saddleback Memorial Medical Center, Laguna Hills , CA, 3Univers ity of California Irvine, Irvine, CA,
4Orange County Health Care Agency (OCHCA), Santa Ana, CA
Background: The CDC's 48-hour nos ocomial definition is commonly implemented as a two or three-calendar day rule by
hos pitals . Our prior work in Orange County (OC), CA hos pitals found that one-third of hos pitals each us ed 48-hour, >2 day,
>3 day cas e definitions . We now as s es s the impact of definition choice on acquis ition and infection rates .
Methods: We conducted a pros pective s urvey of Infection Prevention Programs in OC hos pitals to as s es s the impact of
us ing a >2 day vs . >3 day definition for nos ocomial rates of MRSA, VRE, ESBL (Klebs iella and E. coli), and MDR
Acinetobacter acquisition, as well as MRSA bacteremia and C. difficile infection. Respondents provided monthly data usingboth definitions from January-December 2010. Total patient day denominators were retrieved from a mandatory s tatedis charge datas et. Differences in mean rates between the two nos ocomial definitions were as s es s ed us ing two-tailed t-tes ts .
Results: Nineteen of 31 countywide hos pitals participated, with a total of 1,062,242 patient days in 2010. Acros s
pathogens , we found that us e of the >3-day nos ocomial definition res ulted in acquis ition rates that were, on average, 17%
(range 9-24%) lower than us e of a >2-day definition.
Table. Percent Lost to Capture by using >3d vs. >2d Day Nosocomial Definitions
% Countywide
Paired t-test Events Lost by
Using >2d Definition Using >3d Definition
Using >3d vs.
MDR Acinetobacter C. difficile Infection *ESBL (Klebs iella and E. coli) combined; $Data from 18 hos pitals Conclusion: The common us e of a >3-day definition for reporting nos ocomial acquis ition and infections produces
s ignificantly lower rates than a >2-day definition. This difference could s ubs tantially impact hos pital rankings for public
reports bas ed upon differences in definitions alone. Thes e data s upport the CDC's decis ion to s tandardize nos ocomial
as s es s ment us ing a >2 calendar day rule in January 2013.
Findings in the abstracts are embargoed until 12:01 a.m. PST, Oct. 17th with the exception of research findings presented at the IDWeek press conferences.
1314. Evaluation of Differences in Population-Based Incidence of Clostridium
difficile Infection across Diverse U.S. Geographic Locations, 2010
Part of Session: 181. Chal enges in C. difficile Infection Surveil ance FERNANDA LESSA, MD1, YI MU, PHD2, JESSICA COHEN, MPH1, GHINWA DUMYATI, MD, FSHEA3, MONICA M. FARLEY, MD4,
LISA WINSTON, MD5, KELLY KAST, MPH6, STACY HOLZ BAUER, DVM7, JAMES MEEK, MPH8, Z INTARS G. BELDAVS, MS9, L.
CLIFFORD MCDONALD, MD1, SCOTT FRIDKIN, MD1 and EIP CDI SURVEILLANCE INVESTIGATORS; 1Divis ion of Healthcare Quality
Promotion, Centers for Dis eas e Control and Prevention, Atlanta, GA, 2Centers for Dis eas e Control and Prevention, Divis ion
of Healthcare Quality Promotion, Atlanta, GA, 3Univers ity of Roches ter, Roches ter, NY, 4Emory Univers ity School of
Medicine, Atlanta, GA, 5Univers ity of California, San Francis co/San Francis co General Hos pital, San Francis co, CA,
6Colorado Department of Public Health and Environment, Denver, CO, 7CDC CEFO assigned to the MN Dept. of Hlth, St.
Paul, MN, 8CT EIP, New Haven, CT, 9Oregon Health Authority, Portland, OR
Background: C. difficile infection (CDI) diagnos is and treatment are no longer res tricted to hos pital s ettings . Accurate
es timates of CDI nationally will require accounting for differences in population- and diagnos tic-s pecific factors (e.g., age,
tes ting practices ) that influence incidence meas ures . We analyzed population-bas ed data to identify thes e factors .
Methods: Population-bas ed s urveillance for pers ons ≥ 1 year of age was conducted in 21 counties in 7 U.S. s tates (8.5
million pop) in 2010. A CDI cas e was defined as a pos itive C. difficile toxin or molecular as s ay on a s tool s pecimen from a
pers on without a prior pos itive as s ay in the pas t 8 weeks . Cas es were clas s ified as community-as s ociated (CA) if s tool
was collected as an outpatient or ≤3 days of admis s ion in a pers on with no overnight s tay in a healthcare facility in the
was collected as an outpatient or ≤3 days of admis s ion in a pers on with no overnight s tay in a healthcare facility in thepas t 12 weeks ; otherwis e they were clas s ified as healthcare-as s ociated (HA). We queried participating laboratories aboutmolecular diagnos tics (e.g., PCR) utilization. The U.S .Cens us and Area Res ource File provided county-level demographicsand healthcare utilization data. Two regres s ion models (CA- and HA-CDI) were built to evaluate factors as s ociated withhigher CDI incidence. Site-s pecific incidence was calculated us ing 2010 U.S. Cens us and adjus ted bas ed on the regres s ionmodels .
Results: Of 10,062 cas es identified, 32% were CA. Overall CDI incidence per 100,000 was higher among pers ons who
were female (137 vs . 99; P=0.01), white (140 vs . 75; P<.001), or > 64 years (632 vs . 59; P<.001). Unadjus ted incidence
varied by s ite; CA-CDI ranged from 28–79/100,000 and HA-CDI ranged from 70–155/100,000. By multivariate analys is
independent predictors of higher CA-CDI incidence were age, race, s ex, and PCR us age; for HA-CDI only age was a
s tatis tically s ignificant predictor. After adjus ting for relevant factors , the range of incidence narrowed greatly; CA-CDI
ranged from 29–42/100,000 and HA-CDI ranged from 59–111/100,000 (Figure).
Conclusion: Differences in CDI incidence acros s s ites can be partially explained by differences in PCR us age, age, race
and gender, es pecially for CA-CDI cas es . Variation in antimicrobial us e and infection control practices , not captured in this
analys is , may contribute to the remaining differences in CDI incidence.
Findings in the abstracts are embargoed until 12:01 a.m. PST, Oct. 17th with the exception of research findings presented at the IDWeek press conferences.
1315. Effect of Nucleic Acid Amplification Testing on Population-based Incident
Rates of Clostridium difficile Infection (CDI)
Part of Session: 181. Chal enges in C. difficile Infection Surveil ance CAROLYN GOULD, MD1, JONATHAN EDWARDS, MSTAT1, JESSICA COHEN, MPH1, L. CLIFFORD MCDONALD, MD1, MONICA M.
FARLEY, MD2, HELEN JOHNSTON, MPH3, LUCY WILSON, MD4, SAMIR HANNA, MD5, LISA WINSTON, MD6, STACY HOLZ BAUER,
DVM7, CAROL LYONS, MPH8, ERIN PHIPPS, DVM9, GARY HOLLICK, PHD10, Z INTARS G. BELDAVS, MS11, DALE GERDING, MD,
FIDSA12, FERNANDA LESSA, MD1 and CDC'S CLOSTRIDIUM DIFFICILE INFECTION SURVEILLANCE INVESTIGATORS; 1Centers for
Dis eas e Control and Prevention, Atlanta, GA, 2Atlanta Veterans Medical Center, Atlanta, GA, 3Colorado Department of PublicHealth and Environment, Denver, CO, 4Maryland Department of Health and Mental Hygiene, Baltimore, MD, 5Tennes s eeDepartment of Health, Nas hville, TN, 6Univers ity of California, San Francis co/San Francis co General Hos pital, SanFrancis co, CA, 7CDC CEFO as s igned to the Minnes ota Department of Health, St. Paul, MN, 8Connecticut Emerging InfectionsProgram, New Haven, CT, 9New Mexico Emerging Infections Program, Albuquerque, NM, 10Univers ity of Roches ter MedicalCenter, Roches ter, NY, 11Oregon Health Authority, Portland, OR, 12Edward Hines , Jr. Veterans Affairs Hos pital, Hines , IL Nucleic acid amplification tes ts (NAATs ) targeting toxin genes of C. difficile have higher s ens itivity than enzymeimmunoas s ays (EIA) and are being adopted by clinical laboratories . The us e of NAAT is likely to increas e detection of CDI,but the magnitude of the increas es on incidence rates is unknown.
CDI cas e counts (cas e defined as a pos itive C. difficile s tool s pecimen by toxin or molecular as s ay from a res ident of thes urveillance catchment area without a prior pos itive as s ay in the pas t 8 weeks ) and laboratory tes ting methods frompopulation-bas ed s urveillance operating acros s 35 counties in 10 U.S. s tates during 2009-2011 were evaluated. Labs thatchanged from EIA to NAAT as firs t line tes ting ("s witch labs ") were compared to labs that only us ed EIA during theevaluation period ("non-s witch labs ") which s erved as controls . The median ratio of CDI cas e counts for s witch labs duringequivalent bimonthly time intervals pos t- and pre- s witch, to control for s eas onal variation, was compared to the medianratio for non-s witch labs (s ame catchment area, s ame time). A one-s ided non-parametric median tes t was us ed forcomparis on. The change in CDI incidence in each catchment area attributable to NAAT was calculated as the ratio of thes witch lab median ratio over the non-s witch lab median ratio, by EIP s ite. The proportions of s tools tes ted that were C.
difficile positive in the 3 months pre- and post- NAAT in switch labs were compared using a Mid-P exact test.
Five s witch labs from 3 s tates (CA, GA, CO) were compared to a total of 43 non-s witch labs . The number of monthsevaluated ranged from 14 to 24. The pos t/pre median ratios of cas e counts for s witch labs were greater than the medianratios for non-s witch labs in all s tates : CA: 1.78 vs . 1.0 (P=0.008); GA: 1.59 vs . 1.0 (P=0.01); CO: 1.87 vs . 0.99 (P=0.006),res pectively. The relative percent increas es in CDI incidence attributed to NAAT were 78% in CA, 59% in GA and 89% inCO. Percent of s pecimens tes ting pos itive increas ed from 8% to 19% (P<0.0001) in the 3 months after implementation ofNAAT.
We expect that labs s witching to NAAT will increas e population-bas ed incidence of CDI by 59%-89%. Analys is andinterpretation of CDI rates require adjus tment for more s ens itive tes ting methods . Findings in the abstracts are embargoed until 12:01 a.m. PST, Oct. 17th with the exception of research findings presented at the IDWeek press conferences.
1316. The Biology and Epidemiology of Clostridium difficile in Oxfordshire
Hospitals 2007-2010
Part of Session: 181. Chal enges in C. difficile Infection Surveil ance MADELEINE CULE, PHD1, RORY BOWDEN, PHD2, DAVID EYRE, BM, BCH3, A. SARAH WALKER, PHD1, DAVID GRIFFITHS, BSC4,
JOHN FINNEY1, DAVID WYLLIE, PHD1, DERRICK CROOK, MB, BCH2, TIM PETO, MB BS, DPHIL2, PETER DONNELLY2 and
INFECTIONS IN OXFORDSHIRE RESEARCH DATABASE; 1NIHR Oxford Biomedical Res earch Centre, Oxford, United Kingdom,
2University of Oxford, Oxford, United Kingdom, 3Nihr Oxford Biomedical Research Centre, Oxford, United Kingdom,
4National Institute for Health Research Oxford Biomedical Research Centre, Oxford, United Kingdom
Background: Clos tridium difficileis a major caus e of healthcare-as s ociated diarrhoea and controlling its s pread is the
focus of s ignificant public health effort. However, its biology and trans mis s ion epidemiology are incompletely unders tood.
Methods: Admis s ion records and ward movements for inpatient s tays in hos pitals in Oxfords hire were combined with
res ults of C. difficile EIA tes ting and culture between 1 September 2007 and 1 March 2010 (ca. 750,000 hos pital
admis s ions , 931 culture-pos itive patients ). C. difficile cas es were res olved into 70 dis tinct types us ing Multi-Locus
Sequence Typing. A s tochas tic compartmental model for trans mis s ion of C. difficile between hos pital contacts (EIA pos itive,
EIA negative and not tes ted), including potential trans mis s ion within and between wards , and ward contamination, was
fitted to the available data us ing Markov Chain Monte Carlo. Whole genome s equencing was us ed to validate inferences
from the model and confirmed it was well-calibrated.
Results: Us e of a probabilis tic modelling approach allows novel ins ights into the biology and epidemiology of C. difficile
infection. We s ee s trong evidence for heterogeneity between s trains , particularly that NAP1/ST1/Ribotype 027 is more
trans mis s ible, being res pons ible for 50% of trans mis s ions but only 13% of new introductions to the hos pital. We find that aminority (22%) of patients continue to trans mit for s everal months after initial diagnos is , and identify a potentiallys ignificant role for a median of 14 days (IQR 6-30 days ) pos t-ward-dis charge contamination leading to pos t-ward-dis chargetrans mis s ion. We find limited evidence for onward trans mis s ion prior to EIA tes t (likely ons et of s ymptoms ). We find noevidence for the exis tence of "s upers preader" patients (the larges t obs erved number of onward trans mis s ions is 6), andfind evidence for reductions in the amount of trans mis s ion over calendar time, and differences between the hos pitals inthe s tudy. We confirm earlier findings that the majority of C. difficile cas es cannot be explained by contact withs ymptomatic EIA-pos itive patients .
Conclusion: Trans mis s ion declined over time and varied by genotype. Statis tical modelling provides a us eful metric for
as s es s ing cas e-to-cas e trans mis s ion.
Findings in the abstracts are embargoed until 12:01 a.m. PST, Oct. 17th with the exception of research findings presented at the IDWeek press conferences.
1317. Prevalence and Risk Factors for Asymptomatic Clostridium difficile
Carriage
Part of Session: 181. Chal enges in C. difficile Infection Surveil ance ERIK DUBBERKE, MD, MSPH1, FAISAL ALASMARI, MD2, SONDRA SEILER, BA1, TIFFANY HINK, BS3 and CAREY-ANN BURNHAM,
PHD4; 1Was hington Univers ity School of Medicine, St. Louis , MO, 2Was hington Univers ity School of Medicine, St.Louis , MO,
3Washington University Schoold of Medicine, St Louis, MO, 4Washington University School of Medicine, St Louis, MO
Background: C. difficile infection (CDI) incidence has increas ed dramatically over the las t decade. Recent s tudies s ugges t
as ymptomatic carriers may be an important res ervoir of C. difficile (CD) in healthcare s ettings . We s ought to identify the
prevalence and ris k factors for as ymptomatic CD carriage on admis s ion to the hos pital.
Patients admitted to medical and s urgical wards at Barnes -Jewis h Hos pital (BJH) without diarrhea and anticipated length ofs tay of >48 hours were pros pectively enrolled from Jun 21, 2010, through Oct 25, 2011. Stool, or rectal s wabs werecollected within 48 hours of admit and s tored at -30C. Demographics , comorbidites , and healthcare and medicationexpos ures 90 days prior to admis s ion were collected. Specimens were heat s hocked at 80C for 10 min and inoculated intocyclos erine, cefoxitin, manitol broth with lys ozyme and taurocholate (Anaerobe Sys tems ). Growth was plated onto bloodagar. CD was identified by colony and Gram s tain morphology, and s tandard biochemical tes ts .CD is olates weres ubcultured in BHI, and culture s upernatant tes ted for GDH and toxins A and B (C. DIFF QUIK CHEK COMPLETE). Chi-s quare/Fis her's exact tes t was us ed for data analys is .
259 s ubjects had an admis s ion s tool/s wab s pecimen. 204 (79%) were not colonized, 40(16%) had toxigenic CD (TCD), and15(6%) had nontoxigenic CD. There were no differences between TCD colonized and uncolonized s ubjects for age (mean 56v 58, p=.46) or proportion that were admitted to the medicine s ervice (83% v 88%, p=.32), admitted from anotherhealthcare facility (33% v 24%, p=.23), or reas on for admis s ion (p=.45). There were no differences in any of 12comorbidities or pas t his tory of CDI (1% v 2%, p=.82). There were als o no differences in antibiotics expos ure in the 90days prior to admis s ion (55% v 56%, p= .91), or hos pitalization in the prior 90 days (50% v 50%, p=.43). 4(2%) TCDcolonized patients and 2(1%) uncolonized patients were diagnos ed with CDI (p=.07).
Conclusion: There was a high prevalence of TCD colonization on admis s ion to BJH. There were no as s ociations between
demographics or antibiotic or healthcare expos ures between colonized and uncolonized patients . As ymptomatic TCD
carriers may be an important s ource of TCD in acute care facilities .
Findings in the abstracts are embargoed until 12:01 a.m. PST, Oct. 17th with the exception of research findings presented at the IDWeek press conferences.

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