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Key Points Increased risk of SARS-CoV-2 infection was associated with community prevalence. Increased risk of SARS-CoV-2 infection was associated with exposure to infected family members and personal infection prevention measures

Simple parametric functional forms, if appropriate, are preferred over more complicated functional forms in clinical prediction models. In this paper, we illustrate our practical approach to obtaining the appropriate functional forms for continuous variables in developing a clinical prediction model for risk of Clostridium dicile infection. First, we used a nonpara- metric regression smoother to establish the reference curve. Then, we used regression spline function-restricted cubic spline (RCS) and simple para- metric forms to approximate the reference curve. Based on the shape of the reference curve, the model t information (AIC), and the formal statistical test (Vuong test), we selected the simple parametric forms to replace the more elaborated RCS functions. Finally, we rened the simple parametric forms in the multiple variable regression model using the Wald test and the likelihood-ratio test. In addition, we compared the calibration and discrim- ination aspects between the model with appropriate functional forms and the model with simple linear terms. The calibration 2 (8.4 versus 10) and calibration plot, the area under ROC curve (0.88 vs 0.84,p < 0:05), and inte- grated discrimination improvement (0.0072, p < 0:001) indicated the model with appropriate forms was better calibrated and had higher discrimination ability.

Objective:To assess potential transmission of antibiotic-resistant organisms (AROs) using surrogate markers and bacterial cultures.Design:Pilot study.Setting:A 1,260-bed tertiary-care academic medical center.Participants:The study included 25 patients (17 of whom were on contact precautions for AROs) and 77 healthcare personnel (HCP).Methods:Fluorescent powder (FP) and MS2 bacteriophage were applied in patient rooms. HCP visits to each room were observed for 2–4 hours; hand hygiene (HH) compliance was recorded. Surfaces inside and outside the room and HCP skin and clothing were assessed for fluorescence, and swabs were collected for MS2 detection by polymerase chain reaction (PCR) and selective bacterial cultures.Results:Transfer of FP was observed for 20 rooms (80%) and 26 HCP (34%). Transfer of MS2 was detected for 10 rooms (40%) and 15 HCP (19%). Bacterial cultures were positive for 1 room and 8 HCP (10%). Interactions with patients on contact precautions resulted in fewer FP detections than interactions with patients not on precautions (P < .001); MS2 detections did not differ by patient isolation status. Fluorescent powder detections did not differ by HCP type, but MS2 was recovered more frequently from physicians than from nurses (P = .03). Overall, HH compliance was better among HCP caring for patients on contact precautions than among HCP caring for patients not on precautions (P = .003), among nurses than among other nonphysician HCP at room entry (P = .002), and among nurses than among physicians at room exit (P = .03). Moreover, HCP who performed HH prior to assessment had fewer fluorescence detections (P = .008).Conclusions:Contact precautions were associated with greater HCP HH compliance and reduced detection of FP and MS2.

Background Hospitalized patients with diarrhea who have a negative Clostridoides difficile (C. difficile) test are not routinely evaluated for alternative causes of infectious diarrhea. This study assessed for potential infectious causes of diarrhea in hospitalized patients with an order for repeat C. difficile toxin enzyme immunoassay (tEIA) testing after an initial tEIA test was negative. Methods For patients age ≥18 years who had a second C. difficile tEIA test ordered within 96 h after a negative tEIA test, remnant fecal specimens from the first (negative) tEIA test were evaluated using the BioFire FilmArray Gastrointestinal Panel PCR, C. difficile toxigenic culture, and culture on a blood agar plate (BAP) to identify other potential causes of infectious diarrhea. Growth of organisms on the BAP was also used to assess potential disruptions in the gastrointestinal microbiota. Results Among 84 remnant specimens, toxigenic C. difficile was identified in 9 (11%) by culture or PCR, while potential alternative causes of infectious diarrhea, including norovirus, rotavirus, enteropathogenic Escherichia coli, and Salmonella, were identified in 11 specimens (13%) by PCR. For the majority of patients, no infectious cause of diarrhea was identified, but 84% exhibited disrupted gastrointestinal microbiota, which may contribute to diarrhea. Conclusions When a hospitalized patient has a negative C. difficile tEIA test but continues to have diarrhea, alternative infectious and noninfectious causes of diarrhea should be considered. If the patient has clinical signs and symptoms suggestive of infection or risk factors for gastrointestinal infection, laboratory testing for other etiologic agents may be appropriate.

Clostridioides difficile infection (CDI) imposes a substantial burden on the health care system in the United States. Understanding the biological basis for the spectrum of C. difficile-related disease manifestations is imperative to improving treatment and prevention of CDI. Here, we investigate the correlates of asymptomatic C. difficile colonization using a multi-omics approach, comparing the fecal microbiome and metabolome profiles of patients with CDI versus asymptomatically-colonized patients. We find that microbiomes of asymptomatic patients are significantly enriched for species in the class Clostridia relative to those of symptomatic patients. Asymptomatic patient microbiomes were enriched with fucose, rhamnose, and sucrose degradation pathways relative to CDI patient microbiomes. Fecal metabolomics corroborates this result: we identify carbohydrate compounds enriched in asymptomatic patients relative to CDI patients, and correlated with a number of commensal Clostridia. Further, we reveal that across C. difficile isolates, the carbohydrates rhamnose and lactulose do not serve as robust growth substrates in vitro, corroborating their enriched detection in our metagenomic and metabolite profiling of asymptomatic individuals. We conclude that in asymptomatically-colonized individuals, carbohydrate metabolism by other commensal Clostridia may prevent CDI by inhibiting C. difficile proliferation. These insights into C. difficile colonization and putative commensal competition suggest novel avenues to develop probiotic or prebiotic therapeutics against CDI.

Large-scale genomic studies have identified within-host adaptation as a hallmark of bacterial infections. However, the impact of physiological, metabolic, and immunological differences between distinct niches on the pathoadaptation of opportunistic pathogens remains elusive. Here, we profile the within-host adaptation and evolutionary trajectories of 976 isolates representing 119 lineages of uropathogenic Escherichia coli (UPEC) sampled longitudinally from both the gastrointestinal and urinary tracts of 123 patients with urinary tract infections. We show that lineages persisting in both niches within a patient exhibit increased allelic diversity. Habitat-specific selection results in niche-specific adaptive mutations and genes, putatively mediating fitness in either environment. Within-lineage inter-habitat genomic plasticity mediated by mobile genetic elements (MGEs) provides the opportunistic pathogen with a mechanism to adapt to the physiological conditions of either habitat, and reduced MGE richness is associated with recurrence in gut-adapted UPEC lineages. Collectively, our results establish niche-specific adaptation as a driver of UPEC within-host evolution.

PURPOSE OF REVIEW: Accurate and timely diagnosis of Clostridioides difficile infection (CDI) is imperative to prevent C. difficile transmission and reduce morbidity and mortality due to CDI, but CDI laboratory diagnostics are complex. The purpose of this article is to review the role of laboratory tests in the diagnosis of CDI, and the role of diagnostic stewardship in optimization of C. difficile testing. RECENT FINDINGS: Results from C. difficile diagnostic tests should be interpreted with an understanding of the strengths and limitations inherent in each testing approach. Use of highly sensitive molecular diagnostic tests without accounting for clinical signs and symptoms may lead to over-diagnosis of CDI and increased facility CDI rates. Current guidelines recommend a two-step, algorithmic approach for testing. Diagnostic stewardship interventions, such as education, order sets, order search menus, reflex orders, hard and soft stop alerts, electronic references, feedback and benchmarking, decision algorithms, and predictive analytics may help improve use of C. difficile laboratory tests and CDI diagnosis. The diagnostic stewardship approaches with the highest reported success rates include computerized clinical decision support (CCDS) interventions, face-to-face feedback, and real-time evaluations. SUMMARY: CDI is a clinical diagnosis supported by laboratory findings. Together, clinical evaluation combined with diagnostic stewardship can optimize the accurate diagnosis of CDI.

A gold standard diagnostic for Clostridioides difficile infection (CDI) does not exist. An area of controversy is how to manage patients whose stool tests positive by nucleic acid amplification tests but negative by toxin enzyme immunoassay., Clostridioides difficile infection (CDI) is most commonly diagnosed using nucleic acid amplification tests (NAAT); the low positive predictive value of these assays results in patients colonized with C. difficile unnecessarily receiving CDI treatment antibiotics. The risks and benefits of antibiotic treatment in individuals with such cases are unknown. Fecal samples of NAAT-positive, toxin enzyme immunoassay (EIA)-negative patients were collected before, during, and after randomization to vancomycin (n = 8) or placebo (n = 7). C. difficile and antibiotic-resistant organisms (AROs) were selectively cultured from fecal and environmental samples. Shotgun metagenomics and comparative isolate genomics were used to understand the impact of oral vancomycin on the microbiome and environmental contamination. Overall, 80% of placebo patients and 71% of vancomycin patients were colonized with C. difficile posttreatment. One person randomized to placebo subsequently received treatment for CDI. In the vancomycin-treated group, beta-diversity (P = 0.0059) and macrolide-lincosamide-streptogramin (MLS) resistance genes (P = 0.037) increased after treatment; C. difficile and vancomycin-resistant enterococci (VRE) environmental contamination was found in 53% of patients and 26% of patients, respectively. We found that vancomycin alters the gut microbiota, does not permanently clear C. difficile, and is associated with VRE colonization/environmental contamination. (This study has been registered at ClinicalTrials.gov under registration no. NCT03388268.) IMPORTANCE A gold standard diagnostic for Clostridioides difficile infection (CDI) does not exist. An area of controversy is how to manage patients whose stool tests positive by nucleic acid amplification tests but negative by toxin enzyme immunoassay. Existing data suggest most of these patients do not have CDI, but most are treated with oral vancomycin. Potential benefits to treatment include a decreased risk for adverse outcomes if the patient does have CDI and the potential to decrease C. difficile shedding/transmission. However, oral vancomycin perturbs the intestinal microbiota and promotes antibiotic-resistant organism colonization/transmission. We conducted a double-blinded randomized controlled trial to assess the risk-benefit of oral vancomycin treatment in this population. Oral vancomycin did not result in long-term clearance of C. difficile, perturbed the microbiota, and was associated with colonization/shedding of vancomycin-resistant enterococci. This work underscores the need to better understand this population of patients in the context of C. difficile/ARO-related outcomes and transmission.

Antibiotics are deployed against bacterial pathogens, but their targeting of conserved microbial processes means they also collaterally perturb the commensal microbiome. To understand acute and persistent effects of antibiotics on the gut microbiota of healthy adult volunteers, we quantify microbiome dynamics before, during, and 6 months after exposure to 4 commonly used antibiotic regimens. We observe an acute decrease in species richness and culturable bacteria after antibiotics, with most healthy adult microbiomes returning to pre-treatment species richness after 2 months, but with an altered taxonomy, resistome, and metabolic output, as well as an increased antibiotic resistance burden. Azithromycin delays the recovery of species richness, resulting in greater compositional distance. A subset of volunteers experience a persistent reduction in microbiome diversity after antibiotics and share compositional similarities with patients hospitalized in intensive care units. These results improve our quantitative understanding of the impact of antibiotics on commensal microbiome dynamics, resilience, and recovery.

Background. Intestinal microbiota restoration can be achieved by replacing a subject’s perturbed microbiota with that of a healthy donor. Recurrent Clostridioides difficile infection (rCDI) is one key application of such treatment. Another emerging application of interest is depletion of antibiotic resistant genes (ARGs) and organisms (AROs). In this study, we investigated fecal specimens from a multicenter, randomized, double-blind, placebo-controlled phase 2b study of microbiota-based investigational drug RBX2660. Patients were administered either placebo, 1 dose of RBX2660 and 1 placebo, or 2 doses of RBX2660 via enema and longitudinally tracked for changes in their microbiome and antibiotic resistome. Results. All patients exhibited significant recovery of gut microbiome diversity and a decrease of ARG abundance during the first 7 days post-treatment. However, the microbiome and resistome shifts towards healthier configurations were more significant and longer-lasting in RBX2660 recipients compared to placebo. We quantified microbiome and resistome modification by RBX2660 using a novel ‘transplantation index’ metric. We identified taxonomic and metabolic features distinguishing the baseline microbiome of non-transplanted patients and taxa specifically enriched during the process of transplantation. We elucidated the correlation between resistome and taxonomic transplantations and post-treatment dynamics of patient-specific and RBX2660-specific ARGs. Whole genome sequencing of AROs cultured from RBX2660 product and patient samples indicate ARO eradication in patients via RBX2660 administration, but also, to a lesser extent, introduction of RBX2660-derived AROs. Conclusions. Through shotgun metagenomic sequencing, we elucidated the effects of RBX2660 in the microbiome and resistome. Antibiotic discontinuation alone resulted in significant recovery of gut microbial diversity and reduced ARG abundance, but RBX2660 administration more rapidly and completely changed the composition of patients’ microbiome, resistome, and ARO colonization by transplanting RBX2660 microbiota into the recipients. Although ARGs and AROs were transmitted through RBX2660, the resistome post-RBX2660 more closely resembled that of the administered product—a proxy for the donor—than an antibiotic perturbed state.

Accurate and timely diagnosis of Clostridioides difficile infection (CDI) is imperative to prevent C. difficile transmission and reduce morbidity and mortality due to CDI, but CDI laboratory diagnostics are complex. The purpose of this article is to review the role of laboratory tests in the diagnosis of CDI and the role of diagnostic stewardship in optimization of C. difficile testing. Results from C. difficile diagnostic tests should be interpreted with an understanding of the strengths and limitations inherent in each testing approach. Use of highly sensitive molecular diagnostic tests without accounting for clinical signs and symptoms may lead to over-diagnosis of CDI and increased facility CDI rates. Current guidelines recommend a two-step, algorithmic approach for testing. Diagnostic stewardship interventions, such as education, order sets, order search menus, reflex orders, hard and soft stop alerts, electronic references, feedback and benchmarking, decision algorithms, and predictive analytics, may help improve use of C. difficile laboratory tests and CDI diagnosis. The diagnostic stewardship approaches with the highest reported success rates include computerized clinical decision support (CCDS) interventions, face-to-face feedback, and real-time evaluations. CDI is a clinical diagnosis supported by laboratory findings. Together, clinical evaluation combined with diagnostic stewardship can optimize the accurate diagnosis of CDI.

A 62-year-old woman received RBX2660, an investigational microbiome restoration therapeutic, for recurrent multidrug-resistant (MDR) urinary tract infection (UTI). RBX2660 increased gut microbiome diversity but did not eliminate uropathogen carriage, and MDR UTI recurred after subsequent antibiotic exposure. Thus, restoration of microbiome diversity does not preclude disease recurrence by residual MDR pathogens.

ObjectiveTo determine the prevalence of Clostridium difficile colonization among patients who meet the 2017 IDSA/SHEA C. difficile infection (CDI) Clinical Guideline Update criteria for the preferred patient population for C. difficile testing.DesignRetrospective cohort.SettingTertiary-care hospital in St. Louis, Missouri.PatientsPatients whose diarrheal stool samples were submitted to the hospital’s clinical microbiology laboratory for C. difficile testing (toxin EIA) from August 2014 to September 2016.InterventionsElectronic and manual chart review were used to determine whether patients tested for C. difficile toxin had clinically significant diarrhea and/or any alternate cause for diarrhea. Toxigenic C. difficile culture was performed on all stool specimens from patients with clinically significant diarrhea and no known alternate cause for their diarrhea.ResultsA total of 8,931 patients with stool specimens submitted were evaluated: 570 stool specimens were EIA positive (+) and 8,361 stool specimens were EIA negative (−). Among the EIA+stool specimens, 107 (19% of total) were deemed eligible for culture. Among the EIA− stool specimens, 515 (6%) were eligible for culture. One EIA+stool specimen (1%) was toxigenic culture negative. Among the EIA− stool specimens that underwent culture, toxigenic C. difficile was isolated from 63 (12%).ConclusionsMost patients tested for C. difficile do not have clinically significant diarrhea and/or potential alternate causes for diarrhea. The prevalence of toxigenic C. difficile colonization among EIA− patients who met the IDSA/SHEA CDI guideline criteria for preferred patient population for C. difficile testing was 12%.

OBJECTIVETo evaluate healthcare worker (HCW) risk of self-contamination when donning and doffing personal protective equipment (PPE) using fluorescence and MS2 bacteriophage.DESIGNProspective pilot study.SETTINGTertiary-care hospital.PARTICIPANTSA total of 36 HCWs were included in this study: 18 donned/doffed contact precaution (CP) PPE and 18 donned/doffed Ebola virus disease (EVD) PPE.INTERVENTIONSHCWs donned PPE according to standard protocols. Fluorescent liquid and MS2 bacteriophage were applied to HCWs. HCWs then doffed their PPE. After doffing, HCWs were scanned for fluorescence and swabbed for MS2. MS2 detection was performed using reverse transcriptase PCR. The donning and doffing processes were videotaped, and protocol deviations were recorded.RESULTSOverall, 27% of EVD PPE HCWs and 50% of CP PPE HCWs made ≥1 protocol deviation while donning, and 100% of EVD PPE HCWs and 67% of CP PPE HCWs made ≥1 protocol deviation while doffing (P=.02). The median number of doffing protocol deviations among EVD PPE HCWs was 4, versus 1 among CP PPE HCWs. Also, 15 EVD PPE protocol deviations were committed by doffing assistants and/or trained observers. Fluorescence was detected on 8 EVD PPE HCWs (44%) and 5 CP PPE HCWs (28%), most commonly on hands. MS2 was recovered from 2 EVD PPE HCWs (11%) and 3 CP PPE HCWs (17%).CONCLUSIONSProtocol deviations were common during both EVD and CP PPE doffing, and some deviations during EVD PPE doffing were committed by the HCW doffing assistant and/or the trained observer. Self-contamination was common. PPE donning/doffing are complex and deserve additional study.Infect Control Hosp Epidemiol 2017;38:1077–1083

The objective of this study was to evaluate the clinical characteristics and outcomes of hospitalized patients tested for Clostridium difficile and determine the correlation between pretest probability for C. difficile infection (CDI) and assay results. Patients with testing ordered for C. difficile were enrolled and assigned a high, medium, or low pretest probability of CDI based on clinical evaluation, laboratory, and imaging results. Stool was tested for C. difficile by toxin enzyme immunoassay (EIA) and toxigenic culture (TC). Chi-square analyses and the log rank test were utilized. Among the 111 patients enrolled, stool samples from nine were TC positive and four were EIA positive. Sixty-one (55%) patients had clinically significant diarrhea, 19 (17%) patients did not, and clinically significant diarrhea could not be determined for 31 (28%) patients. Seventy-two (65%) patients were assessed as having a low pretest probability of having CDI, 34 (31%) as having a medium probability, and 5 (5%) as having a high probability. None of the patients with low pretest probabilities had a positive EIA, but four were TC positive. None of the seven patients with a positive TC but a negative index EIA developed CDI within 30 days after the index test or died within 90 days after the index toxin EIA date. Pretest probability for CDI should be considered prior to ordering C. difficile testing and must be taken into account when interpreting test results. CDI is a clinical diagnosis supported by laboratory data, and the detection of toxigenic C. difficile in stool does not necessarily confirm the diagnosis of CDI.

Background: Antimicrobial exposure is a significant risk factor for the development of antibiotic-resistant organisms (ARO); however, the depth and duration of this impact is not well described. The study goal is to define impact of antibiotics on the gut microbiome of healthy volunteers (HVs). Methods: HVs were randomized to receive either 5 days of levofloxacin (LVX), azithromycin (AZM), cefpodoxime (CPD), or AZM + CPD (Fig. 1). Stool samples were collected at 15 time points per patient before, during, and after antibiotics. Remnant stool samples from the microbiology laboratory were collected from patients admitted to the medical intensive care unit (MICU) as a comparison of the microbiome in a critically ill state. DNA was extracted from samples and was submitted for shotgun sequencing. Relative abundance, resistome, and metabolic pathway abundance of bacterial taxa were determined and statistical analysis conducted in R software. Results: In total, 289 stool specimens from 20 HVs, and 26 remnant stool specimens were obtained from patients admitted from the MICU (Fig. 1). Community diversity and richness decreased in the first week post-ABX for all HVs (P < .01). Linear discriminant analysis identified Bacteroides and Clostridium as taxonomic groups enriched after CPD, while AZM and LVX produced a relative abundance increase in diverse Firmicutes spp. Longitudinal tracking confirmed that after all antibiotics except LVX, HV microbiomes lost species diversity and shifted toward a state similar to that observed in MICU patients (Fig. 2). The gut microbiome of most HVs exhibited resiliency and returned to a higher diversity level similar to their starting point; however, 10% of HVs did not. Moreover, antibiotic-specific increases in resistance markers reveal innate resistance to β-lactams and macrolides within the gut microbiome of the HVs. Finally, HV microbiomes, which shifted toward a MICU-like taxonomic state, also clustered with microbial metabolic profiles from MICU patients.The HV microbial metabolic profiles were significantly enriched for important biosynthesis pathways producing chorismate and polysaccharides. MICU patient gut microbiomes were enriched for fatty acid regulation and quinolone biosynthesis, and for many degradation pathways important for different aspects of antibiotic resistance such as membrane integrity, alternative respiration, and antibiotic inactivation. Conclusions: Short courses of antibiotics can cause acute and chronic microbiome disruptions in HVs, as evidenced by decreased microbiome diversity and increases in specific innate resistance elements. These data support the need for antimicrobial stewardship to support rationale antibiotic use to prevent gut microbiome disruptions.Funding: CDC BAA 200-2016-91962Disclosures: None

Clostridioides difficile infection (CDI) accounts for a substantial proportion of deaths attributable to antibiotic-resistant bacteria in the United States. Although C. difficile can be an asymptomatic colonizer, its pathogenic potential is most commonly manifested in patients with antibiotic-modified intestinal microbiomes. In a cohort of 186 hospitalized patients, we showed that host and microbe-associated shifts in fecal metabolomes had the potential to distinguish patients with CDI from those with non-C. difficile diarrhea and C. difficile colonization. Patients with CDI exhibited a chemical signature of Stickland amino acid fermentation that was distinct from those of uncolonized controls. This signature suggested that C. difficile preferentially catabolizes branched chain amino acids during CDI. Unexpectedly, we also identified a series of noncanonical, unsaturated bile acids that were depleted in patients with CDI. These bile acids may derive from an extended host-microbiome dehydroxylation network in uninfected patients. Bile acid composition and leucine fermentation defined a prototype metabolomic model with potential to distinguish clinical CDI from asymptomatic C. difficile colonization.

The spread of multidrug resistance among pathogenic organisms threatens the efficacy of antimicrobial treatment options. The human gut serves as a reservoir for many drug-resistant organisms and their resistance genes, and perturbation of the gut microbiome by antimicrobial exposure can open metabolic niches to resistant pathogens. Once established in the gut, antimicrobial-resistant bacteria can persist even after antimicrobial exposure ceases. Strategies to prevent multidrug-resistant organism (MDRO) infections are scarce, but autologous fecal microbiota transplantation (autoFMT) may limit gastrointestinal MDRO expansion. AutoFMT involves banking one’s feces during a healthy state for later use in restoring gut microbiota following perturbation. This pilot study evaluated the effect of amoxicillin-clavulanic acid (Amox-Clav) exposure and autoFMT on gastrointestinal microbiome taxonomic composition, resistance gene content, and metabolic capacity. Importantly, we found that metabolic capacity was perturbed even in cases where gross phylogeny remained unchanged and that autoFMT was safe and well tolerated., Strategies to prevent multidrug-resistant organism (MDRO) infections are scarce, but autologous fecal microbiota transplantation (autoFMT) may limit gastrointestinal MDRO expansion. AutoFMT involves banking one’s feces during a healthy state for later use in restoring gut microbiota following perturbation. This pilot study evaluated the effect of autoFMT on gastrointestinal microbiome taxonomic composition, resistance gene content, and metabolic capacity after exposure to amoxicillin-clavulanic acid (Amox-Clav). Ten healthy participants were enrolled. All received 5 days of Amox-Clav. Half were randomized to autoFMT, derived from stool collected pre-antimicrobial exposure, by enema, and half to saline enema. Participants submitted stool samples pre- and post-Amox-Clav and enema and during a 90-day follow-up period. Shotgun metagenomic sequencing revealed taxonomic composition, resistance gene content, and metabolic capacity. Amox-Clav significantly altered gut taxonomic composition in all participants (n = 10, P 0.05, compared to enrollment). Alterations to microbial metabolic capacity occurred following antimicrobial exposure even in participants without substantial taxonomic disruption, potentially creating open niches for pathogen colonization. Our findings suggest that metabolic potential is an important consideration for complete assessment of antimicrobial impact on the microbiome. AutoFMT was well tolerated and may have contributed to phylogenetic recovery. (This study has been registered at ClinicalTrials.gov under identifier NCT02046525.) IMPORTANCE The spread of multidrug resistance among pathogenic organisms threatens the efficacy of antimicrobial treatment options. The human gut serves as a reservoir for many drug-resistant organisms and their resistance genes, and perturbation of the gut microbiome by antimicrobial exposure can open metabolic niches to resistant pathogens. Once established in the gut, antimicrobial-resistant bacteria can persist even after antimicrobial exposure ceases. Strategies to prevent multidrug-resistant organism (MDRO) infections are scarce, but autologous fecal microbiota transplantation (autoFMT) may limit gastrointestinal MDRO expansion. AutoFMT involves banking one’s feces during a healthy state for later use in restoring gut microbiota following perturbation. This pilot study evaluated the effect of amoxicillin-clavulanic acid (Amox-Clav) exposure and autoFMT on gastrointestinal microbiome taxonomic composition, resistance gene content, and metabolic capacity. Importantly, we found that metabolic capacity was perturbed even in cases where gross phylogeny remained unchanged and that autoFMT was safe and well tolerated.

Background Multi-drug-resistant organisms (MDRO) have complicated the treatment of urinary tract infections (UTIs), especially in patients with recurrent UTIs (rUTI). The objective of this pilot prospective cohort study is to determine the role of the fecal microbiome in rUTIs. Methods Stool and urine specimens were prospectively collected from patients with MDRO UTIs at 6 time points during and after the UTI, and with any rUTI. Specimens underwent semi-quantitative culture on differential and selective media for MDROs, and isolates underwent phenotypic susceptibility testing and whole-genome sequencing. Comparative genomics and clonal tracking were used to detect clonal uropathogen strains in the urinary and gastrointestinal tracts. Resistance genes, resistance-plasmids, and virulence genes of MDROs were characterized in silico. Results A total of 110 isolates (95 Escherichia coli, 2 Klebsiella pneumoniae, 13 Proteus mirabilis) were cultured from the urine and stool of 15 patients (7 non-rUTI, 8 rUTI). Clonal uropathogens were isolated between the urinary tract and their intestinal reservoir (Figure 1). Integration of clonality information with semiquantitative culturing implicated three potential routes for recurrence of UTIs: (i) bladder colonization following an intestinal bloom of uropathogens, (ii) reinfection from an external source, and (III) bacterial persistence within the urinary tract (Figures 2 and 3). Antibiotic susceptibility testing and genomic profiling indicated that antibiotic-resistant uropathogen populations colonizing the urinary tract and intestinal reservoir at symptomatic and asymptomatic timepoints have similar resistance profiles that are largely determined via a pool of shared resistance plasmids (Figure 3). Conclusion This study provides the first time-resolved analysis of uropathogen persistence following UTIs, showing that clonal antibiotic-resistant uropathogens can be detected in both the urine and stool at varying time points post-initial infection. The study implicates 3 potential routes of rUTI, including uropathogen persistence within the gut microbiota, reinfection from an external source, and persistent bacteriuria. Study findings could be utilized to inform future diagnostics and therapies for treatment of rUTIs. Disclosures Carey-Ann Burnham, PhD, BioFire: Research Grant; bioMerieux: Research Grant; Cepheid: Research Grant; Luminex: Research Grant.

This prospective cohort study evaluated the presence of MRSA and VRE in the food of hospitalized patients. 149 patients were enrolled and 910 food specimens cultured; 3.2% were positive for MRSA and 2.4% positive for VRE, from a variety of food types.

Background Antibiotics (ABX) are frequently inappropriately used to treat nonbacterial causes of respiratory illnesses. The goal of this prospective cohort study was to characterize the impact of ABX used to treat community-acquired pneumonia (CAP) on the fecal microbiome and resistome in healthy volunteers (HV). Methods Twenty HVs were randomized to receive 5 days of levofloxacin (LV), azithromycin (AZ), cefpodoxime (CF), or AZ+CF. Stool was collected before, during, and after ABX, then underwent microbiologic culture and shotgun sequencing. DNA was extracted, then sequenced using the Illumina NextSeq platform. Relative abundance of bacterial taxa was estimated by MetaPhlAn and antibiotic resistance gene (ARG) composition by ShortBRED. Analysis was in R. Results The mean HV age was 37 (range 24–59) and 10 were female. Species diversity measured via Shannon Index and richness were significantly lower in samples taken from all HVs 3 days post-ABX (P < 0.01 for all). While nonmetric multidimensional scaling (NDMS) ordination shows high interpatient dissimilarity (Bray–Curtis) for most samples, the post-ABX intrapatient dissimilarity varies by ABX. The AZ group exhibited chronic alterations in taxa dissimilarity and the CF group had increases in dissimilarity directly post-ABX. The CF+AZ group displayed both acute and persistent perturbations (Figure 1). Although there was no significant change in ARG richness post-ABX, there was a significant increase in overall ARG abundance across all samples (P < 0.003). Within each ABX, there were unique changes in ARG abundance, and groups with CF had increases in ARG abundance (Figure 2). Conclusion ABX used to treat CAP can cause acute microbiome disruptions, as evidenced by decreased microbiome species diversity and richness, and an increase in ARG abundance post-ABX. The duration of this impact is variable. To prevent microbiome disruptions, measures to prevent inappropriate ABX use via ABX stewardship are necessary. Disclosures E. R. Dubberke, Rebiotix: Consultant and Investigator, Consulting fee and Research support. Pfizer: Consultant and Grant Investigator, Consulting fee and Research grant. Synthetic biologics: Consultant, Consulting fee. Merck: Consultant and Investigator, Consulting fee and Research support. Valneva: Consultant, Consulting fee. Achaogen: Consultant, Consulting fee. Alere: webinar, Speaker honorarium. Biofire: webinar, Speaker honorarium.

Background MDRO present a greater threat to public health than ever before, and antimicrobial options are decreasing. Altered colonic microbiota following antimicrobial exposure allows for subsequent colonization by MDRO. Ingestion of prophylactic Lactobacillus rhamnosus GG (LGG) could be an approach to prevent the spread of, and subsequent infection due to MDRO, by promoting a healthy bacterial milieu within the colon. Methods This is a prospective, double-blinded, randomized clinical trial in which a total of 87 subjects on broad-spectrum antibiotics were randomized to receive LGG twice daily (n = 43) vs placebo (n = 44). Stool or rectal swab specimens were collected for culture at enrollment, every 3 days during admission, and at discharge. Selective media were used to detect the following MDRO: Clostridioides difficile (CD), vancomycin-resistant Enterococcus (VRE), and antibiotic-resistant Gram-negatives (GN). The primary outcome was MDRO acquisition. Secondary outcomes included analysis for loss of any MDRO if colonized at enrollment, and acquisition or loss of individual MDRO. Results Subjects in both groups had similar prevalence of colonization with any MDRO at study enrollment (LGG 40% vs. placebo 39%), with similar colonization prevalence for individual MDRO (Figure 1). There was no difference in any MDRO acquisition (LGG 27%, placebo 33%, OR 1.36, 95% CI 0.42–4.41) or any individual MDRO acquisition (Figure 2). There was also no difference in loss of any MDRO (LGG 18%, placebo 24%, OR 1.44, 95% CI 0.27–7.68) or any individual MDRO (Figure 2). Conclusion LGG administration did not prevent acquisition of MDRO or accelerate loss of MDRO colonization. Disclosures All authors: No reported disclosures.

Background Clostridium difficile infection (CDI) is a frequent cause of diarrhea among allogeneic hematopoietic cell transplant (HCT) recipients. It is unknown whether risk factors for CDI vary by time posttransplant. Methods We performed a 3-year prospective cohort study of CDI in allogeneic HCT recipients. Participants were enrolled during their transplant hospitalizations. Clinical assessments were performed weekly during hospitalizations and for 12 weeks posttransplant, and monthly for 30 months thereafter. Data were collected through patient interviews and chart review, and included CDI diagnosis, demographics, transplant characteristics, medications, infections, and outcomes. CDI cases were included if they occurred within 1 year of HCT and were stratified by time from transplant. Multivariable logistic regression was used to determine risk factors for CDI. Results One hundred eighty-seven allogeneic HCT recipients were enrolled, including 63 (34%) patients who developed CDI. 38 (60%) CDI cases occurred during the preengraftment period (days 0-30 post-HCT) and 25 (40%) postengraftment (day >30). Lack of any preexisting comorbid disease was significantly associated with lower risk of CDI preengraftment (odds ratio [OR], 0.3; 95% confidence interval [CI], 0.1-0.9). Relapsed underlying disease (OR, 6.7; 95% CI, 1.3-33.1), receipt of any high-risk antimicrobials (OR, 11.8; 95% CI, 2.9-47.8), and graft-versus-host disease (OR, 7.8; 95% CI, 2.0-30.2) were significant independent risk factors for CDI postengraftment. Conclusions A large portion of CDI cases occurred during the postengraftment period in allogeneic HCT recipients, suggesting that surveillance for CDI should continue beyond the transplant hospitalization and preengraftment period. Patients with continued high underlying severity of illness were at increased risk of CDI postengraftment.

OBJECTIVETo determine whetherClostridium difficileis present in the food of hospitalized patients and to estimate the risk of subsequent colonization associated withC. difficilein food.METHODSThis was a prospective cohort study of inpatients at a university-affiliated tertiary care center, May 9, 2011–July 12, 2012. Enrolled patients submitted a portion of food from each meal. Patient stool specimens and/or rectal swabs were collected at enrollment, every 3 days thereafter, and at discharge, and were cultured forC. difficile. Clinical data were reviewed for evidence of infection due toC. difficile.A stochastic, discrete event model was developed to predict exposure toC. difficilefrom food, and the estimated number of new colonization events from food exposures per 1,000 admissions was determined.RESULTSA total of 149 patients were enrolled and 910 food specimens were obtained. Two food specimens from 2 patients were positive forC. difficile(0.2% of food samples; 1.3% of patients). Neither of the 2 patients was colonized at baseline withC. difficile. Discharge colonization status was available for 1 of the 2 patients and was negative. Neither was diagnosed withC. difficileinfection while hospitalized or during the year before or after study enrollment. Stochastic modeling indicated contaminated hospital food would be responsible for less than 1 newly colonized patient per 1,000 hospital admissions.CONCLUSIONSThe recovery ofC. difficilefrom the food of hospitalized patients was rare. Modeling suggests hospital food is unlikely to be a source ofC. difficileacquisition.Infect Control Hosp Epidemiol2016;1401–1407

The incidence and severity of Clostridium difficile infection (CDI) have been increasing in recent years [1–7], but national surveillance efforts and interhospital comparisons have been limited by the lack of a standard CDI surveillance system. As a result, the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) codes assigned at hospital discharge have been used as a proxy to estimate CDI prevalence in the United States [8–12]. Using administrative data (ICD-9-CM codes) to compare CDI rates between hospitals has several potential advantages. Administrative discharge data are inexpensive to obtain, are systematically collected, and utilize a single ICD-9-CM code to designate CDI (008.45), thus potentially providing a nationally representative method for tracking CDI rates [8, 13, 14]. Two administrative databases have been used to estimate CDI prevalence in the United States: the National Hospital Discharge Survey (NHDS) and the Nationwide Inpatient Sample (NIS). ICD-9-CM code data are collected differently in each database; neither data set collects all potential ICD-9-CM codes assigned at hospital discharge. The NHDS is collected annually by the National Center for Health Statistics at the Centers for Disease Control and Prevention (CDC), and about 90% of a panel of 500 hospitals participate [8]. The NIS, on the other hand, is collected from all states that participate in the Healthcare Cost and Utilization Project and includes information from about 1000 US hospitals [15]. The NHDS collects up to the first 7 ICD-9-CM codes assigned per patient, and the NIS collects up to the first 9–15 codes assigned per patient (the number of codes captured varies by state). Despite their advantages, a recent study suggests that ICD-9-CM codes may not be acceptable for hospital-onset CDI surveillance. A multicenter study performed at the CDC Prevention Epicenters hospitals compared the incidences of hospital-onset CDI as measured by ICD-9-CM codes with toxin assay results. ICD-9-CM codes overestimated the incidence of hospital-onset CDI, compared with toxin assay results, indicating that ICD-9-CM codes are not an acceptable surrogate for hospital-onset CDI surveillance [16]. The degree to which ICD-9-CM codes overreported the incidence of hospital-onset CDI varied by year and by hospital, indicating that ICD-9-CM codes would not have been useful for intrahospital or interhospital CDI surveillance. No previously published CDI prevalence study using ICD-9-CM codes has differentiated between the NHDS and NIS criteria. The data collection discrepancies between these 2 data sets may account for the conflicting results of previous studies of CDI prevalence. It is not known how the differences in the number of ICD-9-CM codes available for prevalence estimation affect the estimated CDI prevalence and how CDI burden estimates based on ICD-9-CM codes compare with toxin assay results. Therefore, we investigated how the NHDS and NIS criteria affect CDI prevalence and how these definitions compare with toxin assay results at multiple healthcare facilities during a 6-year study period.

Objective.To develop and validate a risk prediction model that could identify patients at high risk for Clostridium difficile infection (CDI) before they develop disease.Design and Setting.Retrospective cohort study in a tertiary care medical center.Patients.Patients admitted to the hospital for at least 48 hours during the calendar year 2003.Methods.Data were collected electronically from the hospital's Medical Informatics database and analyzed with logistic regression to determine variables that best predicted patients' risk for development of CDI. Model discrimination and calibration were calculated. The model was bootstrapped 500 times to validate the predictive accuracy. A receiver operating characteristic curve was calculated to evaluate potential risk cutoffs.Results.A total of 35,350 admitted patients, including 329 with CDI, were studied. Variables in the risk prediction model were age, CDI pressure, times admitted to hospital in the previous 60 days, modified Acute Physiology Score, days of treatment with high-risk antibiotics, whether albumin level was low, admission to an intensive care unit, and receipt of laxatives, gastric acid suppressors, or antimotility drugs. The calibration and discrimination of the model were very good to excellent (C index, 0.88; Brier score, 0.009).Conclusions.The CDI risk prediction model performed well. Further study is needed to determine whether it could be used in a clinical setting to prevent CDI-associated outcomes and reduce costs.

Background Clostridium difficile infection (CDI) is a common complication of lung and allogeneic hematopoietic cell (HCT) transplant, but the epidemiology and outcomes of CDI after transplant are poorly described. Methods We performed a prospective, multicenter study of CDI within 365 days post-allogeneic HCT or lung transplantation. Data were collected via patient interviews and medical chart review. Participants were followed weekly in the 12 weeks post-transplant and while hospitalized and contacted monthly up to 18 months post-transplantation. Results Six sites participated in the study with 614 total participants; 4 enrolled allogeneic HCT (385 participants) and 5 enrolled lung transplant recipients (229 participants). One hundred and fifty CDI cases occurred within 1 year of transplantation; the incidence among lung transplant recipients was 13.1% and among allogeneic HCTs was 31.2%. Median time to CDI was significantly shorter among allogeneic HCT than lung transplant recipients (27 days vs 90 days; P = .037). CDI was associated with significantly higher mortality from 31 to 180 days post-index date among the allogeneic HCT recipients (Hazard ratio [HR] = 1.80; P = .007). There was a trend towards increased mortality among lung transplant recipients from 120 to 180 days post-index date (HR = 4.7, P = .09). Conclusions The epidemiology and outcomes of CDI vary by transplant population; surveillance for CDI should continue beyond the immediate post-transplant period.

Objective.To describe a pseudo-outbreak ofClostridium difficileinfection (CDI) caused by a faulty toxin assay lot and to determine the effect of sensitivity, specificity, and repeated testing forC. difficileon perceived CDI burden, positive predictive value, and false-positive results.Design.Outbreak investigation and criterion standard.Patients.Patients hospitalized at a tertiary care hospital who had at least 1 toxin assay for detection ofC. difficileperformed during the period from July 1, 2004, through June 30, 2006.Methods.The run control chart method and thex2test were used to compare CDI rates and the proportion of positive test results before, during, and after the pseudo-outbreak. The effect of repeated testing was evaluated by using 3 hypothetical models with a sample of 10,000 patients and various assay sensitivity and specificity estimates.Results.In November of 2005, the CDI rate at the hospital increased from 1.5 to 2.6 cases per 1,000 patient-days (P< .01), and the proportion of positive test results increased from 13.6% to 22.1% (P< .01). An investigation revealed a pseudo-outbreak caused by a faulty toxin assay lot. A decrease of only 1.2% in the specificity of the toxin assay would result in a 32% increase in perceived incidence of CDI at this institution. When calculated by use of the manufacturer's stated specificity and sensitivity and this institution's testing practices, the positive predictive value of the test decreased from 80.6% to 4.1% for patients who received 3 tests.Conclusion.Specificity is as important as sensitivity when testing for CDI. False-positive CDI cases can drain hospital resources and adversely affect patients. Repeated testing forC. difficileshould be performed with caution.

Objectives.To compare Clostridium difficile infection (CDI) rates determined with use of a traditional definition (ie, with healthcare-onset CDI defined as diagnosis of CDI more than 48 hours after hospital admission) with rates determined with use of expanded definitions, including both healthcare-onset CDI and community-onset CDI, diagnosed within 48 hours after hospital admission in patients who were hospitalized in the previous 30 or 60 days, and to determine whether differences exist between patients with CDI onset in the community and those with CDI onset in a healthcare setting.Design.Prospective cohortSetting.Tertiary acute care facility.Patients.General medicine patients who received a diagnosis of CDI during the period January 1, 2004, through December 31, 2005.Methods.CDI was classified as healthcare-onset CDI, healthcare facility–associated CDI after hospitalization within the previous 30 days, and/or healthcare facility-associated CDI after hospitalization within the previous 60 days. Patient demographic characteristics and medication exposures were obtained. The CDI incidence with use of each definition, CDI rate variability, patient demographic characteristics, and medication exposures were compared.Results.The healthcare-onset CDI rate (1.6 cases per 1,000 patient-days) was significantly lower than the 30-day healthcare facility–associated CDI rate (2.4 cases per 1,000 patient-days; PPPPP = .02) or intravenous vancomycin (P = .01) during hospitalization.Conclusions.Compared with the traditional definition, expanded definitions identify more patients with CDI. There is good correlation between traditional and expanded CDI definitions; therefore, it is unclear whether expanded surveillance is necessary to identify an abnormal change in CDI rates. Cases that met the expanded definitions were less likely to have occurred in patients with fourth-generation cephalosporin and vancomycin exposure.

CDAD led to significantly worse outcomes in these patients., Data are limited on the attributable outcomes of Clostridium difficile–associated disease (CDAD), particularly in CDAD-endemic settings. We conducted a retrospective cohort study of nonsurgical inpatients admitted for >48 hours in 2003 (N = 18,050). The adjusted hazard ratios for readmission (hazard ratio 2.19, 95% confidence interval [CI] 1.87–2.55) and deaths within 180 days (hazard ratio 1.23, 95% CI 1.03–1.46) were significantly different among CDAD case-patients and noncase patients. In a propensity score matched-pairs analysis that used a nested subset of the cohort (N = 706), attributable length of stay attributable to CDAD was 2.8 days, attributable readmission at 180 days was 19.3%, and attributable death at 180 days was 5.7%. CDAD patients were significantly more likely than controls to be discharged to a long-term-care facility or outside hospital. Even in a nonoutbreak setting, CDAD had a statistically significant negative impact on patient illness and death, and the impact of CDAD persisted beyond hospital discharge.