Clostridium difficile ribotype does not predict severe infection.

BACKGROUND: Studies of Clostridium difficile outbreaks suggested that certain ribotypes (eg, 027 and 078) cause more severe disease than other ribotypes. A growing number of studies challenge the validity of this hypothesis. METHODS: We conducted a cross-sectional study of C. difficile infection (CDI) to test whether ribotype predicted clinical severity when adjusted for the influence of other predictors. Toxigenic C. difficile isolates were cultured from stool samples, screened for genes encoding virulence factors by polymerase chain reaction (PCR) and ribotyped using high-throughput, fluorescent PCR ribotyping. We collected data for 15 covariates (microbiologic, epidemiologic, and laboratory variables) and determined their individual and cumulative influence on the association between C. difficile ribotype and severe disease. We then validated this influence using an independent data set. RESULTS: A total of 34 severe CDI cases were identified among 310 independent cases of disease (11.0%). Eleven covariates, including C. difficile ribotype, were significant predictors of severe CDI in unadjusted analysis. However, the association between ribotypes 027 and 078 and severe CDI was not significant after adjustment for any of the other covariates. After full adjustment, severe cases were significantly predicted only by patients' white blood cell count and albumin level. This result was supported by analysis of a validation data set containing 433 independent CDI cases (45 severe cases; 10.4%). CONCLUSIONS: Ribotype is not a significant predictor of severe CDI when adjusted for the influence of any other variables separately or in combination. White blood cell count and albumin level are the most clinically relevant predictors of severe CDI cases.

Microbiome data distinguish patients with Clostridium difficile infection and non-C. difficile-associated diarrhea from healthy controls.

Antibiotic usage is the most commonly cited risk factor for hospital-acquired Clostridium difficile infections (CDI). The increased risk is due to disruption of the indigenous microbiome and a subsequent decrease in colonization resistance by the perturbed bacterial community; however, the specific changes in the microbiome that lead to increased risk are poorly understood. We developed statistical models that incorporated microbiome data with clinical and demographic data to better understand why individuals develop CDI. The 16S rRNA genes were sequenced from the feces of 338 individuals, including cases, diarrheal controls, and nondiarrheal controls. We modeled CDI and diarrheal status using multiple clinical variables, including age, antibiotic use, antacid use, and other known risk factors using logit regression. This base model was compared to models that incorporated microbiome data, using diversity metrics, community types, or specific bacterial populations, to identify characteristics of the microbiome associated with CDI susceptibility or resistance. The addition of microbiome data significantly improved our ability to distinguish CDI status when comparing cases or diarrheal controls to nondiarrheal controls. However, only when we assigned samples to community types was it possible to differentiate cases from diarrheal controls. Several bacterial species within the Ruminococcaceae, Lachnospiraceae, Bacteroides, and Porphyromonadaceae were largely absent in cases and highly associated with nondiarrheal controls. The improved discriminatory ability of our microbiome-based models confirms the theory that factors affecting the microbiome influence CDI. IMPORTANCE The gut microbiome, composed of the trillions of bacteria residing in the gastrointestinal tract, is responsible for a number of critical functions within the host. These include digestion, immune system stimulation, and colonization resistance. The microbiome's role in colonization resistance, which is the ability to prevent and limit pathogen colonization and growth, is key for protection against Clostridium difficile infections. However, the bacteria that are important for colonization resistance have not yet been elucidated. Using statistical modeling techniques and different representations of the microbiome, we demonstrated that several community types and the loss of several bacterial populations, including Bacteroides, Lachnospiraceae, and Ruminococcaceae, are associated with CDI. Our results emphasize the importance of considering the microbiome in mediating colonization resistance and may also direct the design of future multispecies probiotic therapies.

The systemic inflammatory response to Clostridium difficile infection.

BACKGROUND: The systemic inflammatory response to Clostridium difficile infection (CDI) is incompletely defined, particularly for patients with severe disease. METHODS: Analysis of 315 blood samples from 78 inpatients with CDI (cases), 100 inpatients with diarrhea without CDI (inpatient controls), and 137 asymptomatic outpatient controls without CDI was performed. Serum or plasma was obtained from subjects at the time of CDI testing or shortly thereafter. Severe cases had intensive care unit admission, colectomy, or death due to CDI within 30 days after diagnosis. Thirty different circulating inflammatory mediators were quantified using an antibody-linked bead array. Principal component analysis (PCA), multivariate analysis of variance (MANOVA), and logistic regression were used for analysis. RESULTS: Based on MANOVA, cases had a significantly different inflammatory profile from outpatient controls but not from inpatient controls. In logistic regression, only chemokine (C-C motif) ligand 5 (CCL5) levels were associated with cases vs. inpatient controls. Several mediators were associated with cases vs. outpatient controls, especially hepatocyte growth factor, CCL5, and epithelial growth factor (inversely associated). Eight cases were severe and associated with elevations in IL-8, IL-6, and eotaxin. CONCLUSIONS: A broad systemic inflammatory response occurs during CDI and severe cases appear to differ from non-severe infections.

Poor functional status as a risk factor for severe Clostridium difficile infection in hospitalized older adults.

OBJECTIVES: To determine the role of impaired functional status as a risk factor for severe Clostridium difficile infection (CDI) in older adults. DESIGN: Prospective cohort study. SETTING: University of Michigan Health System, a 930-bed tertiary care hospital. PARTICIPANTS: Hospitalized individuals with CDI aged 50 and older. MEASUREMENTS: Demographic and clinical characteristics and a composite outcome, CDI severity score: fever (>38°C), acute organ dysfunction, white blood cell count greater than 15,000/µL, lack of response to therapy, intensive care unit admission, need for colectomy, or death from CDI. Preadmission functional status was assessed according to ability to perform activities of daily living (ADLs); participants were assigned to an ADL class (independent, some assistance, full assistance). Secondary outcomes included length of stay, 90-day mortality and readmission, and CDI recurrence. RESULTS: Ninety hospitalized individuals with CDI were identified (mean age 66.6 ± 10.2); 58 (64.4%) had severe CDI as measured according to a positive severity score. At baseline, 25 (27.8%) required assistance with ADLs. On univariate analysis, ADL class of full assistance was associated with a positive severity score (odds ratio (OR) = 7, 95% confidence interval (CI) = 1.83-26.79, P = .004). In a multivariable model including age, ADL class, congestive heart failure, diabetes mellitus, depression, weighted Charlson-Deyo comorbidity score, immunosuppression, prior CDI, and proton pump inhibitor use, an ADL class of full assistance retained its association with a positive severity score (OR = 8.1, 95% CI = 1.24-52.95, P = .03). ADL class was not associated with secondary outcomes. CONCLUSION: In this cohort of hospitalized older adults, impaired functional status was an independent risk factor for severe CDI.

Procalcitonin levels associate with severity of Clostridium difficile infection.

OBJECTIVE: Clostridium difficile infection (CDI) is a major cause of morbidity and biomarkers that predict severity of illness are needed. Procalcitonin (PCT), a serum biomarker with specificity for bacterial infections, has been little studied in CDI. We hypothesized that PCT associated with CDI severity. DESIGN: Serum PCT levels were measured for 69 cases of CDI. Chart review was performed to evaluate the presence of severity markers and concurrent acute bacterial infection (CABI). We defined the binary variables clinical score as having fever (T >38°C), acute organ dysfunction (AOD), and/or WBC >15,000 cells/mm(3) and expanded score, which included the clinical score plus the following: ICU admission, no response to therapy, colectomy, and/or death. RESULTS: In univariate analysis log10 PCT associated with clinical score (OR 3.13, 95% CI 1.69-5.81, P<.001) and expanded score (OR 3.33, 95% CI 1.77-6.23, P<.001). In a multivariable model including the covariates log10 PCT, enzyme immunoassay for toxin A/B, ribotype 027, age, weighted Charlson-Deyo comorbidity index, CABI, and extended care facility residence, log10 PCT associated with clinical score (OR 3.09, 95% CI 1.5-6.35, P = .002) and expanded score (OR 3.06, 95% CI 1.49-6.26, P = .002). PCT >0.2 ng/mL was 81% sensitive/73% specific for a positive clinical score and had a negative predictive value of 90%. CONCLUSION: An elevated PCT level associated with the presence of CDI severity markers and CDI was unlikely to be severe with a serum PCT level below 0.2 ng/mL. The extent to which PCT changes during CDI therapy or predicts recurrent CDI remains to be quantified.