A Multi-Center Prospective Derivation and Validation of a Clinical Prediction Tool for Severe Clostridium difficile Infection

Predicting Clostridioides difficile infection outcomes with explainable machine learning

BACKGROUND

Clostridioides difficile infection results in life-threatening short-term outcomes and the potential for subsequent recurrent infection. Predicting these outcomes at diagnosis, when important clinical decisions need to be made, has proven to be a difficult task.

METHODS

52 clinical features from existing models or the literature were collected retrospectively within ±48 h of diagnosis among 1660 inpatient infections. A modified desirability of outcome ranking (DOOR) was designed to encompass clinically-important severe events attributable to the acute infection (intensive care transfer due to sepsis, shock, colectomy/ileostomy, mortality) and/or 60-day recurrence. A deep neural network was constructed and interpreted using SHapley Additive exPlanations (SHAP). High-importance features were used to train a reduced, shallow network and performance was compared to existing conventional models (7 severity, 7 recurrence; after summing DOOR probabilities to align with conventional binary outputs) using area under the ROC curve (AUROC) and DeLong tests.

FINDINGS

The full (52-feature) model achieved an out-of-sample AUROC 0.823 for severity and 0.678 for recurrence. SHAP identified 13 unique, highly-important features (age, hypotension, initial treatment, onset, PCR cycle threshold, number of prior episodes, antibiotic exposure, fever, hypotension, pressors, leukocytosis, creatinine, lactate) that were used to train a reduced model, which performed similarly to the full model (severity AUROC difference P = 0.130; recurrence P = 0.426) and significantly better than the top severity model (reduced model predicting severity 0.837, ATLAS 0.749; P = 0.001). The reduced model also outperformed the top recurrence model, but this was not statistically-significant (reduced model recurrence AUROC 0.653, IDSA Recurrence Risk Criteria 0.595; P = 0.196). The final, reduced model was deployed as a web application with real-time SHAP explanations.

INTERPRETATION

Our final model outperformed existing severity and recurrence models; however, it requires external validation. A DOOR output allows specific clinical questions to be asked with explainable predictions that can be feasibly implemented with limited computing resources.

FUNDING

National Institutes of Health-Institute of Allergy and Infectious Diseases.

Clinical Characteristics and Risk Factors for Clostridioides difficile Infection in the Hematopoietic Cell Transplantation Population

Background

Hematopoietic cell transplantation (HCT) recipients are at increased risk of developing primary and recurrent Clostridioides difficile infection (CDI). The objective of our study was to characterize the risk factors for primary and recurrent CDI in a large cohort of patients hospitalized for HCT.

Methods

We conducted a retrospective cohort study of adults who underwent HCT from 2010-2023 to analyze the epidemiology, timing, and risk factors for CDI. We compared patients who developed CDI with those who did not, controlling for patient demographics, comorbidities, transplant factors, medications, and laboratory values.

Results

Of the 2,725 adults who underwent HCT, 252 (9.3%) developed primary CDI within one-year of transplantation. The incidence was higher among allogenic HCT recipients (17.8%) compared to autologous recipients (4.1%). Independent risk factors for primary CDI included receipt of penicillin antibiotics, prior chemotherapy, and umbilical cord stem cells. Receipt of macrolide antibiotics was an independent risk factor for recurrent CDI, while receipt of autologous HCT was associated with a reduced risk of both primary and recurrent CDI.

Conclusions

CDI presents an early complication after HCT, particularly in allogenic recipients who experience higher incidence rates and severe complications. Early recognition and management of these risk factors are essential to prevent these adverse outcomes.

Generalizability of predictive models for Clostridioides difficile infection, severity and recurrence at an urban safety-net hospital

INTRODUCTION

Predictive models for Clostridioides difficile infection can identify high-risk patients and aid clinicians in preventing infection. Issues of generalizability regarding current predictive models have been acknowledged but, to the authors' knowledge, have never been quantified.

METHODS

C. difficile infection, severity and recurrence predictive models were created using multi-variate logistic regression through case-control sampling from an urban safety-net hospital. Models were validated using five-fold cross-validation, and inverse probability weights (IPW) based on two different catchment area definitions were used to improve external validity. Akaike Information Criterion (AIC), area under the receiver operating characteristic curve (AUROC), and sensitivity and specificity with bootstrapped confidence intervals (CI) were used to assess and compare model fit and performance.

RESULTS

Changes in performance before and after weighting were small across all models, although differences were more apparent after weighting the recurrence model (AUROC values of 0.78, 0.76 and 0.71 for the unweighted and two weighted models, respectively). Overall, the infection model performed the best (AUROC 0.82, 95% CI 0.78-0.85), followed by the recurrence model (AUROC 0.78, 95% CI 0.69-0.86) and then the severity model (AUROC 0.70, 95% CI 0.63-0.78).

CONCLUSIONS

The performance of the models after weighting did not change drastically, suggesting that the models predicting C. difficile infection, severity and recurrence may not be impacted by patient selection factors. However, other researchers may wish to consider addressing these catchment forces using IPW.

An integrated pipeline for prediction of Clostridioides difficile infection

With the expansion of electronic health records(EHR)-linked genomic data comes the development of machine learning-enable models. There is a pressing need to develop robust pipelines to evaluate the performance of integrated models and minimize systemic bias. We developed a prediction model of symptomatic Clostridioides difficile infection(CDI) by integrating common EHR-based and genetic risk factors(rs2227306/IL8). Our pipeline includes (1) leveraging phenotyping algorithm to minimize temporal bias, (2) performing simulation studies to determine the predictive power in samples without genetic information, (3) propensity score matching to control for the confoundings, (4) selecting machine learning algorithms to capture complex feature interactions, (5) performing oversampling to address data imbalance, and (6) optimizing models and ensuring proper bias-variance trade-off. We evaluate the performance of prediction models of CDI when including common clinical risk factors and the benefit of incorporating genetic feature(s) into the models. We emphasize the importance of building a robust integrated pipeline to avoid systemic bias and thoroughly evaluating genetic features when integrated into the prediction models in the general population and subgroups.

Clostridioides difficile PCR Tcdb Cycle Threshold predicts toxin EIA positivity but not severity of infection

BACKGROUND

Diagnosis of Clostridioides difficile Infection (CDI) entails compatible clinical presentation and laboratory findings. We evaluated real-time polymerase chain reaction (qPCR) cycle threshold (CT) as a predictor for disease severity and TcdB enzyme immunoassay (EIA) results.

METHODS

Inpatients or emergency department patients who tested positive for tcdB gene by PCR were evaluated. Patients' stools underwent testing for GDH and TcdA/B by EIA. Medical health records were reviewed for demographic, clinical presentation, laboratory, treatment and outcome data. Severity of CDI was calculated using various severity score indexes.

RESULTS

The median CT of cases was 32.05 ± 5.45. The optimal cut-off for predicting toxin EIA positivity and severe CDI based on chart review was 32.6 and 29.8, respectively, with the area under the receiver operator characteristics curve (AUC) of 0.74 and 0.60 respectively.

CONCLUSION

CT value was an acceptable predictor for EIA toxin but less so for clinical severity. Our study potentially supports a diagnostic algorithm including CT value to reduce the number of EIA toxin assays performed.

Clostridioides difficile Infection: Clinical Practice and Health Outcomes in 6 Large Tertiary Hospitals in Eastern Australia

Background

Clostridioides difficile infection (CDI) is associated with significant morbidity and mortality in both healthcare and community settings. We aimed to define the predisposing factors, risks for severe disease, and mortality determinants of CDI in eastern Australia over a 1-year period.

Methods

This is an observational retrospective study of CDI in hospitalized patients aged ≥18 years in 6 tertiary institutions from 1 January 2016 to 31 December 2016. Patients were identified through laboratory databases and medical records of participating institutions. Clinical, imaging, and laboratory data were input into an electronic database hosted at a central site.

Results

A total of 578 patients (578 CDI episodes) were included. Median age was 65 (range, 18-99) years and 48.2% were male. Hospital-onset CDI occurred in 64.0%. Recent antimicrobial use (41.9%) and proton pump inhibitor use (35.8%) were common. Significant risk factors for severe CDI were age <65 years (P < .001), malignancy within the last 5 years (P < .001), and surgery within the previous 30 days (P < .001). Significant risk factors for first recurrence included severe CDI (P = .03) and inflammatory bowel disease (P = .04). Metronidazole was the most common regimen for first episodes of CDI with 65.2% being concordant with Australian treatment guidelines overall. Determinants for death at 60 days included age ≥65 years (P = .01), severe CDI (P < .001), and antibiotic use within the prior 30 days (P = .02). Of those who received metronidazole as first-line therapy, 10.1% died in the 60-day follow-up period, compared to 9.8% of those who received vancomycin (P = .86).

Conclusions

Patients who experience CDI are vulnerable and require early diagnosis, clinical surveillance, and effective therapy to prevent complications and improve outcomes.

Validation of Clinical Risk Models for Clostridioides difficile-Attributable Outcomes

Clostridioides difficile is the leading health care-associated pathogen, leading to substantial morbidity and mortality; however, there is no widely accepted model to predict C. difficile infection severity. Most currently available models perform poorly or were calibrated to predict outcomes that are not clinically relevant. We sought to validate six of the leading risk models (Age Treatment Leukocyte Albumin Serum Creatinine (ATLAS), C. difficile Disease (CDD), Zar, Hensgens, Shivashankar, and C. difficile Severity Score (CDSS)), guideline severity criteria, and PCR cycle threshold for predicting C. difficile-attributable severe outcomes (inpatient mortality, colectomy/ileostomy, or intensive care due to sepsis). Models were calculated using electronic data available within ±48 h of diagnosis (unavailable laboratory measurements assigned zero points), calibrated using a large retrospective cohort of 3,327 inpatient infections spanning 10 years, and compared using receiver operating characteristic (ROC) and precision-recall curves. ATLAS achieved the highest area under the ROC curve (AuROC) of 0.781, significantly better than the next best performing model (Zar 0.745; 95% confidence interval of AuROC difference 0.0094–0.6222; P = 0.008), and highest area under the precision-recall curve of 0.232. Current IDSA/SHEA severity criteria demonstrated moderate performance (AuROC 0.738) and PCR cycle threshold performed the worst (0.531). The overall predictive value for all models was low, with a maximum positive predictive value of 37.9% (ATLAS cutoff ≥9). No clinical model performed well on external validation, but ATLAS did outperform other models for predicting clinically relevant C. difficile-attributable outcomes at diagnosis. Novel markers should be pursued to augment or replace underperforming clinical-only models.

European Society of Clinical Microbiology and Infectious Diseases: 2021 update on the treatment guidance document for Clostridioides difficile infection in adults

SCOPE

In 2009, the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) published the first treatment guidance document for Clostridioides difficile infection (CDI). This document was updated in 2014. The growing literature on CDI antimicrobial treatment and novel treatment approaches, such as faecal microbiota transplantation (FMT) and toxin-binding monoclonal antibodies, prompted the ESCMID study group on C. difficile (ESGCD) to update the 2014 treatment guidance document for CDI in adults.

METHODS AND QUESTIONS

Key questions on CDI treatment were formulated by the guideline committee and included: What is the best treatment for initial, severe, severe-complicated, refractory, recurrent and multiple recurrent CDI? What is the best treatment when no oral therapy is possible? Can prognostic factors identify patients at risk for severe and recurrent CDI and is there a place for CDI prophylaxis? Outcome measures for treatment strategy were: clinical cure, recurrence and sustained cure. For studies on surgical interventions and severe-complicated CDI the outcome was mortality. Appraisal of available literature and drafting of recommendations was performed by the guideline drafting group. The total body of evidence for the recommendations on CDI treatment consists of the literature described in the previous guidelines, supplemented with a systematic literature search on randomized clinical trials and observational studies from 2012 and onwards. The Grades of Recommendation Assessment, Development and Evaluation (GRADE) system was used to grade the strength of our recommendations and the quality of the evidence. The guideline committee was invited to comment on the recommendations. The guideline draft was sent to external experts and a patients' representative for review. Full ESCMID endorsement was obtained after a public consultation procedure.

RECOMMENDATIONS

Important changes compared with previous guideline include but are not limited to: metronidazole is no longer recommended for treatment of CDI when fidaxomicin or vancomycin are available, fidaxomicin is the preferred agent for treatment of initial CDI and the first recurrence of CDI when available and feasible, FMT or bezlotoxumab in addition to standard of care antibiotics (SoC) are preferred for treatment of a second or further recurrence of CDI, bezlotoxumab in addition to SoC is recommended for the first recurrence of CDI when fidaxomicin was used to manage the initial CDI episode, and bezlotoxumab is considered as an ancillary treatment to vancomycin for a CDI episode with high risk of recurrence when fidaxomicin is not available. Contrary to the previous guideline, in the current guideline emphasis is placed on risk for recurrence as a factor that determines treatment strategy for the individual patient, rather than the disease severity.

Prognostic factors for severe and recurrent Clostridioides difficile infection: a systematic review

OBJECTIVES

Clostridioides difficile infection (CDI), its subsequent recurrences (rCDIs), and severe CDI (sCDI) provide a significant burden for both patients and the healthcare system. Identifying patients diagnosed with initial CDI who are at increased risk of developing sCDI/rCDI could lead to more cost-effective therapeutic choices. In this systematic review we aimed to identify clinical prognostic factors associated with an increased risk of developing sCDI or rCDI.

METHODS

PubMed, Embase, Emcare, Web of Science and COCHRANE Library databases were searched from database inception through March, 2021. The study eligibility criteria were cohort and case-control studies. Participants were patients ≥18 years old diagnosed with CDI, in which clinical or laboratory factors were analysed to predict sCDI/rCDI. Risk of bias was assessed by using the Quality in Prognostic Research (QUIPS) tool and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool modified for prognostic studies. Study selection was performed by two independent reviewers. Overview tables of prognostic factors were constructed to assess the number of studies and the respective effect direction and statistical significance of an association.

RESULTS

136 studies were included for final analysis. Greater age and the presence of multiple comorbidities were prognostic factors for sCDI. Identified risk factors for rCDI were greater age, healthcare-associated CDI, prior hospitalization, proton pump inhibitors (PPIs) started during or after CDI diagnosis, and previous rCDI.

CONCLUSIONS

Prognostic factors for sCDI and rCDI could aid clinicians to make treatment decisions based on risk stratification. We suggest that future studies use standardized definitions for sCDI/rCDI and systematically collect and report the risk factors assessed in this review, to allow for meaningful meta-analysis of risk factors using data of high-quality trials.

External Validation and Comparison of Clostridioides difficile Severity Scoring Systems

BACKGROUND

Many models have been developed to predict severe outcomes from Clostridioides difficile infection. These models are usually developed at a single institution and largely are not externally validated. This aim of this study was to validate previously published risk scores in a multicenter cohort of patients with CDI.

METHODS

Retrospective study on four separate inpatient cohorts with CDI from three distinct sites: The Universities of Michigan (2010-2012 and 2016), Chicago (2012), and Wisconsin (2012). The primary composite outcome was admission to an intensive care unit, colectomy, and/or death attributed to CDI within 30 days of positive testing. Both within each cohort and combined across all cohorts, published CDI severity scores were assessed and compared to each other and the IDSA guideline definitions of severe and fulminant CDI.

RESULTS

A total of 3,646 patients were included for analysis. Including the two IDSA guideline definitions, fourteen scores were assessed. Performance of scores varied within each cohort and in the combined set (mean area under the receiver operator characteristic curve(AUC 0.61, range 0.53-0.66). Only half of the scores had performance at or better than IDSA severe and fulminant definitions (AUCs 0.64 and 0.63, respectively). Most of the scoring systems had more false than true positives in the combined set (mean: 81.5%, range:0-91.5%).

CONCLUSIONS

No published CDI severity score showed stable, good predictive ability for adverse outcomes across multiple cohorts/institutions or in a combined multicenter cohort.

ACG Clinical Guidelines: Prevention, Diagnosis, and Treatment of Clostridioides difficile Infections

Clostridioides difficile infection occurs when the bacterium produces toxin that causes diarrhea and inflammation of the colon. These guidelines indicate the preferred approach to the management of adults with C. difficile infection and represent the official practice recommendations of the American College of Gastroenterology. The scientific evidence for these guidelines was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation process. In instances where the evidence was not appropriate for Grading of Recommendations Assessment, Development, and Evaluation but there was consensus of significant clinical merit, key concept statements were developed using expert consensus. These guidelines are meant to be broadly applicable and should be viewed as the preferred, but not the only, approach to clinical scenarios.

Leptin Receptor q223r Polymorphism Influences Clostridioides difficile Infection-Induced Neutrophil CXCR2 Expression in an Interleukin-1β Dependent Manner

Neutrophils are key first-responders in the innate immune response to C. difficile infection (CDI) and play a central role in disease pathogenesis. Studies have clearly shown that tissue neutrophil numbers need to be tightly regulated for optimal CDI outcomes: while excessive colonic neutrophilia is associated with severe CDI, neutrophil depletion also results in worse outcomes. However, the biological mechanisms that control CDI-induced neutrophilia remain poorly defined. C-X-C chemokine receptor 2 (CXCR2) is a chemotactic receptor that is critical in neutrophil mobilization from bone marrow to blood and tissue sites. We have previously reported that a single nucleotide polymorphism (SNP) in leptin receptor (LEPR), present in up to 50% of people, influenced CDI-induced neutrophil CXCR2 expression and tissue neutrophilia. Homozygosity for mutant LEPR (i.e. RR genotype) was associated with higher CXCR2 expression and more tissue neutrophils. Here, we investigated the biological mechanisms that regulate neutrophil CXCR2 expression after CDI, and the influence of host genetics on this process. Our data reveal that: a) CXCR2 plays a key role in CDI-induced neutrophil extravasation from blood to colonic tissue; b) plasma from C. difficile-infected mice upregulated CXCR2 on bone marrow neutrophils; c) plasma from C. difficile-infected RR mice induced a higher magnitude of CXCR2 upregulation and had more IL-1β; and d) IL-1β neutralization reduced CXCR2 expression on bone marrow and blood neutrophils and their subsequent accrual to colonic tissue. In sum, our data indicate that IL-1β is a key molecular mediator that communicates between gastro-intestinal tract (i.e. site of CDI) and bone marrow (i.e. primary neutrophil reservoir) and regulates the intensity of CDI-induced tissue neutrophilia by modulating CXCR2 expression. Further, our studies highlight the importance of host genetics in affecting these innate immune responses and provide novel insights into the mechanisms by which a common SNP influences CDI-induced neutrophilia.

Comparative effectiveness of early-targeted use of fidaxomicin versus oral vancomycin among hospitalized veterans' affairs patients with infections due to Clostridioides difficile

STUDY OBJECTIVES

This study sought to compare real-world effectiveness outcomes between hospitalized patients with Clostridioides difficile infections (CDIs) who received early-targeted fidaxomicin or oral vancomycin at two Veterans Affairs Medical Centers (VAMCs).

DESIGN

A retrospective cohort study was performed among hospitalized patients at two VAMCs from January 2008 until July 2017.

SETTING

Albany and Syracuse VAMCs.

PATIENTS

Patients were included in this analysis if they were age ≥18 years; were hospitalized; had a CDI with a Hines Severity Score Index (SSI) ≥2; received oral vancomycin (January 2008-June 2014 at Albany or Syracuse VAMCs) or fidaxomicin (March 2012-July 2017 at Albany VAMC) within 5 days of positive CDI stool sample for ≥ 48 hours.

INTERVENTION

Receipt of an oral vancomycin- or fidaxomicin-containing CDI regimen.

MEASUREMENTS

The primary outcome was a composite of 30-day mortality and 60-day recurrence.

MAIN RESULTS

The study included 54 oral vancomycin and 38 fidaxomicin recipients. The population was predominantly male (97.8%), and mean ± standard deviation age was 74.6 ± 11.1 years. The composite outcome was significantly different between fidaxomicin and vancomycin recipients (26.3% fidaxomicin vs. 51.9% vancomycin; odds ratio (OR): 0.33, 95% CI: 0.14-0.81, p = 0.01). This finding was maintained in the multivariate analysis after adjustment for confounders (adjusted OR: 0.25, 95% CI: 0.09-0.73, p = 0.01) CONCLUSIONS: This real-world effectiveness study suggests that use of fidaxomicin potentially results in better outcomes relative to oral vancomycin for initial treatment of hospitalized VAMC patients with CDIs.

A Risk Score to Predict Clostridioides difficile Infection

Background

Clostridioides difficile infection (CDI) is a major cause of severe diarrhea. In this retrospective study, we identified CDI risk factors by comparing demographic and clinical characteristics for Kaiser Permanente Northern California members ≥18 years old with and without laboratory-confirmed incident CDI.

Methods

We included these risk factors in logistic regression models to develop 2 risk scores that predict future CDI after an Index Date for Risk Score Assessment (IDRSA), marking the beginning of a period for which we estimated CDI risk.

Results

During May 2011 to July 2014, we included 9986 CDI cases and 2 230 354 members without CDI. The CDI cases tended to be older, female, white race, and have more hospitalizations, emergency department and office visits, skilled nursing facility stays, antibiotic and proton pump inhibitor use, and specific comorbidities. Using hospital discharge as the IDRSA, our risk score model yielded excellent performance in predicting the likelihood of developing CDI in the subsequent 31–365 days (C-statistic of 0.848). Using a random date as the IDRSA, our model also predicted CDI risk in the subsequent 31–365 days reasonably well (C–statistic 0.722).

Conclusions

These results can be used to identify high-risk populations for enrollment in C difficile vaccine trials and facilitate study feasibility regarding sample size and time to completion.

Systematic review on the definition and predictors of severe Clostridiodes difficile infection

Clostridiodes difficile infection (CDI) is one of the most common hospital-acquired infections with high mortality rates. Optimal management of CDI depends on early recognition of severity. However, currently, there is no acceptable standard of prediction. We reviewed severe CDI predictors in published literature and its definition according to clinical guidelines. We systematically reviewed studies describing clinical predictors for severe CDI in medical databases (Cochrane, EMBASE, Global Health Library, and MEDLINE/PubMed). They were independently evaluated by two reviewers. Six hundred thirty-three titles and abstracts were screened, and 31 studies were included. We excluded studies that were restricted to a specific patient population. There were 16 articles that examined mortality in CDI, as compared with 15 articles investigating non-mortality outcomes of CDI. The commonest risk factors identified were comorbidities, white blood cell count, serum albumin level, age, serum creatinine level and intensive care unit admission. Generally, the studies had small patient populations, were retrospective in nature, and mostly from Western centers. The commonest severe CDI criteria in clinical guidelines were raised white blood cell count, followed by low serum albumin and raised serum creatinine levels. There was no commonly agreed upon definition of severe CDI severity in the literature. Current clinical guidelines' definitions for severe CDI are heterogeneous. Hence, there is a need for prospective multi-center studies using standardized protocol for biospecimen investigation collection and shared data on outcomes of patients in order to devise a universally accepted definition for severe CDI.

Fecal Microbiota Transplantation: Redefining Surgical Management of Refractory Clostridium difficile Infection

Fecal microbiota transplantation (FMT) is the process of transplanting stool from a healthy donor into the gut of a diseased individual for therapeutic purposes. It has a clearly defined role in the treatment of recurrent Clostridium difficile (reclassified as " Clostridioides difficile ") infection (CDI), with cure rates over 90% and decreased rates of subsequent recurrence compared with anti-CDI antibiotics. There is emerging evidence that FMT is also effective in the treatment of severe and fulminant CDI, with associated decreases in mortality and colectomy rates compared with standard antibiotic therapy. FMT shows promise as salvage therapy for critically-ill CDI patients refractory to maximum medical therapy and not deemed to be surgical candidates. FMT should be considered early in the course of severe CDI and should be delivered immediately in patients with signs of refractory CDI. Expansion of FMT's use along the spectrum of CDI severity has potential to decrease associated rates of mortality and colectomy.

Evolving Strategies to Manage Clostridium difficile Colitis

Clostridium difficile infection remains a common nosocomial illness with a significant impact on health care delivery. As molecular phenotyping of this organism has changed our understanding of its transmission and virulence, so too have diagnostic methods and treatment strategies evolved in recent years. The burden of this infection falls predominantly on elderly patients with comorbidities who have recently received antibiotics. Oral or enteral vancomycin is now preferred for first-line antimicrobial treatment across the disease spectrum, including mild-moderate initial cases. Fidaxomicin (a novel macrolide antibiotic), bezlotoxumab (a monoclonal antibody against toxin TcdB), and fecal microbiota transplantation expand the therapeutic armamentarium, particularly for recurrent infection. Operative treatment should be reserved for patients with fulminant infection, and early identification of patients who would benefit from an operation remains a challenge. Less invasive surgical options-such as laparoscopic diverting ileostomy with colonic irrigation-may improve survival and other outcomes relative to total abdominal colectomy and represent an attractive alternative particularly for frail patients.

External validation of clinical prediction rules for complications and mortality following Clostridioides difficile infection

Background

Several clinical prediction rules (CPRs) for complications and mortality of Clostridioides difficile infection (CDI) have been developed but only a few have gone through external validation, and none is widely recommended in clinical practice.

Methods

CPRs were identified through a systematic review. We included studies that predicted severe or complicated CDI (cCDI) and mortality, reported at least an internal validation step, and for which data were available with minimal modifications. Data from a multicenter prospective cohort of 1380 adults with confirmed CDI were used for external validation. In this cohort, cCDI occurred in 8% of the patients and 30-day all-cause mortality occurred in 12%. The performance of each tool was assessed using individual outcomes, with the same cut-offs and standard parameters.

Results

Seven CPRs were assessed. Three predictive scores for cCDI showed low sensitivity (25–61%) and positive predictive value (PPV; 9–31%), but moderate specificity (54–90%) and negative predictive value (NPV; 82–95%). One model [using age, white blood cell count (WBC), narcotic use, antacids use, and creatinine ratio > 1.5× the normal level as covariates] showed a probability of 25% of cCDI at the optimal cut-off point with 36% sensitivity and 84% specificity. Two scores for mortality had low sensitivity (4–55%) and PPV (25–31%), and moderate specificity (71–78%) and NPV (87–92%). One predictive model for 30-day all-cause mortality [Charlson comorbidity index, WBC, blood urea nitrogen (BUN), diagnosis in ICU, and delirium] showed an AUC-ROC of 0.74. All other CPRs showed lower AUC values (0.63–0.69). Errors in calibration ranged from 12%- 27%.

Conclusions

Included CPRs showed moderate performance for clinical use in a large validation cohort with a majority of patients infected with ribotype 027 strains and a low rate of cCDI and mortality. These data show that better CPRs need to be developed and validated.

Treatment of Severe and Fulminnant Clostridioides difficile Infection

PURPOSE OF REVIEW

This article will review current management strategies for severe and fulminant Clostridioides difficile infection (CDI).

RECENT FINDINGS

Clostridioides difficile is the most common nosocomial cause of infectious diarrhea. With the rise of hypervirulent strains of CDI, almost 8% of patients hospitalized with CDI are afflicted with severe CDI (SCDI) or fulminant CDI (FCDI). A significant proportion of these patients do not respond to recommended anti-CDI antibiotic therapy such as oral vancomycin and fidaxomicin. Current recommendations suggest that patients with refractory CDI should proceed to colectomy or diverting loop ileostomy with colonic lavage. However, both of these surgical interventions result in high rates of post-surgical mortality approaching 30%. Fecal microbiota transplantation (FMT) is a promising therapy that is recommended in recurrent CDI. Recent studies have found that FMT can safely produce cure rates between 70 and 90% in patients with SCDI and FCDI, while significantly decreasing rates of CDI-related mortality and colectomy. A patient population likely to benefit the most from FMT is elderly patients due to their increased risk for CDI, treatment failure, and high comorbidity burden that may preclude surgical intervention. FMT should be considered in patients with SCDI or FCDI particularly when traditional anti-CDI antibiotics are ineffective.

A Generalizable, Data-Driven Approach to Predict Daily Risk of Clostridium difficile Infection at Two Large Academic Health Centers

OBJECTIVE An estimated 293,300 healthcare-associated cases of Clostridium difficile infection (CDI) occur annually in the United States. To date, research has focused on developing risk prediction models for CDI that work well across institutions. However, this one-size-fits-all approach ignores important hospital-specific factors. We focus on a generalizable method for building facility-specific models. We demonstrate the applicability of the approach using electronic health records (EHR) from the University of Michigan Hospitals (UM) and the Massachusetts General Hospital (MGH). METHODS We utilized EHR data from 191,014 adult admissions to UM and 65,718 adult admissions to MGH. We extracted patient demographics, admission details, patient history, and daily hospitalization details, resulting in 4,836 features from patients at UM and 1,837 from patients at MGH. We used L2 regularized logistic regression to learn the models, and we measured the discriminative performance of the models on held-out data from each hospital. RESULTS Using the UM and MGH test data, the models achieved area under the receiver operating characteristic curve (AUROC) values of 0.82 (95% confidence interval [CI], 0.80-0.84) and 0.75 ( 95% CI, 0.73-0.78), respectively. Some predictive factors were shared between the 2 models, but many of the top predictive factors differed between facilities. CONCLUSION A data-driven approach to building models for estimating daily patient risk for CDI was used to build institution-specific models at 2 large hospitals with different patient populations and EHR systems. In contrast to traditional approaches that focus on developing models that apply across hospitals, our generalizable approach yields risk-stratification models tailored to an institution. These hospital-specific models allow for earlier and more accurate identification of high-risk patients and better targeting of infection prevention strategies. Infect Control Hosp Epidemiol 2018;39:425-433.

Patient and Strain Characteristics Associated With Clostridium difficile Transmission and Adverse Outcomes

Background

No study has used whole-genome sequencing (WGS) to investigate risk factors for Clostridium difficile (CD) transmission between cases, or assessed the impact of recent acquisition on patient outcome.

Methods

This 20 month retrospective cohort study included consecutive cytotoxin-positive diarrheal samples, which underwent culture, ribotyping, and WGS (Illumina). Sequenced isolates were compared using single nucleotide variants (SNVs). Independent predictors of acquisition from another case, onward transmission, 120-day recurrence, and 30-day mortality were identified using logistic regression with backwards elimination.

Results

Of 660 CD cases, 640 (97%) were sequenced, of which 567 (89%) shared a ribotype with a prior case, but only 227 (35%) were ≤2 SNVs from a prior case, supporting recent acquisition. Plausible (<2 SNVs) recent ward-based acquisition from a symptomatic case was more frequent in certain ribotypes; 64% (67/105) for ribotype-027 cases, compared with 11% (6/57) for ribotype-078. Independent risk factors (adjusted P < .05) for CD acquisition included older age, longer inpatient duration, and ribotype; these factors, and male sex, increased onward transmission. Patients with a plausible donor had a greater risk of recurrence (adjusted P = .001) and trended towards greater 30-day mortality (adjusted P = .06). Ribotype had no additional mortality or recurrence impact after adjusting for acquisition (P > .1).

Conclusions

Greater transmission of certain lineages suggests CD may have different reservoirs and modes of transmission. Acquiring CD from a recent case is associated with poorer clinical outcomes. Clinical characteristics associated with increased healthcare-associated CD transmission could be used to target preventative interventions.

Using Machine Learning and the Electronic Health Record to Predict Complicated Clostridium difficile Infection

Background

Clostridium (Clostridioides) difficile infection (CDI) is a health care–associated infection that can lead to serious complications. Potential complications include intensive care unit (ICU) admission, development of toxic megacolon, need for colectomy, and death. However, identifying the patients most likely to develop complicated CDI is challenging. To this end, we explored the utility of a machine learning (ML) approach for patient risk stratification for complications using electronic health record (EHR) data.

Methods

We considered adult patients diagnosed with CDI between October 2010 and January 2013 at the University of Michigan hospitals. Cases were labeled complicated if the infection resulted in ICU admission, colectomy, or 30-day mortality. Leveraging EHR data, we trained a model to predict subsequent complications on each of the 3 days after diagnosis. We compared our EHR-based model to one based on a small set of manually curated features. We evaluated model performance using a held-out data set in terms of the area under the receiver operating characteristic curve (AUROC).

Results

Of 1118 cases of CDI, 8% became complicated. On the day of diagnosis, the model achieved an AUROC of 0.69 (95% confidence interval [CI], 0.55–0.83). Using data extracted 2 days after CDI diagnosis, performance increased (AUROC, 0.90; 95% CI, 0.83–0.95), outperforming a model based on a curated set of features (AUROC, 0.84; 95% CI, 0.75–0.91).

Conclusions

Using EHR data, we can accurately stratify CDI cases according to their risk of developing complications. Such an approach could be used to guide future clinical studies investigating interventions that could prevent or mitigate complicated CDI.

Healthcare-associated Clostridium difficile infection: role of correct hand hygiene in cross-infection control

INTRODUCTION

Clostridium difficile (CD) is the most common cause of health-care-associated infectious diarrhea with increasing incidence and severity in recent years. The main cause of hospital's acquired cross infections can be attributed to incorrect hand hygiene. We described the epidemiology of CD infection (CDI) in a teaching hospital in Southern Italy during a two years surveillance period and evaluated the health-care workers compliance to hand hygiene.

METHODS

CDI Incidence rates were calculated as the number of patients with positive C. difficile toxin assay per 10,000 patient-days. Compliance with hand hygiene was the ratio of the number of performed actions to the number of opportunities observed. Approximately 400 Hand Hygiene (HH) opportunities/year /ward were observed. We finally checked out if any correlation could be found.

RESULTS

From January 2015 to December 2016 a total number of 854 CD determinations were performed in patients with clinical symptoms of diarrhea. The search for toxins A and B was positive in 175 cases (21,2%), confirming the diagnosis of CDI. Compliance to hand hygiene was significantly inversely associated with the number of CDIs: the lower the compliance of health-care workers with hand hygiene the higher was the number of cases of CDIs (p = 0.003).

CONCLUSIONS

According to our results proper handwashing of health-care workers appears to be a key intervention in interrupting CD cross infections regardless of age and type of department in which the patient is admitted.

Leptin receptor q223r polymorphism influences neutrophil mobilization after Clostridium difficile infection

Clostridium difficile is the leading cause of nosocomial infections in the United States. Clinical disease outcomes after C. difficile infection (CDI) are dependent on intensity of host inflammatory responses. Specifically, peak peripheral white blood cell (WBC) count >20 × 10⁹ l^-1 is an indicator of adverse outcomes in CDI patients, and is associated with higher 30-day mortality. We show that homozygosity for a common single nucleotide polymorphism (Q to R mutation in leptin receptor that is present in up to 50% of people), significantly increases the risk of having peak peripheral WBC count >20 × 10⁹ l^-1 (odds ratio=5.41; P=0.0023) in CDI patients. In a murine model of CDI, we demonstrate that mice homozygous for the same single nucleotide polymorphism (RR mice) have more blood and tissue leukocytes (specifically neutrophils), exaggerated tissue inflammation, and higher mortality as compared with control mice, despite similar pathogen burden. Further, we show that neutrophilia in RR mice is mediated by gut microbiota-directed expression of CXC chemokine receptor 2 (CXCR2), which promotes the release of neutrophils from bone marrow reservoir. Overall these studies provide novel mechanistic insights into the role of human genetic polymorphisms and gut microbiota in regulating the fundamental biological process of CDI-induced neutrophilia.

European Practice for CDI Treatment

Clostridium difficile infection (CDI) remains a significant cause of morbidity and mortality worldwide. Historically, two antibiotics (metronidazole and vancomycin) and a recent third (fidaxomicin) have been used routinely for CDI treatment; convincing data are now available showing that metronidazole is the least efficacious agent. The European Society of Clinical Microbiology and Infectious Diseases CDI treatment guidelines outline the treatment options for a variety of CDI clinical scenarios, including use of the more traditional anti-CDI therapies (e.g., metronidazole, vancomycin), the role of newer anti-CDI agents (e.g., fidaxomicin), indications for surgical intervention and for non-antimicrobial management (e.g., faecal microbiota transplantation, FMT). A 2017 survey of 20 European countries found that while the majority (n = 14) have national CDI guidelines that provide a variety of recommendations for CDI treatment, only five have audited guideline implementation. A variety of restrictions are in place in 13 (65%) countries prior to use of new anti-CDI treatments, including committee/infection specialist approval or economic review/restrictions. Novel anti-CDI agents are being evaluated in Phase III trials; it is not yet clear what will be the roles of these agents. Prophylaxis is an optimum approach to reduce the impact of CDI especially in high-risk populations; monoclonal antibodies, antibiotic blocking approaches and multiple vaccines are currently in advanced clinical trials. The treatment of recurrent CDI is particularly troublesome, and several different live bio therapeutics are being developed, in addition to FMT.

External Validation of Velazquez-Gomez Severity Score Index and ATLAS Scores and the Identification of Risk Factors Associated with Mortality in Clostridium difficile Infections

Treatment guidelines for Clostridium difficile infection (CDI) are limited by a lack of widely accepted clinical prediction tools (CPTs). Two published CPTs, the Velazquez-Gomez Severity Score Index (VGSSI) and ATLAS scores, were evaluated, and variables showing the greatest correlation with mortality in patients with CDI were identified to further develop an objective, mortality-based CPT. A retrospective review of the charts of 271 hospitalized patients with CDI was performed. VGSSI and ATLAS scores were assigned. Means and correlations of these scores with mortality were evaluated. Multivariate logistic regression analysis was performed on 32 known potential mortality predictor variables. Mortality was overall strongly associated with VGSSI and ATLAS scores with poor correlation within the intermediate ranges. Mean scores for nonsurvivors indicated poor calibration. The variables most associated with mortality were Age, vasopressors, steroids, creatinine level, and albumin. Although both CPTs revealed the ability to discriminate patients at greater risk for mortality, precision and overall calibration were lacking. Five variables were identified which had the greatest correlation with mortality. Utilization of these variables to enhance or modify the existing CPTs is suggested as the next step in the development of a useful and accurate mortality-based CPT for the treatment of CDI.

Sleeping with the enemy: Clostridium difficile infection in the intensive care unit

Over the last years, there was an increase in the number and severity of Clostridium difficile infections (CDI) in all medical settings, including the intensive care unit (ICU). The current prevalence of CDI among ICU patients is estimated at 0.4–4% and has severe impact on morbidity and mortality. An estimated 10–20% of patients are colonized with C. difficile without showing signs of infection and spores can be found throughout ICUs. It is not yet possible to predict whether and when colonization will become infection. Figuratively speaking, our patients are sleeping with the enemy and we do not know when this enemy awakens.

Most patients developing CDI in the ICU show a mild to moderate disease course. Nevertheless, difficult-to-treat severe and complicated cases also occur. Treatment failure is particularly frequent in ICU patients due to comorbidities and the necessity of continued antibiotic treatment. This review will give an overview of current diagnostic, therapeutic, and prophylactic challenges and options with a special focus on the ICU patient.

First, we focus on diagnosis and prognosis of disease severity. This includes inconsistencies in the definition of disease severity as well as diagnostic problems. Proceeding from there, we discuss that while at first glance the choice of first-line treatment for CDI in the ICU is a simple matter guided by international guidelines, there are a number of specific problems and inconsistencies. We cover treatment in severe CDI, the problem of early recognition of treatment failure, and possible concepts of intensifying treatment. In conclusion, we mention methods for CDI prevention in the ICU.

Rethinking Strategies to Select Antibiotic Therapy in Clostridium difficile infection

In recent years, Clostridium difficile infection (CDI) has become a global public health threat associated with increased morbidity, mortality, and economic burden, all of which are exacerbated with disease recurrence. Current guidelines informing treatment decisions are largely based on definitions of disease severity at diagnosis, with subjective components not well delineated across treatment algorithms and clinical trials. Furthermore, there is little evidence linking severity at onset to outcome. However, reducing the risk of recurrence may offer both a better outcome for the individual and decreased downstream economic impact. The authors present data supporting the opinion that patients deemed at low risk for recurrence should receive vancomycin (or metronidazole when cost is an issue), while those at higher risk of recurrence would benefit from fidaxomicin treatment. Although further prospective studies are needed, choosing treatment with the goal of preventing recurrent CDI may offer a better guide than disease severity.

Bezlotoxumab: anti-toxin B monoclonal antibody to prevent recurrence of Clostridium difficile infection

Clostridium difficile infection (CDI) is the most common nosocomial infection in the U.S. 25% of CDI patients go on to develop recurrent CDI (rCDI) following current standard of care (SOC) therapy, leading to morbidity, mortality and economic loss. The first passive immunotherapy drug targeting C.difficile toxin B (bezlotoxumab) has been approved recently by the FDA and EMA for prevention of rCDI. Areas covered: A body of key studies was selected and reviewed by the authors. The unmet needs in CDI care were ascertained with emphasis in rCDI, including the epidemiology, pathophysiology and current management. The current knowledge about the immune response to C. difficile toxins and how this knowledge led to the development and the clinical use of bezlotoxumab is described. Current and potential future competitors to the drug were examined. Expert commentary: A single 10 mg/kg intravenous infusion of bezlotoxumab has been shown to decrease rCDI by ~40% (absolute reduction ~10%) in patients being treated for primary CDI or rCDI with SOC antibiotics. Targeting C.difficile toxins by passive immunotherapy is a novel mechanism for prevention of C.difficile infection. Bezlotoxumab will be a valuable adjunctive therapy to reduce the burden of CDI.

External Validation of Three Prediction Tools for Patients at Risk of a Complicated Course of Clostridium difficile Infection: Disappointing in an Outbreak Setting

OBJECTIVE Estimating the risk of a complicated course of Clostridium difficile infection (CDI) might help doctors guide treatment. We aimed to validate 3 published prediction models: Hensgens (2014), Na (2015), and Welfare (2011). METHODS The validation cohort comprised 148 patients diagnosed with CDI between May 2013 and March 2014. During this period, 70 endemic cases of CDI occurred as well as 78 cases of CDI related to an outbreak of C. difficile ribotype 027. Model calibration and discrimination were assessed for the 3 prediction rules. RESULTS A complicated course (ie, death, colectomy, or ICU admission due to CDI) was observed in 31 patients (21%), and 23 patients (16%) died within 30 days of CDI diagnosis. The performance of all 3 prediction models was poor when applied to the total validation cohort with an estimated area under the curve (AUC) of 0.68 for the Hensgens model, 0.54 for the Na model, and 0.61 for the Welfare model. For those patients diagnosed with CDI due to non-outbreak strains, the prediction model developed by Hensgens performed the best, with an AUC of 0.78. CONCLUSION All 3 prediction models performed poorly when using our total cohort, which included CDI cases from an outbreak as well as endemic cases. The prediction model of Hensgens performed relatively well for patients diagnosed with CDI due to non-outbreak strains, and this model may be useful in endemic settings. Infect Control Hosp Epidemiol 2017;38:897-905.

Clostridium difficile

Clostridium difficile infections (CDIs) have emerged as one of the principal threats to the health of hospitalized and immunocompromised patients. The importance of C difficile colonization is increasingly recognized not only as a source for false-positive clinical testing but also as a source of new infections within hospitals and other health care environments. In the last five years, several new treatment strategies that capitalize on the increasing understanding of the altered microbiome and host defenses in patients with CDI have completed clinical trials, including fecal microbiota transplantation. This article highlights the changing epidemiology, laboratory diagnostics, pathogenesis, and treatment of CDI.

Predictors of severe outcomes in patients with Clostridium difficile infection from a Hispanic population

BACKGROUND

Factors associated with complicated Clostridium difficile infection (CDI) may vary among populations, and predictors of severe outcomes in CDI have not been studied in Hispanic patients. The aim of this study was to identify factors associated with a higher risk of colectomy, all-cause mortality, and CDI-associated mortality in a Hispanic population.

METHODS

We performed a retrospective study of all hospitalized patients with a diagnosis of CDI between January 1, 2011 and September 30, 2015 in a 450-bed teaching hospital in Monterrey, northeast Mexico. Three main outcomes were defined: fulminant colitis with subsequent colectomy, all-cause mortality within 30 days of diagnosis, and CDI-attributable mortality.

RESULTS

Of 261 patients with diarrhea, 176 were diagnosed with CDI. For colectomy, Charlson comorbidity index, ICU stay and mechanical ventilation prior to CDI diagnosis, days with diarrhea prior to treatment, total days of hospital stay and days after CDI diagnosis, elevated ATLAS score, days of diarrhea post CDI treatment, and treatment failure significantly predicted the necessity of surgical treatment with colectomy.

CONCLUSION

Treatment failure, persistent diarrhea, and a high ATLAS score were identified as risk factors for severe outcomes of CDI. A low albumin concentration and high creatinine were associated with higher overall mortality.

Clostridium difficile in an Urban, University-Affiliated Long-Term Acute-Care Hospital

OBJECTIVES To describe the characteristics and impact of Clostridium difficile infection (CDI) in a long-term acute-care hospital (LTACH). DESIGN Retrospective matched cohort study. SETTING A 38-bed, urban, university-affiliated LTACH. METHODS The characteristics of LTACH-onset CDI were assessed among patients hospitalized between July 2008 and October 2015. Patients with CDI were matched to concurrently hospitalized patients without a diagnosis of CDI. Severe CDI was defined as CDI with 2 or more of the following criteria: age ≥65 years, serum creatinine ≥2 mg/dL, or peripheral leukocyte count ≥20,000 cells/μL. A conditional Poisson regression model was developed to determine characteristics associated with a composite primary outcome of 30-day readmission to an acute-care hospital, or mortality. RESULTS The overall incidence of CDI was 21.4 cases per 10,000 patient days, with 27% of infections classified as severe. Patients with CDI had a mean age of 70 years (SD, 14 years), a mean Charlson comorbidity index of 3.6 (SD, 2.0), a median length of stay of 33 days (interquartile range [IQR], 24-45 days), and a median time between admission and CDI diagnosis of 16 days (IQR, 9-23 days). The most commonly prescribed antibiotic preceding a CDI diagnosis was a cephalosporin, with median duration of 8 days (IQR, 4-14 days). In multivariate analysis, CDI was not significantly associated with the primary outcome (relative risk, 0.97; 95% CI, 0.59-1.58). CONCLUSIONS Incidence of CDI in an urban, university-affiliated LTACH was high. Future research should focus on infection prevention measures to decrease the burden of CDI in this complex patient population. Infect Control Hosp Epidemiol 2017;38:294-299.

ECCMID 2016: addressing the burden of recurrent Clostridium difficile infections

26th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID), 9-12th April 2016, Amsterdam, The Netherlands The European Congress of Clinical Microbiology and Infectious Diseases (ECCMID) is the annual scientific meeting of the European Society of Clinical Microbiology. ECCMID 2016, held in Amsterdam, The Netherlands, was attended by over 11,600 clinical microbiologists and infectious disease physicians from more than 120 countries. The Congress offered an essential opportunity to learn more about the diagnosis, prevention and treatment of healthcare-associated infections, especially those caused by Clostridium difficile. Recurrent C. difficile infections have an especially serious adverse impact on patients, their families and healthcare systems across Europe and around the world, and continue to be a cause for concern among ECCMID delegates and their colleagues responsible for managing vulnerable patients in acute hospitals and other healthcare facilities.

Clostridium difficile infection

Infection of the colon with the Gram-positive bacterium Clostridium difficile is potentially life threatening, especially in elderly people and in patients who have dysbiosis of the gut microbiota following antimicrobial drug exposure. C. difficile is the leading cause of health-care-associated infective diarrhoea. The life cycle of C. difficile is influenced by antimicrobial agents, the host immune system, and the host microbiota and its associated metabolites. The primary mediators of inflammation in C. difficile infection (CDI) are large clostridial toxins, toxin A (TcdA) and toxin B (TcdB), and, in some bacterial strains, the binary toxin CDT. The toxins trigger a complex cascade of host cellular responses to cause diarrhoea, inflammation and tissue necrosis - the major symptoms of CDI. The factors responsible for the epidemic of some C. difficile strains are poorly understood. Recurrent infections are common and can be debilitating. Toxin detection for diagnosis is important for accurate epidemiological study, and for optimal management and prevention strategies. Infections are commonly treated with specific antimicrobial agents, but faecal microbiota transplants have shown promise for recurrent infections. Future biotherapies for C. difficile infections are likely to involve defined combinations of key gut microbiota.

Clostridium difficile outbreak caused by NAP1/BI/027 strain and non-027 strains in a Mexican hospital

Background

Clostridium difficile infections caused by the NAP1/B1/027 strain are more severe, difficult to treat, and frequently associated with relapses.

Methods

A case–control study was designed to examine a C. difficile infection (CDI) outbreak over a 12-month period in a Mexican hospital. The diagnosis of toxigenic CDI was confirmed by real-time polymerase chain reaction, PCR (Cepheid Xpert C. difficile/Epi).

Results

During the study period, 288 adult patients were evaluated and 79 (27.4%) patients had confirmed CDI (PCR positive). C. difficile strain NAP1/B1/027 was identified in 31 (39%) of the patients with confirmed CDI (240 controls were included). Significant risk factors for CDI included any underlying disease (p < 0.001), prior hospitalization (p < 0.001), and antibiotic (p < 0.050) or steroid (p < 0.001) use. Laboratory abnormalities included leukocytosis (p < 0.001) and low serum albumin levels (p < 0.002). Attributable mortality was 5%. Relapses occurred in 10% of patients. Risk factors for C. difficile NAP1/B1/027 strain infections included prior use of quinolones (p < 0.03).

Risk factors for CDI caused by non-027 strains included chronic cardiac disease (p < 0.05), chronic renal disease (p < 0.009), and elevated serum creatinine levels (p < 0.003). Deaths and relapses were most frequent in the 027 group (10% and 19%, respectively).

Conclusions

C. difficile NAP1/BI/027 strain and non-027 strains are established pathogens in our hospital. Accordingly, surveillance of C. difficile infections is now part of our nosocomial prevention program.

Clostridium difficile

Clostridium difficile has re-emerged as a major hospital-acquired infection since 2001. Despite development of polymerase chain reaction-based testing, no single clinical diagnostic test has emerged with sufficient sensitivity, specificity, and turnaround time to be entirely reliable for disease diagnosis. The importance of C difficile acquired outside the hospital environment remains an unknown factor and awaits further epidemiologic investigation. This article discusses the changing epidemiology, clinical presentation, and pathogenesis of C difficile infection and highlights the ongoing challenges of laboratory diagnosis, treatment, and disease relapse.