Search

Background & Aims: HBV coinfection is common among people living with HIV (PLWH) and is the most important cause of hepatocellular carcinoma (HCC). While risk prediction tools for HCC have been validated in patients with HBV monoinfection, they have not been evaluated in PLWH. Thus, we performed an external validation of PAGE-B in people with HIV/HBV coinfection.Methods: We included data on PLWH from four European cohorts who were positive for HBsAg and did not have HCC before starting tenofovir. We estimated the predictive performance of PAGE-B for HCC occurrence over 15 years in patients receiving tenofovir-containing antiretroviral therapy. Model discrimination was assessed after multiple imputation using Cox regression with the prognostic index as a covariate, and by calculating Harrell's c-index. Calibration was assessed by comparing our cumulative incidence with the PAGE-B derivation study using Kaplan-Meier curves.Results: In total, 2,963 individuals with HIV/HBV coinfection on tenofovir-containing antiretroviral therapy were included. PAGE-B was Conclusions: For individuals with HIV/HBV coinfection, PAGE-B is a valid tool to determine the need for HCC screening. Impact and implications: Chronic HBV infection is the most important cause of hepatocellular carcinoma (HCC) among people living with HIV. Valid risk prediction may enable better targeting of HCC screening efforts to high-risk individuals. We aimed to validate PAGE-B, a risk prediction tool that is based on age, sex, and platelets, in 2,963 individuals with HIV/HBV coinfection who received tenofovir-containing antiretroviral therapy. In the present study, PAGE-B showed good discrimination, adequate calibration, and a cut-off of

Objectives Clostridium difficile infections (CDI) account for 1.5% of diarrhoeic episodes in patients attending a general practitioner in the Netherlands, but its sources are unknown. We searched for community clusters to recognize localized point sources of CDI. Methods Between October 2010 and February 2012, a community-based prospective nested case–control study was performed in three laboratories in the Netherlands with a study population of 2 810 830 people. Bernoulli spatial scan and space–time permutation models were used to detect spatial and/or temporal clusters of CDI. In addition, a multivariate conditional logistic regression model was constructed to test livestock exposure as a supposed risk factor in CDI patients without hospital admission within the previous 12 weeks (community-acquired (CA) CDI). Results In laboratories A, B and C, 1.3%, 1.8% and 2.1% of patients with diarrhoea tested positive for CDI, respectively. The mean age of CA-CDI patients (n = 124) was 49 years (standard deviation, 22.6); 64.5% were female. No spatial or temporal clusters of CDI cases were detected compared to C. difficile–negative diarrhoeic controls. Except for one false-positive signal, no spatiotemporal interaction amongst CDI cases was found. Livestock exposure was not related to CA-CDI (odds ratio, 0.99; 95% confidence interval, 0.44–2.24). Ten percent of CA-CDIs was caused by PCR ribotype 078, spatially dispersed throughout the study area. Conclusions The absence of clusters of CDI cases in a community cohort of diarrhoeic patients suggests a lack of localized point sources of CDI in the living environment of these patients.

OBJECTIVEEstimating 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).METHODSThe 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.RESULTSA 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.CONCLUSIONAll 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 infections (CDIs) are frequent in hospitals, but also seem to increase in the community. Here, we aim to determine the incidence of CDI in general practice and to evaluate current testing algorithms for CDI. Three Dutch laboratories tested all unformed faeces (12 714) for C. difficile when diagnostic testing (for any enteric pathogen) was requested by a general practitioner (GP). Additionally, a nested case-control study was initiated, including 152 CDI patients and 304 age and sex-matched controls. Patients were compared using weighted multivariable logistic regression. One hundred and ninety-four samples (1.5%) were positive for C. difficile (incidence 0.67/10 000 patient years). This incidence was comparable to that of Salmonella spp. Compared with diarrhoeal controls, CDI was associated with more severe complaints, underlying diseases, antibiotic use and prior hospitalization. In our study, GPs requested a test for C. difficile in 7% of the stool samples, thereby detecting 40% of all CDIs. Dutch national recommendations advise testing for C. difficile when prior antibiotic use or hospitalization is present (18% of samples). If these recommendations were followed, 61% of all CDIs would have been detected. In conclusion, C. difficile is relatively frequent in general practice. Currently, testing for C. difficile is rare and only 40% of CDI in general practice is detected. Following recommendations that are based on traditional risk factors for CDI, would improve detection of CDI.

Clostridium difficile infections (CDIs) are a common cause of antibiotic-associated diarrhoea and associated with CDI-related mortality in c . 10%. To date, there is no prediction model in use that guides clinicians to identify patients at high risk for complicated CDI. From 2006 to 2009, nine Dutch hospitals included hospitalized CDI patients in a prospective cohort. Potential predictors of a complicated course (ICU admission, colectomy or death due to CDI) were evaluated in uni- and multivariate logistic regression. A score was constructed that was internally validated by bootstrapping. Furthermore, a pilot external validation was performed. Twelve per cent of 395 CDI patients had a complicated course within 30 days after diagnosis. Age (≥85 years, OR 4.96; 50–84 years, 1.83), admission due to diarrhoea (OR 3.27), diagnosis at the ICU department (OR 7.03), recent abdominal surgery (OR 0.23) and hypotension (OR 3.25) were independent predictors of a complicated course. These variables were used to construct a prediction model. A score subsequently classified patients into high risk (39% with a complicated course), intermediate (16%), low (5%) or virtually no risk of experiencing a complicated course. The score performed well after internal validation (AUC 0.78) and a pilot external validation among 139 patients showed similar good performance (AUC 0.73). We present an easy-to-use, clinically useful risk score that is capable of categorizing CDI patients according to their outcome. Because classification is available at diagnosis, it could have major implications for treatment choice.

To the Editor: With interest, we read the article by Bacci et al. in which they conclude that Clostridium difficile strains containing the binary toxin gene were associated with a higher case-fatality rate after 30 days, even when the analysis was stratified for PCR ribotype (1). Although this was an appealing conclusion, in our opinion the study was severely limited by selection bias and confounding by underlying diseases. First, in Danish patients with a C. difficile infection (CDI), isolates were characterized only if they were isolated during outbreaks or from patients with severe diseases or if isolates were found to be moxifloxacin resistant. Therefore, selection bias was likely to occur. Second, adjustment for concurrent conditions was not performed. This adjustment was especially warranted because outbreaks on specific hospital wards (e.g., intensive care units) could have influenced the all-cause mortality rate. Last, the selection of specific patients and strains questions the generalizability of the authors’ conclusion. In an approach to confirm the findings of Bacci et al. (1), we used data from a cohort study conducted during 2006–2009 in 13 Dutch hospitals (2). A total of 1,350 consecutive hospitalized patients with unformed feces and a positive C. difficile toxin test result were included in the study. We checked the 30-day survival for study patients in the Dutch Civil Registration System. For 626 (46%) of the patients, a C. difficile strain was available for PCR ribotyping and binary toxin gene characterization. Patient data (e.g., age, sex, hospitalization, and antimicrobial drug use in the 3 months before onset of diarrhea) were collected by review of electronic and paper patient charts and by contacting the treating physician. Underlying diseases present at hospital admission were classified into 7 disease categories (Table, footnote). In addition, during at least 6 months, the Charlson comorbidity index at admission was determined in 9 of the 13 hospitals (total of 357 CDI patients). Proportional hazards modeling was used for survival analysis. The Medical Review Ethics Committee of the Leiden University Medical Center approved this study Table Thirty-day mortality rates, stratified by binary toxin status, for persons with Clostridium difficile infection, the Netherlands, 2006–2009* During the study period, CDI was endemic in all hospitals in the cohort study (13 cases/10,000 admissions). The all-cause risk for dying within 30 days was 22% (12/55) for persons infected with binary toxin–positive 027 strains, 15% (15/100) for those infected with binary toxin–positive non-027 strains, and 11% (50/471) for those infected with binary toxin–negative strains (Table). Selection bias (e.g., by primarily characterizing isolates of patients with severe disease) was unlikely because the number of deaths among CDI patients without strain characterization (100/724 [14%]) was similar to that among patients with a characterized strain (77/626 [12%]; p = 0.41). Thirty-day mortality rates were significantly higher among patients with CDI due to type 027 strains than among patients with binary toxin–negative strains (hazard ratio [HR] 2.2); additional adjustment for age and concurrent condition(s) resulted in a relatively constant HR of 2.0–2.4. Patients with CDI due to binary toxin–positive non-027 strains did not have a substantially higher 30-day mortality rate (HR 1.5); additional adjustment for age and concurrent condition(s) lowered the HR to 1.1–1.4, depending on the method of adjustment. In accordance with findings in the Danish study, we observed a high 30-day mortality rate among persons infected with type 027 isolates. The 30-day mortality rate was lower among persons infected with non-027 binary toxin–positive isolates, especially after correction for concurrent condition(s); however, confidence intervals overlapped with those for type 027. Therefore, we cannot statistically contradict the conclusion of Bacci et al. (1). Nevertheless, because mortality rates in our study among patients with non-027 type CDI strongly resembled mortality rates among patients with CDI caused by binary toxin–negative isolates and because the Danish study was prone to bias and lacked adjustment for confounding, we think that the results of Bacci et al. (1) should be interpreted with caution. Furthermore, a large clinical study from 2008 concluded that C. difficile type 078, which is the most frequently found binary toxin positive non-027 strain, was not associated with a high all-cause mortality rate (3). A more recent publication confirmed this finding (4). Therefore, in our opinion, there is currently no convincing epidemiologic proof that binary toxin is a marker for infection with virulent C. difficile.

Background. Mortality among patients with Clostridium difficile infection (CDI) is high. Because of high age and multiple underlying diseases, CDI-related mortality is difficult to estimate. We estimated CDI-related mortality in an endemic situation, not influenced by outbreaks and consequently certain patients and C. difficile strains. Methods. Between 2006 and 2009, 13 Dutch hospitals included all hospitalized CDI patients. Nine hospitals individually matched each CDI patient to 2 control patients, based on ward and time of CDI hospitalization. Survival status was obtained via the Dutch Civil Registration System. Kaplan-Meier and Cox regression were used for survival analysis. Results. We identified 1366 patients with CDI (1.33 per 1000 admissions). All-cause mortality risk was 13% after 30 days and 37% after 1 year. The highest mortality was seen among elderly patients and patients with polymerase chain reaction ribotype 027. Three hundred seventeen CDI patients were matched to 317 patients without diarrhea and 232 patients with diarrhea, with a 30-day mortality risk of 5.4% and 8.6%, respectively. CDI patients had a 2.5-fold increased 30-day mortality rate compared to controls without diarrhea (hazard ratio 2.5 [95% confidence interval, 1.4–4.3]) when adjusted for age, sex, and underlying diseases. CDI-related death occurred mainly within 30 days after diagnosis. Conclusions. Mortality among CDI patients is high, even in an endemic situation. Our results show that CDI is associated with to a 2.5-fold increase in 30-day mortality. This highlights the considerable disease burden and clinical impact of CDI, even in absence of an outbreak.

In the last decade, outbreaks of nosocomial Clostridium difficile infections (CDI) occurred worldwide. A new emerging type, PCR-ribotype 027, was the associated pathogen. Antimicrobial susceptibility profiles of this type were extensively investigated and used to partly explain its spread. In Europe, the incidence of C. difficile PCR-ribotype 078 recently increased in humans and piglets. Using recommendations of the European Committee on Antimicrobial Susceptibility Testing (EUCAST) and the Clinical and Laboratory Standards Institute (CLSI) we studied the antimicrobial susceptibility to eight antimicrobials, mechanisms of resistance and the relation with previously prescribed antimicrobials in human (n=49) and porcine (n=50) type 078 isolates. Human and porcine type 078 isolates showed similar antimicrobial susceptibility patterns for the antimicrobials tested. In total, 37% of the isolates were resistant to four or more antimicrobial agents. The majority of the human and porcine isolates were susceptible to amoxicillin (100%), tetracycline (100%) and clindamycin (96%) and resistant to ciprofloxacin (96%). More variation was found for resistance patterns to erythromycin (76% in human and 59% in porcine isolates), imipenem (29% in human and 50% in porcine isolates) and moxifloxacin (16% for both human and porcine isolates). MIC values of cefuroxim were high (MICs >256 mg/L) in 96% of the isolates. Resistance to moxifloxacin and clindamycin was associated with a gyr(A) mutation and the presence of the erm(B) gene, respectively. A large proportion (96%) of the erythromycin resistant isolates did not carry the erm(B) gene. The use of ciprofloxacin (humans) and enrofloxacin (pigs) was significantly associated with isolation of moxifloxacin resistant isolates. Increased fluoroquinolone use could have contributed to the spread of C. difficile type 078.

Molecular typing is an essential tool to monitor Clostridium difficile infections and outbreaks within healthcare facilities. Molecular typing also plays a key role in defining the regional and global changes in circulating C. difficile types. The patterns of C. difficile types circulating within Europe (and globally) remain poorly understood, although international efforts are under way to understand the spatial and temporal patterns of C. difficile types. A complete picture is essential to properly investigate type-specific risk factors for C. difficile infections (CDI) and track long-range transmission. Currently, conventional agarose gel-based polymerase chain reaction (PCR) ribotyping is the most common typing method used in Europe to type C. difficile. Although this method has proved to be useful to study epidemiology on local, national and European level, efforts are made to replace it with capillary electrophoresis PCR ribotyping to increase pattern recognition, reproducibility and interpretation. However, this method lacks sufficient discriminatory power to study outbreaks and therefore multilocus variable-number tandem repeat analysis (MLVA) has been developed to study transmission between humans, animals and food. Sequence-based methods are increasingly being used for C. difficile fingerprinting/typing because of their ability to discriminate between highly related strains, the ease of data interpretation and transferability of data. The first studies using whole-genome single nucleotide polymorphism typing of healthcare-associated C. difficile within a clinically relevant timeframe are very promising and, although limited to select facilities because of complex data interpretation and high costs, these approaches will likely become commonly used over the coming years.

Nonsevere Clostridium difficile infection (CDI) and severe CDI, which carries a higher risk than nonsevere CDI for treatment failure and CDI recurrence, are difficult to distinguish at the time of diagnosis. To investigate the prognostic value of 3 markers of severe CDI suggested by recent guidelines (fever, leukocytosis, and renal failure), we used the database of 2 randomized controlled trials, which contained information for 1105 patients with CDI. Leukocytosis (risk ratio [RR], 2.29; 95% confidence interval [CI], 1.63-3.21) and renal failure (RR, 2.52; 95% CI, 1.82-3.50) were associated with treatment failure. Fever, although associated with treatment failure (RR, 2.45; 95% CI, 1.07-5.61), was rare. Renal failure was the only significant predictor of recurrence (RR, 1.45; 95% CI, 1.05-2.02). Different timing of measurements of leukocyte count and serum creatinine level around the CDI diagnosis led to a different severity classification in many cases. In conclusion, both leukocytosis and renal failure are useful predictors, although timing of measurement is important.

Clostridium difficile is the most common cause of antibiotic-associated diarrhoea in hospitals and other healthcare facilities. The elderly are particularly susceptible and at increased risk for adverse outcome as a result of C. difficile infection. The aim of this study was to determine the prevalence of C. difficile colonization among residents of nursing homes in Hesse and to compare it with the prevalence in the general population living outside long-term care facilities (LTCF). We assessed possible risk factors for C. difficile colonization and determined the genotype of circulating strains. C. difficile was isolated from 11/240 (4.6%) nursing home residents and 2/249 (0.8%) individuals living outside LTCF (p = 0.02). Ten of 11 (90.9%) isolates from nursing homes and one of two isolates from the population outside LTCF were toxigenic. The prevalence of C. difficile colonization varied from 0% to 10% between different nursing homes. Facilities with known actual or recent CDI cases were more likely to have colonized residents than facilities without known CDI cases. C. difficile PCR-ribotypes 014 and 001 were the most prevalent genotypes and accounted for 30% and 20% of toxigenic isolates in nursing homes, respectively. Interestingly, no individuals carried the epidemic strain PCR-ribotype 027. Our results suggest that residents of nursing homes in Germany are at high risk for colonization by virulent C. difficile strains. The high prevalence of C. difficile colonization in nursing homes underscores the importance of good adherence to standard infection control precautions even in the absence of a diagnosed infection. They also emphasize the need for specific programs to increase the awareness of healthcare professionals in LTCF for CDI.

SUMMARYBetween 2000 and 2009, the total number of patients withClostridium difficileinfections increased considerably in Southeastern Germany. A clear seasonality was observed with a higher number of affected patients occurring in the winter months (January–March). Moxifloxacin and erythromycin-resistantC. difficilePCR ribotypes 001 (72%) and 027 (4·6%) were the most commonly isolated strains.

Background: Clostridium difficile infections (CDIs) are common in developed countries and affect .250000 hospitalized patients annually in the USA. The most important risk factor for the disease is antibiotic therapy. Methods: To determine the period at risk for CDI after cessation of antibiotics, we performed a multicentre case –control study in the Netherlands between March 2006 and May 2009. Three hundred and thirty-seven hospitalized patients with diarrhoea and a positive toxin test were compared with 337 patients without diarrhoea. Additionally, a control group of patients with diarrhoea due to a cause other than CDI (n¼ 227) was included. Results: In the month prior to the date of inclusion, CDI patients more frequently used an antibiotic compared with non-diarrhoeal patients (77% versus 49%). During antibiotic therapy and in the first month after cessation of the therapy, patients had a 7 –10-fold increased risk for CDI (OR 6.7 –10.4). This risk declined in the period between 1 and 3 months after the antibiotic was stopped (OR 2.7). Similar results were observed when the second control group was used. All antibiotic classes, except first-generation cephalosporins and macrolides, were associated with CDI. Second- and third-generation cephalosporins (OR 3.3 and 5.3, respectively) and carbapenems (OR 4.7) were the strongest risk factors for CDI. Patients with CDI used more antibiotic classes and more defined daily doses, compared with non-diarrhoeal patients. Conclusions: Antibiotic use increases the risk for CDI during therapy and in the period of 3 months after cessation of antibiotic therapy. The highest risk for CDI was found during and in the first month after antibiotic use. Our study will aid clinicians to identify high-risk patients.

Rapid identification of hypervirulent Clostridium difficile strains is essential for preventing their spread. Recent completion of several full-length C. difficile genomes provided an excellent opportunity to identify potentially unique genes that characterize hypervirulent strains. Based on sequence comparisons between C. difficile strains we describe two gene insertions into the genome of hypervirulent PCR ribotypes 078 and 027. Analysis of these regions, of 1.7 and 4.2 kb, respectively, revealed that they contain several interesting ORFs. The 078 region is inserted intergenically and introduces an enzyme that is involved in the biosynthesis of several antibiotics. The 027 insert disrupts the thymidylate synthetase (thyX) gene and replaces it with an equivalent, catalytically more efficient, thyA gene. Both gene insertions were used to develop ribotype-specific PCRs, which were validated by screening a large strain collection consisting of 68 different PCR ribotypes supplemented with diverse 078 and 027 strains derived from different geographical locations and individual outbreaks. The genetic markers were stably present in the hypervirulent PCR ribotypes 078 and 027, but were also found in several other PCR ribotypes. Comparative analysis of amplified fragment length polymorphisms, PCR ribotype banding patterns and toxin profiles showed that all PCR ribotypes sharing the same insert from phylogenetically coherent clusters. The identified loci are unique to these clusters, to which the hypervirulent ribotypes 078 and 027 belong. This provides valuable information on strains belonging to two distinct lineages within C. difficile that are highly related to hypervirulent strains.

The purpose of this investigation was to study risk factors for Clostridium difficile infection (CDI) in an endemic setting. In a 34-month prospective case–control study, we compared the risk factors and clinical characteristics of all consecutively diagnosed hospitalised CDI patients (n = 93) with those of patients without diarrhoea (n = 76) and patients with non-CDI diarrhoea (n = 64). The incidence of CDI was 17.5 per 10,000 hospital admissions. C. difficile polymerase chain reaction (PCR) ribotype 014 was the most frequently found type (15.9%), followed by types 078 (12.7%) and 015 (7.9%). Independent risk factors for endemic CDI were the use of second-generation cephalosporins, previous hospital admission and previous stay at the intensive care unit (ICU). The use of third-generation cephalosporins was a risk factor for diarrhoea in general. We found no association of CDI with the use of fluoroquinolones or proton pump inhibitors (PPIs). The overall 30-day mortality among CDI patients, patients without diarrhoea and patients with non-CDI diarrhoea was 7.5%, 0% and 1.6%, respectively. In this endemic setting, risk factors for CDI differed from those in outbreak situations. Some risk factors that have been ascribed to CDI earlier were, in this study, not specific for CDI, but for diarrhoea in general. The 30-day mortality among CDI patients was relatively high.

After the first outbreaks of Clostridium difficile PCR ribotype 027 (North American pulsed-field type 1, restriction endonuclease analysis group BI) in the Netherlands in 2005, a national surveillance programme for C. difficile infection (CDI) was started. Furthermore, national guidelines were developed to rapidly recognise type 027 infections and prevent further spread. The mean incidence of CDI measured in 14 hospitals remained stable throughout the years: an incidence of 18 per 10,000 admissions was seen in 2007 and 2008. Between April 2005 and June 2009 a total of 2,788 samples were available for PCR ribotyping. A decrease was seen in the number and incidence of type 027 after the second half of 2006. In the first half of 2009, the percentage of type 027 isolates among all CDI decreased to 3.0%, whereas type 001 increased to 27.5%. Type 014 was present in 9.3% of the isolates and C. difficile type 078 slightly increased to 9.1%. We conclude that currently there is a significant decrease in type 027-associated CDI in the Netherlands.