Multicentre derivation and validation of a simple predictive index for healthcare-associated Clostridium difficile infection

Development of a Prediction Model to Identify the Risk of Clostridioides difficile Infection in Hospitalized Patients Receiving at Least One Dose of Antibiotics

OBJECTIVE

This study's objective was to develop a risk-prediction model to identify hospitalized patients at risk of Clostridioides difficile infection (CDI) who had received at least one dose of systemic antibiotics in a large tertiary hospital.

PATIENTS AND METHODS

This was a retrospective case-control study that included patients hospitalized for more than 2 days who received antibiotic therapy during hospitalization. The study included two groups: patients diagnosed with hospital CDI and controls without hospital CDI. Cases were matched 1:3 with assigned controls by age and sex. Descriptive statistics were used to identify the study population by comparing cases with controls. Continuous variables were stated as the means and standard deviations. A multivariate analysis was built to identify the significantly associated covariates between cases and controls for CDI.

RESULTS

A total of 364 patients were included and distributed between the two groups. The control group included 273 patients, and the case group included 91 patients. The risk factors for CDI were investigated, with only significant risks identified and included in the risk assessment model: age older than 70 years (p = 0.034), chronic kidney disease (p = 0.043), solid organ transplantation (p = 0.021), and lymphoma or leukemia (p = 0.019). A risk score of ≥2 showed the best sensitivity, specificity, and accuracy of 78.02%, 45.42%, and 78.02, respectively, with an area under the curve of 0.6172.

CONCLUSION

We identified four associated risk factors in the risk-prediction model. The tool showed good discrimination that might help predict, identify, and evaluate hospitalized patients at risk of developing CDI.

Diagnostic prediction models to identify patients at risk for healthcare-facility-onset Clostridioides difficile: A systematic review of methodology and reporting

OBJECTIVE

To systematically review the methodology, performance, and generalizability of diagnostic models for predicting the risk of healthcare-facility-onset (HO) Clostridioides difficile infection (CDI) in adult hospital inpatients (aged ≥18 years).

BACKGROUND

CDI is the most common cause of healthcare-associated diarrhea. Prediction models that identify inpatients at risk of HO-CDI have been published; however, the quality and utility of these models remain uncertain.

METHODS

Two independent reviewers evaluated articles describing the development and/or validation of multivariable HO-CDI diagnostic models in an inpatient setting. All publication dates, languages, and study designs were considered. Model details (eg, sample size and source, outcome, and performance) were extracted from the selected studies based on the CHARMS checklist. The risk of bias was further assessed using PROBAST.

RESULTS

Of the 3,030 records evaluated, 11 were eligible for final analysis, which described 12 diagnostic models. Most studies clearly identified the predictors and outcomes but did not report how missing data were handled. The most frequent predictors across all models were advanced age, receipt of high-risk antibiotics, history of hospitalization, and history of CDI. All studies reported the area under the receiver operating characteristic curve (AUROC) as a measure of discriminatory ability. However, only 3 studies reported the model calibration results, and only 2 studies were externally validated. All of the studies had a high risk of bias.

CONCLUSION

The studies varied in their ability to predict the risk of HO-CDI. Future models will benefit from the validation on a prospective external cohort to maximize external validity.

A Systematic Literature Review on Risk Factors for and Timing of Clostridioides difficile Infection in the United States

INTRODUCTION

Clostridioides difficile infection (CDI) is a major public health threat. Up to 40% of patients with CDI experience recurrent CDI (rCDI), which is associated with increased morbidity. This study aimed to define an at-risk population by obtaining a detailed understanding of the different factors leading to CDI, rCDI, and CDI-related morbidity and of time to CDI.

METHODS

We conducted a systematic literature review (SLR) of MEDLINE (using PubMed) and EMBASE for relevant articles published between January 1, 2016, and November 11, 2022, covering the US population.

RESULTS

Of the 1324 articles identified, 151 met prespecified inclusion criteria. Advanced patient age was a likely risk factor for primary CDI within a general population, with significant risk estimates identified in nine of 10 studies. Older age was less important in specific populations with comorbidities usually diagnosed at earlier age, such as bowel disease and cancer. In terms of comorbidities, the established factors of infection, kidney disease, liver disease, cardiovascular disease, and bowel disease along with several new factors (including anemia, fluid and electrolyte disorders, and coagulation disorders) were likely risk factors for primary CDI. Data on diabetes, cancer, and obesity were mixed. Other primary CDI risk factors were antibiotics, proton pump inhibitors, female sex, prior hospitalization, and the length of stay in hospital. Similar factors were identified for rCDI, but evidence was limited. Older age was a likely risk factor for mortality. Timing of primary CDI varied depending on the population: 2-3 weeks in patients receiving stem cell transplants, within 3 weeks for patients undergoing surgery, and generally more than 3 weeks following solid organ transplant.

CONCLUSION

This SLR uses recent evidence to define the most important factors associated with CDI, confirming those that are well established and highlighting new ones that could help to identify patient populations at high risk.

Fluoroquinolone-associated adverse events of interest among hospitalized veterans affairs patients with community-acquired pneumonia who were treated with a fluoroquinolone: A focus on tendonitis, Clostridioides difficile infection, and aortic aneurysm

STUDY OBJECTIVE

The objectives of this study were to (i) quantify the incidence of three concerning fluoroquinolone adverse events of interest (FQAEI, i.e., adverse tendon event (TE), clostridioides difficile infection (CDI), and aortic aneurysm/dissection (AAD)), (ii) identify the patient-level factors that predict these events, and (iii) develop clinical risk scores to estimate the predicted probabilities of each FQAEI based on patient-level covariates available on clinical presentation.

DESIGN

Retrospective cohort study.

SETTING

Upstate New York Veterans' Healthcare Administration from 2011 to 2016.

PATIENTS

Hospitalized patients with community-acquired pneumonia receiving care in the Upstate New York Veterans' Healthcare Administration from 2011 to 2016.

INTERVENTION

N/A.

MEASUREMENTS

The outcomes of interest for this study were the occurrence of TE, CDI, and AAD. We also evaluated a composite of these three outcomes, FQAEI.

MAIN RESULTS

The study population consisted of 1071 patients. The overall incidence of FQAEI, TE, AAD, and CDI was 6.5%, 1.8%, 4.5%, and 0.3%, respectively. For each outcome evaluated, the probability of the event of interest was predicted by the presence of certain comorbidities, previous healthcare exposure, choice of specific FQ antibiotic, or therapy duration. Concomitant steroids, pneumonia in preceding 180 days, and creatinine clearance <30 mL/min predicted FQAEI.

CONCLUSIONS

Individual frequencies of three important FQAEIs were quantified, and risk scores were developed to estimate the probabilities of experiencing these events to help clinicians individualize treatment decisions for patients and reduce the potential risks of select FQAEIs.

Can prediction scores be used to identify patients at risk of Clostridioides difficile infection?

PURPOSE OF REVIEW

To describe the current state of literature on modeling risk of incident and recurrent Clostridioides difficile infection (iCDI and rCDI), to underscore limitations, and to propose a path forward for future research.

RECENT FINDINGS

There are many published risk factors and models for both iCDI and rCDI. The approaches include scores with a limited list of variables designed to be used at the bedside, but more recently have also included automated tools that take advantage of the entire electronic health record. Recent attempts to externally validate scores have met with mixed success.

SUMMARY

For iCDI, the performance largely hinges on the incidence, which even for hospitalized patients can be low (often <1%). Most scores fail to achieve high accuracy and/or are not externally validated. A challenge in predicting rCDI is the significant overlap with risk factors for iCDI, reducing the discriminatory ability of models. Automated electronic health record-based tools show promise but portability to other centers is challenging. Future studies should include external validation and consider biomarkers to augment performance.

Potential Cost Savings Associated with Targeted Substitution of Current Guideline-Concordant Inpatient Agents with Omadacycline for the Treatment of Adult Hospitalized Patients with Community-Acquired Bacterial Pneumonia at High Risk for Clostridioides difficile Infections: Results of Healthcare-Decision Analytic Model from the United States Hospital Perspective

Introduction: Approximately 3% of hospitalized patients with community-acquired bacterial pneumonia (CABP) develop healthcare-associated Clostridioides difficile infection (HCA-CDI). The validated Davis risk score (DRS) indicates that patients with a DRS ≥ 6 are at an increased risk of 30-day HCA-CDI. In the phase 3 OPTIC CABP study, 14% of CABP patients with DRS ≥ 6 who received moxifloxacin developed CDI vs. 0% for omadacycline. This study assessed the potential economic impact of substituting current guideline-concordant CABP inpatient treatments with omadacycline in hospitalized CABP patients with a DRS ≥ 6 across US hospitals. Methods: A deterministic healthcare-decision analytic model was developed. The model population was hospitalized adult CABP patients with a DRS ≥ 6 across US hospitals (100,000 patients). In the guideline-concordant arm, 14% of CABP patients with DRS ≥ 6 were assumed to develop an HCA-CDI, each costing USD 20,100. In the omadacycline arm, 5 days of therapy was calculated for the entire model population. Results: The use of omadacycline in place of guideline-concordant CABP inpatient treatments for CABP patients with DRS ≥ 6 was estimated to result in cost savings of USD 55.4 million annually across US hospitals. Conclusion: The findings of this simulated model suggest that prioritizing the use of omadacycline over current CABP treatments in hospitalized CABP with a DRS ≥ 6 may potentially reduce attributable HCA-CDI costs. The findings are not unique to omadacycline and could be applied to any antibiotic that confers a lower risk of HCA-CDI relative to current CABP inpatient treatments.

A randomized, double-blind, placebo-controlled, single and multiple ascending dose Phase 1 study to determine the safety, pharmacokinetics and food and faecal microbiome effects of ibezapolstat administered orally to healthy subjects

Background

Clostridioides difficile infection is the most common cause of healthcare-associated infections in the USA, with limited treatment options. Ibezapolstat is a novel DNA polymerase IIIC inhibitor with in vitro activity against C. difficile.

Objectives and methods

Randomized, double-blind, placebo-controlled study to assess the safety, tolerability and pharmacokinetics of ibezapolstat in healthy volunteers. Microbiome changes associated with ibezapolstat were compared with vancomycin over a 10 day course using shotgun metagenomics.

Results

A total of 62 subjects aged 31 ± 7 years (45% female; average BMI: 25 ± 3 kg/m²) were randomized. Ibezapolstat was well tolerated with a safety signal similar to placebo. Ibezapolstat had minimal systemic absorption with the majority of plasma concentrations less than 1 µg/mL. In the multiday, ascending dose study, ibezapolstat concentrations of 2000 µg/g of stool were observed by Day 2 and for the remainder of the dosing time period. In the multiday, multiple-dose arm, baseline microbiota was comparable between subjects that received ibezapolstat compared with vancomycin. At Day 10 of dosing, differential abundance analysis and β-diversity demonstrated a distinct difference between the microbiome in subjects given vancomycin compared with either dose of ibezapolstat (P = 0.006). α-Diversity changes were characterized as an increase in the Actinobacteria phylum in subjects that received ibezapolstat and an increase in Proteobacteria in subjects given vancomycin.

Conclusions

Ibezapolstat was shown to be safe and well tolerated, with minimal systemic exposure, high stool concentrations and a distinct microbiome profile compared with oral vancomycin. These results support further clinical development of ibezapolstat for patients with C. difficile infection.

Evaluation of a risk assessment model to predict infection with healthcare facility-onset Clostridioides difficile

Disclaimer

In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

Purpose

We evaluated a previously published risk model (Novant model) to identify patients at risk for healthcare facility–onset Clostridioides difficile infection (HCFO-CDI) at 2 hospitals within a large health system and compared its predictive value to that of a new model developed based on local findings.

Methods

We conducted a retrospective case-control study including adult patients admitted from July 1, 2016, to July 1, 2018. Patients with HCFO-CDI who received systemic antibiotics were included as cases and were matched 1 to 1 with controls (who received systemic antibiotics without developing HCFO-CDI). We extracted chart data on patient risk factors for CDI, including those identified in prior studies and those included in the Novant model. We applied the Novant model to our patient population to assess the model’s utility and generated a local model using logistic regression–based prediction scores. A receiver operating characteristic area under the curve (ROC-AUC) score was determined for each model.

Results

We included 362 patients, with 161 controls and 161 cases. The Novant model had a ROC-AUC of 0.62 in our population. Our local model using risk factors identifiable at hospital admission included hospitalization within 90 days of admission (adjusted odds ratio [OR], 3.52; 95% confidence interval [CI], 2.06-6.04), hematologic malignancy (adjusted OR, 12.87; 95% CI, 3.70-44.80), and solid tumor malignancy (adjusted OR, 4.76; 95% CI, 1.27-17.80) as HCFO-CDI predictors and had a ROC-AUC score of 0.74.

Conclusion

The Novant model evaluating risk factors identifiable at admission poorly predicted HCFO-CDI in our population, while our local model was a fair predictor. These findings highlight the need for institutions to review local risk factors to adjust modeling for their patient population.

Decision Analysis: Omadacycline Relative to Moxifloxacin Among Hospitalized Community-Acquired Bacterial Pneumonia Patients at Risk of Clostridioides difficile Infection

BACKGROUND AND OBJECTIVE: Omadacycline is an aminomethylcycline antibiotic approved in the USA as once-daily intravenous/oral monotherapy for adults with community-acquired bacterial pneumonia (CABP). Omadacycline demonstrated noninferiority to the fluoroquinolone moxifloxacin in a phase III CABP trial; adverse-event rates were similar between treatment groups except for Clostridioides difficile infection (CDI), which occurred in 2% of moxifloxacin-treated patients and 0% of patients on omadacycline. Conceptual healthcare-decision analytic models were developed to better understand the economic implications of antibiotic selection and CDI risk in acute-care facilities.

METHODS

A conceptual healthcare-decision analytic model was created to estimate incremental costs associated with treating 100 hospitalized CABP patients with an initial 5-day inpatient regimen of omadacycline instead of moxifloxacin. The underlying model assumption was that treatment with omadacycline has the potential to reduce CDI events relative to moxifloxacin. The model included excess costs associated with each treatment group from admission through discharge. Attributable CDI cost per case in the moxifloxacin group varied from $15,000 to $45,000 (US$). Omadacycline acquisition cost was $300-600/day for 5 days.

RESULTS

At a CDI attributable cost per case of $30,000 (base-case analyses), the incremental treatment cost (US$) per 100 patients ranged from $300,000 to $- 120,000 (cost savings). The excess CDI incidence in moxifloxacin-treated patients would need to be 5-10% for omadacycline to be cost-saving, assuming the attributable CDI cost is approximately $30,000.

CONCLUSION

Targeted omadacycline use may reduce economic burden associated with hospitalized CABP patients treated with moxifloxacin if it can reduce excess cases of moxifloxacin-associated CDI.

Clostridioides (Formerly Clostridium) difficile Infection During Hospitalization Increases the Likelihood of Nonhome Patient Discharge

BACKGROUND

Clostridioides (formerly Clostridium) difficile infection (CDI) is associated with significant morbidity and mortality, including frequent hospitalizations. However, the impact of CDI after hospital discharge is poorly understood. The purpose of this study was to assess patient discharge disposition and understand CDI-related risk factors for nonhome discharge.

METHODS

Using a nationally representative database of Veterans Health Administration (VHA) patients (2003-2014) and a validation database from hospitalized non-VHA patients in Houston, Texas, admission and discharge disposition was obtained for patients with CDI and matched controls. Incidence of and clinical/microbiologic risk factors for nonhome discharge were assessed using these databases.

RESULTS

A total of 15173 VHA patients with CDI and 48599 non-CDI control patients originally admitted from the community were included. Significantly more patients with CDI were discharged to a nonhome location compared with controls (18% vs 8%; P < .0001), most commonly hospice/death (12%) or nursing home/long-term care facility (6%). Results were confirmed using a propensity-matched analysis and a validation cohort of 1941 hospitalized patients with CDI in Houston, Texas. Age, comorbidities, severe CDI, and ribotypes F027, F001, and F053-163 were associated with a nonhome discharge (P < .05 for all).

CONCLUSIONS

Hospitalized patients with CDI frequently required a higher level of medical care residence at discharge compared with non-CDI patients. Risk factors for discharge to a higher level of care included CDI disease severity and variables associated with recurrent CDI.

Incidence and Outcomes Associated With Clostridium difficile Infections: A Systematic Review and Meta-analysis

IMPORTANCE

An understanding of the incidence and outcomes of Clostridium difficile infection (CDI) in the United States can inform investments in prevention and treatment interventions.

OBJECTIVE

To quantify the incidence of CDI and its associated hospital length of stay (LOS) in the United States using a systematic literature review and meta-analysis.

DATA SOURCES

MEDLINE via Ovid, Cochrane Library Databases via Wiley, Cumulative Index of Nursing and Allied Health Complete via EBSCO Information Services, Scopus, and Web of Science were searched for studies published in the United States between 2000 and 2019 that evaluated CDI and its associated LOS.

STUDY SELECTION

Incidence data were collected only from multicenter studies that had at least 5 sites. The LOS studies were included only if they assessed postinfection LOS or used methods accounting for time to infection using a multistate model or compared propensity score-matched patients with CDI with control patients without CDI. Long-term-care facility studies were excluded. Of the 119 full-text articles, 86 studies (72.3%) met the selection criteria.

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers performed the data abstraction and quality assessment. Incidence data were pooled only when the denominators used the same units (eg, patient-days). These data were pooled by summing the number of hospital-onset CDI incident cases and the denominators across studies. Random-effects models were used to obtain pooled mean differences. Heterogeneity was assessed using the I2 value. Data analysis was performed in February 2019.

MAIN OUTCOMES AND MEASURES

Incidence of CDI and CDI-associated hospital LOS in the United States.

RESULTS

When the 13 studies that evaluated incidence data in patient-days due to hospital-onset CDI were pooled, the CDI incidence rate was 8.3 cases per 10 000 patient-days. Among propensity score-matched studies (16 of 20 studies), the CDI-associated mean difference in LOS (in days) between patients with and without CDI varied from 3.0 days (95% CI, 1.44-4.63 days) to 21.6 days (95% CI, 19.29-23.90 days).

CONCLUSIONS AND RELEVANCE

Pooled estimates from currently available literature suggest that CDI is associated with a large burden on the health care system. However, these estimates should be interpreted with caution because higher-quality studies should be completed to guide future evaluations of CDI prevention and treatment interventions.

Molecular epidemiology of Clostridioides difficile in domestic dogs and zoo animals

Animals such as domestic dogs and zoo animals reside in close proximity to humans and could contribute to the dissemination of Clostridioides difficile spores which are common in the community environment. The purpose of this study was to assess C. difficile colonization in domestic dogs attending a day boarding facility and zoo animals receiving systemic antibiotics. Stool samples and paw swabs were collected from dogs who attended a day boarding facility. Stool samples were also collected from zoo animals starting systemic antibiotics. Finally, environmental samples were collected from nearby public parks. Stool samples and swabs were incubated anaerobically in enrichment broth for C. difficile growth, PCR was done to confirm presence of toxin genes, and PCR ribotyping was performed for strain characterization. During the study period, 136 dog stool samples were obtained, the paws of 16 dogs were swabbed, and 250 environmental swabs from surrounding public parks were obtained. Twenty-three of 136 dog stool samples (17%) and 9 of 16 dog paws sampled (56%) grew toxigenic C. difficile. One hundred and four stool samples from 49 zoo animals were collected of which 19 (18%) grew toxigenic C. difficile. Rates of toxigenic C. difficile colonization increased significantly during antibiotic therapy (33%) and then returned to baseline during the follow-up (11%) period (p = 0.019). Fifty-five of 250 environmental swabs from public parks (22%) grew toxigenic C. difficile. Ribotypes associated with human disease including 106 and 014-020 were isolated from all sources. This study demonstrated a high rate of toxigenic C. difficile colonization in domestic dogs and zoo animals with ribotypes similar to those causing human disease. These results demonstrate the relationship between humans, animals, and the environment in the dissemination of spores.

Development of a risk prediction model for hospital-onset Clostridium difficile infection in patients receiving systemic antibiotics

BACKGROUND

Clostridium difficile infection (CDI) is recognized as a significant challenge in health care. Identification of high-risk individuals is essential for the development of CDI prevention strategies. The objective of this study was to develop an easily implementable risk prediction model for hospital-onset CDI in patients receiving systemic antimicrobials.

METHODS

This retrospective, case-control, multicenter study included adult patients admitted to Novant Health Forsyth Medical Center and Novant Health Presbyterian Medical Center from July 1, 2015, to July 1, 2017, who received systemic antibiotics. Cases were subjects with hospital-onset CDI; controls were subjects without a CDI diagnosis. Cases were matched 1:1 with controls by admitted medical unit type. Variables significantly associated with CDI were incorporated into a multivariate analysis. A logistic regression model was used to formulate a point-based risk prediction model. Positive predictive value, negative predictive value, sensitivity, specificity, and accuracy were determined at various point cutoffs of the model. A receiver operating characteristic-area under the curve was created to assess the discrimination of the model.

RESULTS

A total of 200 subjects (100 cases and 100 controls) were included. Most patients were Caucasian and female. Risk factors for CDI identified and incorporated into the model included age ≥70 years (adjusted odds ratio, 1.89; 95% confidence interval 1.05-3.43; P = .0326) and recent hospitalization in the past 90 days (adjusted odds ratio, 3.55; 95% confidence interval 1.90-6.83; P < .0001). Sensitivity and specificity were 76% and 49%, respectively, for scores ≥2 and 20% and 93%, respectively, for a score of 6. Diagnostic performance of various score cutoffs for the model indicated that a score ≥2 was associated with the highest accuracy (63%). The receiver operating characteristic-area under the curve was 0.7.

DISCUSSION

We developed a simple-to-implement hospital-onset CDI risk model that included only independent risks that can be obtained immediately on presentation to the health care facility. Despite this, the model had fair discriminatory power. Similar risk factors were found in previously developed models; however, the utility of these models is limited owing to the difficulty of assessing other included risk factors and the inclusion of risk factors that cannot be evaluated until the patient is discharged from the health care facility.

CONCLUSIONS

Identification of hospitalized patients who are receiving systemic antibiotics, are ≥70 years old, and were recently admitted to the hospital in the past 90 days may allow for an easily implementable hospital-onset CDI risk prevention strategy.