Risk prediction for 30-day mortality among patients with Clostridium difficile infections: a retrospective cohort study

Reducing Clostridioides difficile Infections in a Medical Intensive Care Unit: A Multimodal Quality Improvement Initiative

BACKGROUND

Clostridioides difficile (C. diff) infection causes significant morbidity for hospitalized patients. A large medical intensive care unit had an increase in C. diff infection rates.

OBJECTIVES

The aim of this project was to reduce the C. diff polymerase chain reaction (PCR) test positivity rate and the rate of C. diff PCR tests ordered. Rates were compared between preintervention (July 2017 to December 2019) and postintervention (January 2021 to December 2022) timeframes.

METHODS

Unit leadership led a robust quality improvement project, including use of quality improvement tools such as A3, Gemba walks, and plan-do-study-act cycles. Interventions were tailored to the barriers identified, including standardization of in-room supply carts; use of single-packaged oral care kits; new enteric precautions signage; education to staff, providers, and visitors; scripting for patients and visitors; and use of a C. diff testing algorithm. Statistical process control charts were used to assess for improvements.

RESULTS

The average rate of C. diff PCR test positivity decreased from 34.9 PCR positive tests per 10 000 patient days to 12.3 in the postintervention period, a 66% reduction. The average rate of PCR tests ordered was 28 per 1000 patient days in the preintervention period; this decreased 44% to 15.7 in the postintervention period.

DISCUSSION

We found clinically significant improvements in the rate of C. diff infection and PCR tests ordered as a result of implementing tailored interventions in a large medical intensive care unit. Other units should consider using robust quality improvement methods and tools to conduct similar initiatives to reduce patient harm and improve care and outcomes.

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.

Gray level co-occurrence matrix and wavelet analyses reveal discrete changes in proximal tubule cell nuclei after mild acute kidney injury

Acute kidney injury (AKI) relates to an abrupt reduction in renal function resulting from numerous conditions. Morbidity, mortality, and treatment costs related to AKI are relatively high. This condition is strongly associated with damage to proximal tubule cells (PTCs), generating distinct patterns of transcriptional and epigenetic alterations that result in structural changes in the nuclei of this epithelium. To this date, AKI-related nuclear chromatin redistribution in PTCs is poorly understood, and it is unclear whether changes in PTC chromatin patterns can be detected using conventional microscopy during mild AKI, which can progress to more debilitating forms of injury. In recent years, gray level co-occurrence matrix (GLCM) analysis and discrete wavelet transform (DWT) have emerged as potentially valuable methods for identifying discrete structural changes in nuclear chromatin architecture that are not visible during the conventional histopathological exam. Here we present findings indicating that GLCM and DWT methods can be successfully used in nephrology to detect subtle nuclear morphological alterations associated with mild tissue injury demonstrated in rodents by inducing a mild form of AKI through ischemia-reperfusion injury. Our results show that mild ischemic AKI is associated with the reduction of local textural homogeneity of PTC nuclei quantified by GLCM and the increase of nuclear structural heterogeneity indirectly assessed with DWT energy coefficients. This rodent model allowed us to show that mild ischemic AKI is associated with the significant reduction of textural homogeneity of PTC nuclei, indirectly assessed by GLCM indicators and DWT energy coefficients.

Performance of Clostridioides difficile infection severity scores and risk factors related to 30-day all-cause mortality in patients with cancer

PURPOSE

There are currently no standard definitions for assessing the severity of Clostridioides difficile infection (CDI) in cancer patients. We evaluated the performance of scoring systems for severity and analyzed risk factors for mortality in a cancer cohort.

METHODS

We conducted an observational study in patients with cancer and CDI. We calculated the incidence of hospital-onset (HO-CDI) and community-onset health-care facility associated (CO-HCFA-CDI) episodes. We classified severity using five prognostic scales and calculated sensitivity, specificity, positive (PPV), and negative predictive values (NPV) for mortality and intensive care unit (ICU) admission. In addition, multivariate regression was performed to assess variables associated with mortality.

RESULTS

The HO-CDI and CO-HCFA-CDI incidence rates were 3.7 cases/10,000 patient-days and 1.9 cases/1,000 admissions, respectively. ESCMID criteria showed the higher sensitivity (97%, 95% CI; 85-100%) and NPV (98%, 95% CI; 85-100%), while ATLAS (≥ 6 points) had the highest specificity (95%, 95% CI; 90-98%) for 30-day all-cause mortality; similar performance was observed for ICU admission. Characteristics associated with fatal outcome were neutropenia (≤ 100 cells/ml) (aOR; 3.03, 95% CI; 1.05-8.74, p = 0.040), male gender (aOR; 2.90, 95% CI; 1.08-7.80, p = 0.034), high serum creatinine (aOR; 1.71, 95% CI; 1.09-2.70, p = 0.020), and albumin (aOR; 0.17, 95% CI; 0.07-0.42, p < 0.001).

CONCLUSIONS

Some of the current scales may not be appropriate to discriminate severity in patients with cancer. The variables in this study associated with unfavorable outcomes could be evaluated in prospective studies to develop prognostic scores that identify susceptible patients, especially in immunocompromised populations.

Early Prognostic Stratification of Clostridioides difficile Infection in the Emergency Department: The Role of Age and Comorbidities

Clostridioides difficile infection (CDI) represents a significant cause of morbidity and mortality, mainly in older and frail subjects. Early identification of outcome predictors, starting from emergency department (ED) admission, could help to improve their management. In a retrospective single-center study on patients accessing the ED for diarrhea and hospitalized with a diagnosis of CDI infection, the patients’ clinical history, presenting symptoms, vital signs, and laboratory exams at ED admission were recorded. Quick sequential organ failure assessments (qSOFA) were conducted and Charlson’s comorbidity indices (CCI) were calculated. The primary outcomes were represented by all-cause in-hospital death and the occurrence of major cumulative complications. Univariate and multivariate Cox regression analyses were performed to establish predictive risk factors for poor outcomes. Out of 450 patients, aged > 81 years, dyspnea at ED admission, creatinine > 2.5 mg/dL, white blood cell count > 13.31 × 109/L, and albumin < 30 µmol/L were independently associated with in-hospital death and major complications (except for low albumin). Both in-hospital death and major complications were not associated with multimorbidity. In patients with CDI, the risk of in-hospital death and major complications could be effectively predicted upon ED admission. Patients in their 8th decade have an increased risk independent of comorbidities.

Capturing the environment of the Clostridioides difficile infection cycle

Clostridioides difficile (formerly Clostridium difficile) infection is a substantial health and economic burden worldwide. Great strides have been made over the past several years in characterizing the physiology of C. difficile infection, particularly regarding how gut microorganisms and their host work together to provide colonization resistance. As mammalian hosts and their indigenous gut microbiota have co-evolved, they have formed a complex yet stable relationship that prevents invading microorganisms from establishing themselves. In this Review, we discuss the latest advances in our understanding of C. difficile physiology that have contributed to its success as a pathogen, including its versatile survival factors and ability to adapt to unique niches. Using discoveries regarding microorganism-host and microorganism-microorganism interactions that constitute colonization resistance, we place C. difficile within the fiercely competitive gut environment. A comprehensive understanding of these relationships is required to continue the development of precision medicine-based treatments for C. difficile infection.

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.

Risk Scoring System of Mortality and Prediction Model of Hospital Stay for Critically Ill Patients Receiving Parenteral Nutrition

Predicting the clinical progression of intensive care unit (ICU) patients is crucial for survival and prognosis. Therefore, this retrospective study aimed to develop the risk scoring system of mortality and the prediction model of ICU length of stay (LOS) among patients admitted to the ICU. Data from ICU patients aged at least 18 years who received parenteral nutrition support for ≥50% of the daily calorie requirement from February 2014 to January 2018 were collected. In-hospital mortality and log-transformed LOS were analyzed by logistic regression and linear regression, respectively. For calculating risk scores, each coefficient was obtained based on regression model. Of 445 patients, 97 patients died in the ICU; the observed mortality rate was 21.8%. Using logistic regression analysis, APACHE II score (15–29: 1 point, 30 or higher: 2 points), qSOFA score ≥ 2 (2 points), serum albumin level < 3.4 g/dL (1 point), and infectious or respiratory disease (1 point) were incorporated into risk scoring system for mortality; patients with 0, 1, 2–4, and 5–6 points had approximately 10%, 20%, 40%, and 65% risk of death. For LOS, linear regression analysis showed the following prediction equation: log(LOS) = 0.01 × (APACHE II) + 0.04 × (total bilirubin) − 0.09 × (admission diagnosis of gastrointestinal disease or injury, poisoning, or other external cause) + 0.970. Our study provides the mortality risk score and LOS prediction equation. It could help clinicians to identify those at risk and optimize ICU management.

Validation of the SHEA/IDSA severity criteria to predict poor outcomes among inpatients and outpatients with Clostridioides difficile infection

OBJECTIVE

To determine whether the Society for Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of America (IDSA) Clostridioides difficile infection (CDI) severity criteria adequately predicts poor outcomes.

DESIGN

Retrospective validation study.

SETTING AND PARTICIPANTS

Patients with CDI in the Veterans’ Affairs Health System from January 1, 2006, to December 31, 2016.

METHODS

For the 2010 criteria, patients with leukocytosis or a serum creatinine (SCr) value ≥1.5 times the baseline were classified as severe. For the 2018 criteria, patients with leukocytosis or a SCr value ≥1.5 mg/dL were classified as severe. Poor outcomes were defined as hospital or intensive care admission within 7 days of diagnosis, colectomy within 14 days, or 30-day all-cause mortality; they were modeled as a function of the 2010 and 2018 criteria separately using logistic regression.

RESULTS

We analyzed data from 86,112 episodes of CDI. Severity was unclassifiable in a large proportion of episodes diagnosed in subacute care (2010, 58.8%; 2018, 49.2%). Sensitivity ranged from 0.48 for subacute care using 2010 criteria to 0.73 for acute care using 2018 criteria. Areas under the curve were poor and similar (0.60 for subacute care and 0.57 for acute care) for both versions, but negative predictive values were >0.80.

CONCLUSIONS

Model performances across care settings and criteria versions were generally poor but had reasonably high negative predictive value. Many patients in the subacute-care setting, an increasing fraction of CDI cases, could not be classified. More work is needed to develop criteria to identify patients at risk of poor outcomes.