Clostridioides difficile Near-Patient Testing Versus Centralized Testing: A Pragmatic Cluster Randomized Crossover Trial.

BACKGROUND: Management of suspected Clostridioides difficile infection (CDI) in the hospital setting typically results in patient isolation, laboratory testing, infection control, and presumptive treatment. We investigated whether implementation of rapid near-patient testing (NPT) reduced patient isolation time, hospital length of stay (LOS), antibiotic usage, and cost. METHODS: A 2-period pragmatic cluster randomized crossover trial was conducted. Thirty-nine wards were randomized into 2 study arms. The primary outcome measure was effect of NPT on patient isolation time using a mixed-effects generalized linear regression model. Secondary outcomes examined were hospital LOS and antibiotic therapy based on a negative binomial regression model. Natural experiment (NE), intention-to-treat (ITT), and per-protocol (PP) analyses were conducted. RESULTS: During the entire study period, a total of 656 patients received NPT for CDI and 1667 received standard-of-care testing. For the primary outcome, a significant decrease of patient isolation time with NPT was observed (NE, 9.4 hours [P < .01]; ITT, 2.3 hours [P < .05]; PP, 6.7 hours [P < .1]). A significant reduction in hospital LOS was observed with NPT for short stay (NE, 47.4% [P < .01]; ITT, 18.4% [P < .01]; PP, 34.2% [P < .01]). Each additional hour delay for a negative result increased metronidazole use (24 defined daily doses per 1000 patients; P < .05) and non-CDI-treating antibiotics by 70.13 mg (P < .01). NPT was found to save 25.48 US dollars per patient when including test cost to the laboratory and patient isolation in the hospital. CONCLUSIONS: This pragmatic cluster randomized crossover trial demonstrated that implementation of CDI NPT can contribute to significant reductions in isolation time, hospital LOS, antibiotic usage, and healthcare cost. Clinical Trials Registration. NCT03857464.

Correlation of Clinical Severity With Stool Microbiome Changes in Clostridioides difficile Infection.

CONTEXT.­: Clostridioides difficile infection (CDI) is the world-leading cause of infectious nosocomial diarrhea and pseudomembranous colitis. Antibiotics are the first line of treatment against CDI despite the high likelihood of antibiotic failure and/or recurrence. More data are needed to correlate clinical variables with 16S rRNA microbiome profiles in CDI-infected patients. OBJECTIVE.­: To determine the relationship(s) between a patient's clinical factors and the stool bacteriome of CDI-positive patients and CDI-negative patients with diarrheal symptoms. DESIGN.­: This study used stool samples and clinical data from 358 patients with nosocomial diarrhea, who were divided by their CDI diagnosis (CDI-negative: n = 180; CDI-positive; n = 178). The stool bacteriome was profiled by amplicon deep sequencing of the 16S rRNA gene, followed by correlating clinical data. RESULTS.­: The stool bacteriome was significantly different by severity assessment regardless of CDI status. Phyla and species varied significantly by CDI diagnosis. Severity, defined as a serum white blood cell count greater than 15 cells/µL and/or a creatinine level greater than 1.5 mg/dL, correlated significantly with dysbiosis of the stool bacteriome profile of CDI-positive patients compared to CDI-negative patients. Serum white blood cell count was significantly higher in patients with bacterial dysbiosis, and high levels of creatinine were associated with low bacteriome diversity. CONCLUSIONS.­: Clinical severity of CDI influences the stool microbiome of infected patients. To date, this study has the largest data set comparing 16S rRNA microbiome profiles and clinical variables between CDI-infected and noninfected individuals.

Latent Class Analysis for the Diagnosis of Clostridioides difficile Infection.

BACKGROUND: Clostridioides difficile infection (CDI) is an opportunistic disease that lacks a gold-standard test. Nucleic acid amplification tests such as real-time polymerase chain reaction (PCR) demonstrate an excellent limit of detection (LOD), whereas antigenic methods are able to detect protein toxin. Latent class analysis (LCA) provides an unbiased statistical approach to resolving true disease. METHODS: A cross-sectional study was conducted in patients with suspected CDI (N = 96). Four commercial real-time PCR tests, toxin antigen detection by enzyme immunoassay (EIA), toxigenic culture, and fecal calprotectin were performed. CDI clinical diagnosis was determined by consensus majority of 3 experts. LCA was performed using laboratory and clinical variables independent of any gold standard. RESULTS: Six LCA models were generated to determine CDI probability using 4 variables including toxin EIA, toxigenic culture, clinical diagnosis, and fecal calprotectin levels. Three defined zones as a function of real-time PCR cycle threshold (Ct) were identified using LCA: CDI likely (>90% probability), CDI equivocal (<90% and >10%), CDI unlikely (<10%). A single model comprising toxigenic culture, clinical diagnosis, and toxin EIA showed the best fitness. The following Ct cutoffs for 4 commercial test platforms were obtained using this model to delineate 3 CDI probability zones: GeneXpert®: 24.00, 33.61; Simplexa®: 28.97, 36.85; Elite MGB®: 30.18, 37.43; and BD Max™: 27.60, 34.26. CONCLUSIONS: The clinical implication of applying LCA to CDI is to report Ct values assigned to probability zones based on the commercial real-time PCR platform. A broad range of equivocation suggests clinical judgment is essential to the confirmation of CDI.