Multi-step Testing Research Articles

High Prevalence of Multistep Algorithms in Diagnostic Clostridioides difficile Laboratory Testing.

Laboratory testing practices for diagnosis of Clostridioides difficile infection (CDI) have evolved in response to published guidelines, availability of highly sensitive nucleic acid amplification tests (NAATs), perceived problems with the specificity of NAATs, and CDI reporting requirements. To assess the current state of laboratory practice for diagnostic CDI testing. An optional 8-item supplemental questionnaire was distributed in December 2019 to the 1374 laboratories participating in the College of American Pathologists C difficile Detection (CDF) proficiency testing program challenge CDF-C. Of 1374 CDF-C participants, 1160 (84.4%) responded, predominantly representing laboratories based in the United States (1077 of 1160; 92.8%). The majority reported using a multistep testing algorithm (684 of 1159; 59.0%). Initial testing with a glutamate dehydrogenase and toxin A/B combination test followed by NAAT for discrepant results was the most common testing method (360 of 1146; 31.4%). NAAT alone (299 of 1146; 26.1%) was next, then NAAT followed by an assay that included toxin A/B enzyme immunoassay if NAAT is positive (258 of 1146; 22.5%). Only 5.4% (62 of 1146) reported using toxin A/B immunoassay alone. Most respondents (1093 of 1131; 96.6%) reported rejecting CDI tests on formed stool, but rejection of CDI testing in pediatric patients was uncommon (211 of 1131; 18.7%). Rejection of CDI testing in patients using laxatives was reported more often by US-based respondents (379 of 1054 [36.0%] versus 9 of 77 [11.7%], P < .001). Multistep algorithms for CDI diagnosis are widely used in line with published recommendations. Most respondents reported rejection of formed stool for CDI testing, but few reported rejection of testing in infants and patients taking laxatives, suggesting these may be areas of opportunity for laboratories to pursue in improving CDI testing practices.

Clinical Characteristics and Cycle Thresholds Among Discordant and True Positive Test Results for Clostridiodes difficile

Background: The diagnosis of Clostridioides difficile infection (CDI) is challenging. Despite guideline-directed, multistep testing algorithms and diagnostic stewardship, the treatment of C. difficile colonization persists. The testing algorithm at our system utilizes an initial real-time PCR test (PCR) for Toxin B gene, which if positive, reflexes to an enzyme immunoassay (EIA) for detecting Toxins A and B. Discordant results (PCR +/EIA -) are suggestive of colonization, but the majority of patients with discordant results are treated for CDI. Correlation of C. difficile EIA B polymerase chain reaction (PCR) cycle thresholds (Ct) with the presence of free EIA and disease severity has been observed, but the ability to use Ct in the decision to treat patients with discordant results is unclear. Our study assesses if Ct values and other clinical characteristics favor treatment in select patients with discordant Methods: A retrospective chart review was performed of adult patients (≥ 18-year-old) with positive C. difficile PCR results that were admitted to our health system between June 01 and August 31, 2023. C. difficile PCR and Ct results were obtained by Cepheid GeneXpert and Toxin A and B EIA results were obtained by Meridian Bioscience Immunocard. Patients with discordant (PCR+/EIA) and true positive (PCR+/EIA+) results were compared. We assessed demographics, past medical history, clinical characteristics, severity of illness, PCR Ct values, treatment, and clinical outcomes including: 30-day all-cause mortality and re-admission, and 60-day CDI repeat testing and treatment. Results Of the 122 patients identified, 89 patients had discordant results and 43 had true positive Results: Severity of illness and other clinical and laboratory characteristics were similar between both groups. Mean Ct values were significantly lower for true positive results compared to discordant results, 24.28 vs 29.27, respectively (p26 (p=.08). Of the patients with discordant results, 73 completed treatment for CDI and no difference in clinical outcomes was observed compared to patients with discordant results that were not treated. Conclusion Ct values were lower among patients with true positive results compared to patients with discordant Conclusion: There were no statistically significant different rates of severe or fulminant CDI among patients with discordant results and Ct values &lt; 26, although this finding may be limited by sample size and Ct may be helpful in deciding which discordant patients to treat.

Optimizing energy storage plant discrete system dynamics analysis with graph convolutional networks

Addressing the challenges of suboptimal model performance and excessive parameters and operations in the optimization of energy storage power plants utilizing Graph Convolutional Network (GCN), this paper introduces a novel approach – the packet-switched graph convolutional network. Initially, a GCN extreme learning machine is established. Drawing inspiration from this solid foundation, we have innovatively crafted a group exchange graph convolution module. This module leverages group graph convolution techniques to amalgamate unique node feature information, tailored to diverse topology graph matrices based on various groupings. This innovative approach ensures that information flows freely and effectively among distinct groupings. Furthermore, we have designed a cutting-edge timing depth separation convolution module, comprising two innovative components. The first component introduces timing depth separation convolution, revolutionizing the original timing convolution module. The second component, the packet-switching graph convolutional network, revolutionizes the time sequence depth separation convolution process. It achieves this by employing 1 × 1 convolutional layers between different feature fusion packets, enabling seamless information exchange between distinct packets. Experimental results demonstrate the efficacy of the proposed model, with root mean square error (RMSE) metrics and root mean square error (MAE) metrics for single-step prediction reaching 46.08 and 26.22 at 60 min, respectively. In multi-step testing, the proposed model exhibits a 14.71 % reduction in RMSE error at the 15-min scale and a 9.29 % reduction at the 60-min scale compared to the benchmark model. This performance improvement enhances the operational efficiency and reliability of the energy storage plant, particularly under dynamic changes in the time series.

672. Impact of Multistep Testing Algorithm on Hospital Acquired Clostridioides difficile Infection Rates

Abstract Background Clostridioides difficile infection (CDI) is one of the leading causes of hospital-acquired (HA) infections. Clinically distinguishing true CDI versus colonization is challenging. Our center previously used a polymerase chain reaction (PCR) assay as a standalone test for diagnosing CDI. While PCR is very sensitive for diagnosing CDI, it cannot distinguish between CDI and asymptomatic colonization. A multistep testing algorithm, which consists of an initial C. difficile PCR test followed by a reflex enzyme immunoassay (EIA) for glutamate dehydrogenase (GDH) and Toxin A/B testing, was implemented in our institution. We conducted this study to determine the rates of HA-CDI and C. difficile colonization based on laboratory results. Methods This retrospective observational study was conducted at Allegheny General Hospital (Pittsburgh, PA, US). Patients with a positive C. difficile PCR assay at day 3 or later from admission date were included for analysis. The pre-intervention period was from August 2021 to February 2022 and post-intervention period was from August 2022 to February 2023. Before the intervention, results for C. difficile testing were reported as PCR positive (PCR+) or negative (PCR-). On July 2022, a multistep testing algorithm was implemented with an initial C. difficile PCR assay; if results were positive, a reflex EIA for GDH and Toxin A/B testing was performed and resulted as follows: Figure 1. The HA-CDI rates before and after implementation of a multistep testing algorithm were compared. Results A total of 112 unique patients were included. HA-CDI in the post intervention period decreased by 53% after the intervention (N=57 [pre-intervention] versus N=26 [post-intervention]; P &amp;lt; 0.001). During the post-intervention period, there were 55 PCR+ C. difficile assays, of which 29 (53%) were resulted as "indeterminate, likely C. difficile colonization." Of the 29 indeterminate results, 23 (79%) still received CDI therapy. Conclusion Our study demonstrated that a multistep C. difficile testing algorithm significantly reduced the rates of HA-CDI in our institution. We found that the majority of patients still received CDI therapy despite having a negative EIA toxin result. We plan to analyze the clinical impact of this multistep testing algorithm in a follow-up study. Disclosures Thomas L. Walsh, MD, Accelerate Diagnostics: Advisor/Consultant

Where Did I Go Wrong with My Model? Ten Tips for Getting Results in SEM

Those new to structural equation modeling (SEM) often encounter problems with convergence, software errors, or poor fitting models. Some basic suggestions are offered to help reduce these problems and avoid some common error messages encountered when first testing models. The tips concern initial data management steps, specification of latent variables, avoidance of factor identification problems, special precautions when estimating means, addressing poor measurement model fit, using multistep testing, fitting full structural models, attentiveness to interpretation pitfalls, and troubleshooting software warnings and errors. The advice provided is intended to help save time, effort, and trials and tribulations often encountered by beginner modelers.

10. Capture-based transcriptome sequencing (RNA-Seq) and optical genome mapping (OGM) enhance detection of newly described molecular subtypes of pediatric B-lymphoblastic leukemia (B-ALL)

Molecular subtypes of pediatric B lymphoblastic leukemia (B-ALL) discovered in recent years by comprehensive genomic profiling are increasingly becoming essential determinants of treatment, but frequently remain undetected by routine clinical assays. Serial multi-step testing at our institution [consisting of karyotyping, FISH, Chromosomal Microarray and a custom next-generation sequencing panel (OncoKids®)], fails to detect primary genetic drivers in approximately 15% of B-ALL cases. To address this gap, we investigated whether capture-based transcriptome sequencing (RNA-Seq) and optical genome mapping (OGM) could detect molecular subtypes of B-ALL which remain unidentified by the current multi-modal assessment. RNASeq was performed on 53 banked B-ALL samples with unknown oncogenic drivers. A subtype-defining abnormality was identified in 16/53 cases (30%). These included 12 known fusions (IGH::DUX4 (3 cases), MEF2D::BCL9 (2), and 1 each of MEF2D::SS18, MEF2D::FOXJ2, EP300::ZNF384, TCF3::PBX1, SPTBN1::PDGFRB, ACIN1::NUTM1 and IGH::CEBPA), and 4 previously unreported fusions (RBM26::JAK2, STRBP::JAK2, PAX5::HIPK3 and ETV6::MFN2). OGM was completed for 19 B-ALL cases, either in house or at the Bionano Genomics Service Laboratory. It identified the subtype in 6/19 cases (31%), revealing a known fusion in 3 cases (MEF2D::FOXJ2, MEF2D::SS18 and SPTBN1::PDGFRB), and a novel fusion in 3 cases (RBM26::JAK2, STRBP::JAK2 and PAX5::HIPK3). Among the 19 cases tested by both methods, 12 were negative, 6 had concordant abnormalities, and one showed a TCF3::PBX1 fusion by RNAseq but was negative by OGM. While OGM revealed the nature of genomic rearrangements resulting in abnormal fusions and detected secondary structural abnormalities, RNAseq confirmed expression of detected fusions and allowed base-resolution mapping of fusion junctions. The majority of the known and novel fusions detected in this study define specific subtypes of B-ALL, have established prognostic significance and/or predict response to targeted treatments. Our pilot study thus shows clinical utility, discovery potential of, and high concordance between OGM and RNAseq, and highlights complementarity between the two assays.

A multistep in vitro hemocompatibility testing protocol recapitulating the foreign body reaction to nanocarriers

The development of drug nanocarriers based on polymeric, lipid and ceramic biomaterials has been paving the way to precision medicine, where the delivery of poorly soluble active compounds and personalized doses are made possible. However, the nano-size character of these carriers has been demonstrated to have the potential to elicit pathways of the host response different from those of the same biomaterials when engineered as larger size implants and of the drugs when administered without a carrier. Therefore, a specific regulatory framework needs to be made available that can offer robust scientific insights and provide safety data by reliable tests of these novel nano-devices. In this context, the present work presents a multistep protocol for the in vitro assessment of the hemocompatibility of nanocarriers of different physicochemical properties. Poly (ethyl butyl cyanoacrylate) nanoparticles and lipid-based (LipImage™ 815) nanoparticles of comparable hydrodynamic diameter were tested through a battery of assays using human peripheral blood samples and recapitulating the main pathways of the host response upon systemic administration; i.e., protein interactions, fibrinogen-platelet binding, cytotoxicity, and inflammatory response. The data showed the sensitivity and reproducibility of the methods adopted that were also demonstrated to determine individual variability as well as to discriminate between activation of pathways of inflammation and unintended release of inflammatory signaling caused by loss of cell integrity. Therefore, this multistep testing is proposed as a reliable protocol for nanoparticle development and emerging regulatory frameworks.Graphical abstract

Diagnostic Utility of Multimodal Genomic Profiling for Molecular Classification and MRD Assessment in Adult B-Cell Acute Lymphoblastic Leukemia

Genomic markers define molecular subtypes and measurable residual disease (MRD) targets in B-cell acute lymphoblastic leukemia/lymphoma (B-ALL) and are essential determinants of treatment. Current diagnostic approaches typically involve serial multi-step testing utilizing conventional cytogenetics (CC)/FISH and molecular genetic (RT-qPCR, MLPA, clonality PCR, NGS panel) techniques which are time and sample consuming and ultimately may not adequately identify genomically complex B-ALL subtypes. In contrast, single-step comprehensive genomic profiling by whole genome and whole transcriptome sequencing (WGS/WTS) may be more efficient for the molecular classification of established and newly described entities which are of increasing therapeutic relevance. We have instituted a multimodal platform for molecular testing in B-ALL performing WGS/WTS in parallel with deep NGS-based immunoglobulin (IG) rearrangement MRD and exploratory DNA-breakpoint based MRD assays. We aimed to determine the utility of this approach for subtype classification compared to a standard-of-care diagnostic approach of CC/FISH testing.Forty-two consecutive adult patients underwent both standard-of-care diagnostic testing and WGS/WTS. 20/42 (48%) patients had an abnormal CC/FISH result supporting classification into recognized molecular subgroups. WGS/WTS assessment incorporating somatic coding and non-coding mutations, structural variants, fusions, copy number abnormalities and gene expression subtype prediction (ALLSorts, https://github.com/Oshlack/ALLSorts) was performed with concordant results in all 20 patients. 16/22 patients that were unclassified by CC/FISH were successfully reclassified by WGS/WTS including subtypes enriched for cryptic rearrangements (Ph-like, DUX4, MEF2D) and groups characterized by heterogeneous genomic alterations or a distinctive gene expression signature (PAX5alt, ZEB2/CEBP). A low hypodiploid karyotype was observed in two cases with an apparently normal karyotype by CC. The six patients who remained without a subtype defining driver genetic alteration after comprehensive testing frequently harbored novel IGH translocations or a Ph-like expression signature but without a described fusion.In order to understand the relative contribution from WGS versus WTS, analysis of 36 patients was performed using a truth classification. WGS and WTS produced equivalent classifications for 22 cases. Two cases were based solely on WGS findings (iAMP21 and ZEB2/CEBP) and three cases were based solely on WTS findings (DUX4). Importantly the combination of both WGS and WTS was critical to correctly classify nine cases (Ph-like and PAX5alt).MRD was assessed by a sensitive NGS assay to IG rearrangements (Adaptive Biotechnologies) and by quantitative probe-based droplet digital PCR (ddPCR) assays designed to structural rearrangement DNA breakpoints from genome data (analytical sensitivity 10 -4). Patient-specific ddPCR assays were designed to eight structural variants (KMT2A and IGH translocations, and IKZF1 deletions) in seven patients and assessed in 36 remission samples with parallel testing by multiparametric flow cytometry (MFC). Concordant MFC and ddPCR was observed in 30/36 samples (19 MRD pos, 11 MRD neg). Discordances included two MRD pos by MFC-only and four MRD pos by ddPCR-only; the latter often occurring in the setting of antigen directed therapy or in ALL with a less informative immunophenotype, demonstrating the additional utility of non-MFC based MRD assessment in specific clinical settings. 27/42 patients in our cohort had ≥1 genomic structural rearrangement identified by WGS that could be used for patient-specific MRD monitoring to complement existing MRD assessment.In conclusion WGS/WTS provided a molecular subtype classification in 86% of our cohort compared to 48% by standard-of-care diagnostic testing highlighting that CC/FISH alone is inadequate for contemporary molecular classification of B-ALL, which may have implications for treatment decisions. Importantly, the combination of WGS and WTS was superior to WGS-only or WTS-only for correct molecular subtype assignment. This approach has the potential to improve risk assessment in adult B-ALL and the routine feasibility, improvement in clinical outcomes and health economic impact warrant further assessment. DisclosuresBajel: Abbvie, Amgen, Novartis, Pfizer: Honoraria; Amgen: Speakers Bureau. Dickinson: Janssen: Consultancy, Honoraria; Amgen: Honoraria; Celgene: Research Funding; Gilead Sciences: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Research Funding, Speakers Bureau; Takeda: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Other: travel, accommodation, expenses, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau. Tiong: Servier: Consultancy, Speakers Bureau; Amgen: Speakers Bureau; Pfizer: Consultancy.

Development and clinical validation of an automated cell cytotoxicity neutralization assay for detecting Clostridioides difficile toxins in clinically relevant stools samples

ObjectivesTo improve the diagnostic accuracy of Clostridioides difficile infection, current U.S. and E.U. guidelines recommend multistep testing that detects the presence of C. difficile and toxin in clinically relevant stool samples to confirm active disease. An accepted gold standard to detect C. difficile toxins is the cell cytotoxicity neutralization assay (CCNA). Although highly sensitive, the traditional CCNA has limitations. One such limitation is the subjective interpretation of an analyst to recognize cytopathic effects in cultured cells exposed to a fecal sample containing toxin. To overcome this limitation, an automated CCNA was developed that replaces most human pipetting steps with robotics and incorporates CellTiterGlo® for a semi-quantitative, non-subjective measure of cell viability instead of microscopy. MethodsTo determine sample positivity and control for non-specific cytopathic effects, two thresholds were defined and validated by evaluating the sample with/without antitoxin antisera (sample-antitoxin/sample + antitoxin): 1) a >70% cell viability threshold was validated with samples containing anti-toxin, and 2) a >1.2-fold difference cut-off where sample results above the cut-off are considered positive. ResultsAssay validation demonstrated excellent accuracy, precision, and sample linearity with an LOD of 126.9 pg/mL toxin-B in stool. The positivity cut-offs were clinically validated by comparing 322 diarrheal stool sample results with those run in a predicate, microscopic readout-based CCNA. The automated CCNA demonstrated 96% sensitivity and 100% specificity compared with the predicate CCNA. Conclusions: Overall, the automated CCNA provides a specific, sensitive, and reproducible tool to support determination of CDI epidemiology or the efficacy of interventions such as vaccines.

Impact of Two-Step Testing Algorithm on Reducing Hospital-Onset Clostridioides difficile Infections

Clostridioides difficile infection (CDI) is one of the leading causes of hospital–onset infections. Clinically distinguishing true CDI versus colonization with C. difficile is challenging and often requires reliable and rapid molecular testing methods. At our academic center, we implemented a 2-step testing algorithm to help identify true CDI cases. The University of Mississippi Medical Center is a 700+ bed academic facility located in Jackson, Mississippi. Hospital-onset (HO) CDI was defined based on NHSN Laboratory Identified (LabID) event as the last positive C. difficile test result performed on a specimen using a multistep testing algorithm collected &gt;3 calendar days after admission to the facility. HO-CDI data were collected from all inpatient units except the NICU and newborn nursery. HO-CDI outcomes were assessed based on standardized infection ratio (SIR) data. In May 2020, we implemented a 2-step testing algorithm (Figure 1). All patients with diarrhea underwent C. difficile PCR testing. Those with positive C. difficile PCR test were reflexed to undergo enzyme immunoassay (EIA) glutamate dehydrogenase antigen (Ag) testing and toxin A and B testing. The final results were reported as colonization (C. difficile PCR+/EIA Ag+/Toxin A/B−) or true CDI case (C. difficile PCR+/EIA +/Toxin A/B +) or negative (C. difficile PCR−). All patients with colonization or true infection were placed under contact isolation precautions until diarrhea resolution for 48 hours. During the preintervention period (October 2019–April 2020), 25 HO-CDI cases were reported compared to 8 cases in the postintervention period (June 2020–December 2020). A reduction in CDI SIR occurred in the postintervention period (Q3 2020–Q4 2020, SIR 0.265) compared to preintervention period (Q4 2019–Q1 2020, SIR 0.338) (Figure 2). We successfully reduced our NHSN HO-CDI SIR below the national average after implementing a 2-step testing algorithm for CDI. The 2-step testing algorithm was useful for antimicrobial stewardship to guide appropriate CDI treatment for true cases and for infection prevention to continue isolation of infected and colonized cases to reduce the spread of C. difficile spores.Funding: NoDisclosures: None

The 'Multi-step' to Success: Key Points for C. Diff Labid Reduction

Background Polymerase Chain Reaction (PCR) testing for Clostridioides difficle (C. diff) does not differentiate colonization versus active disease. This healthcare system sought to implement a multi-step testing platform with PCR and toxin testing to distinguish active C diff infections versus colonization and achieve Laboratory –identified (LabID) rate lower than 4.59/10,000 patient days. Methods The hospital healthcare system C. diff database was queried for tests between 2019-2020. Selected tests were associated with adult inpatient hospitalization and National Safety Network (NHSN) LabID criteria (loose stools, day four of admission). Stool samples collected after January 2020 were tested using C. diff multi-step testing platform. Results Multi-step testing dramatically reduced LabID C diff rates from 4.59 in 2019 to 1.60 in 2020 across the healthcare system. Multi-step testing excluded 78 positive PCR with negative toxin results January-October 2020 from NHSN LabID submission. Conclusions The multi-step testing platform contributes to a systemwide 65% reduction in LabID C. diff cases reported to NHSN by differentiating between colonization and active infection. In turn, this leads to correctly identifying, isolating, and treatment of patients. In addition, identification of appropriate interventions and targeted resource allocation allows healthcare systems to move the needle closer to zero for this healthcare associated infection.

Daily Forecasting for Antam's Certified Gold Bullion Prices in 2018-2020 using Polynomial Regression and Double Exponential Smoothing

Gold investment is currently a trend in society, especially the millennial generation. Gold investment for the younger generation is an advantage for the future. Gold bullion is often used as a promising investment, on other hand, the digital gold is available which it is stored online on the gold trading platform. However, any investment certainly has risks, and the price of gold bullion fluctuates from day to day. People who invest in gold hopes to benefit from the initial purchase price even if they must wait up to five years. The problem is how they can notice the best time to sell and buy gold. Therefore, this research proposes a forecasting approach based on time series data and the selling of gold bullion prices per gram in Indonesia. The experiment reported that Holt’s double exponential smoothing provided better forecasting performance than polynomial regression. Holt’s double exponential smoothing reached the minimum of Mean Absolute Percentage Error (MAPE) 0.056% in the training set, 0.047% in one-step testing, and 0.898% in multi-step testing.

Two-step Testing for Clostridioides Difficile is Inadequate in Differentiating Infection From Colonization in Children.

Recent Infectious Disease Society of America guidelines recommend multistep testing algorithms to diagnose Clostridioides difficile infection (CDI), including a combination of nucleic acid amplification-based testing (NAAT) and toxin enzyme immunoassay (EIA). The use of these algorithms in children, including the ability to differentiate between C. difficile colonization and CDI, however, has not been evaluated. We prospectively enrolled asymptomatic pediatric patients with cancer, cystic fibrosis (CF), or inflammatory bowel disease (IBD) and obtained a stool sample for NAAT testing. If positive by NAAT (colonized), EIA was performed. In addition, children with symptomatic CDI who tested positive by NAAT via the clinical laboratory were enrolled, and EIA was performed on residual stool. A functional cell cytotoxicity neutralization assay (CCNA) was also applied to stool samples from both the colonized and symptomatic cohorts. Of the 225 asymptomatic children enrolled in the study, 47 (21%) were colonized with C. difficile including 9/59 (15.5%) with cancer, 30/92 (32.6%) with CF, and 8/74 (10.8%) with IBD. An additional 41 children with symptomatic CDI were enrolled. When symptomatic and colonized children were compared, neither EIA positivity (44% vs 26%, P = 0.07) nor CCNA positivity (49% vs 45%, P = 0.70) differed significantly or were able to predict disease severity in the symptomatic cohort. Use of a multistep testing algorithm with NAAT followed by EIA failed to differentiate symptomatic CDI from asymptomatic colonization in our pediatric cohort. As multistep algorithms are moved into clinical care, the pediatric provider will need to be aware of their limitations.

Sequential introduction of a multistep testing algorithm and nucleic acid amplification testing leading to an increase in Clostridioides difficile detection and a trend toward increased strain diversity.

Most clinical microbiology laboratories have replaced toxin immunoassay (EIA) alone with multistep testing (MST) protocols or nucleic acid amplification testing (NAAT) alone for the detection of C. difficile. Study the effect of changing testing strategies on C. difficile detection and strain diversity. Retrospective study. A Veterans' Affairs hospital. Initially, toxin EIA testing was replaced by an MST approach utilizing a glutamate dehydrogenase (GDH) and toxin EIA followed by tcdB NAAT for discordant results. After 18 months, MST was replaced by a NAAT-only strategy. Available patient stool specimens were cultured for C. difficile. Restriction endonuclease analysis (REA) strain typing and quantitative in vitro toxin testing were performed on recovered isolates. Before MST (toxin EIA), 79 of 708 specimens (11%) were positive, and after MST (MST-A), 121 of 517 specimens (23%) were positive (P < .0001). Prior to NAAT-only testing (MST-B), 80 of the 490 specimens (16%) were positive by MST, and after NAAT-only testing was implemented, 67 of the 368 specimens (18%) were positive (P = nonsignificant). After replacing toxin EIA testing, REA strain group diversity increased (8, 13, 13, and 10 REA groups in the toxin EIA, MST-A, MST-B, and NAAT-only periods, respectively) and in vitro toxin concentration decreased. The average log10 toxin concentration of the isolates were 2.08, 1.88, 1.20 and 1.55 ng/mL for the same periods, respectively. MST and NAAT had similar detection rates for C. difficile. Compared to toxin testing alone, they detected increased diversity of C. difficile strains, many of which were low toxin producing.

4345 Two-step Algorithm for Clostridioides difficile is Inadequate for Differentiating Infection from Colonization in Children

OBJECTIVES/GOALS: In 2017, new guidelines recommended multi-step algorithms for CDI diagnosis, and clinical centers rapidly implemented changes despite limited pediatric data. We assessed a multi-step algorithm using NAAT followed by EIA for ability to differentiate symptomatic CDI from colonization in children. METHODS/STUDY POPULATION: We prospectively enrolled pediatric patients with cancer, cystic fibrosis, or inflammatory bowel disease who were not being tested or treated for CDI and obtained a stool sample for NAAT. If positive by NAAT (colonized), EIA was performed. Children with symptomatic CDI who tested positive by NAAT via the clinical laboratory were also enrolled and EIA performed on residual stool. A functional cell cytotoxicity neutralization assay (CCNA) was performed in addition. RESULTS/ANTICIPATED RESULTS: Of the 138 asymptomatic children enrolled, 24 (17%) were colonized. An additional 37 children with symptomatic CDI were enrolled. Neither EIA positivity (41% versus 21%, P = 0.11) or CCNA positivity (49% versus 46%, P = 0.84) were significantly different between symptomatic versus colonized children. When both EIA and CCNA were positive, children were more commonly symptomatic than colonized (33% versus 13%, P = 0.04). DISCUSSION/SIGNIFICANCE OF IMPACT: A multi-step testing algorithm with NAAT and EIA failed to differentiate symptomatic CDI from colonization in our pediatric cohort. As multi-step algorithms are moved into clinical care, pediatric providers will need to be aware of the continued limitations in diagnostic testing.

Diagnostic Stewardship for Comprehensive Gastrointestinal Pathogen Panel Tests

Syndromic gastrointestinal (GI) panels are molecular tests that evaluate stool specimens for multiple enteric pathogens simultaneously, including viruses, bacteria, and parasites. The Luminex xTAG GI panel includes 14 microbial targets and the Biofire FilmArray GI panel includes 22. The purpose of this scoping review was to describe clinical use of these two commercially available syndromic GI panels. Compared with conventional testing, syndromic panels increase the number of potential pathogens identified by two- to fivefold. Syndromic panels were associated with non-reproducible results, positive results in the absence of clinical disease, and positive results for pathogens of unclear clinical significance. Syndromic panels were less likely to provide new information when performed > 72 h after hospital admission or when repeated within 4 weeks of a previous test. Process measures or clinical outcomes related to testing were infrequently reported. Outcomes-based research is needed to determine the clinical impact of syndromic GI panels. Strategies for diagnostic stewardship that may increase the utility of GI panels include (1) development of clinical criteria for testing, (2) use of multi-step testing algorithms that start with tests for the most common organisms (Clostridium difficile and norovirus), (3) selective reporting of results, (4) reporting results through a mediator such as the infection preventionist or antibiotic stewardship pharmacist, and (5) maintenance of separate pathways for C. difficile testing.

Ultrasensitive Clostridioides difficile Toxin Testing for Higher Diagnostic Accuracy

Currently available diagnostic tests for Clostridioides difficile infection (CDI) lack specificity or sensitivity, which has led to guideline recommendations for multistep testing algorithms. Ultrasensitive assays for detection of C. difficile toxins provide measurements of disease-specific markers at very low concentrations. These assays may show improved accuracy compared to that of current testing methods and offer a potential standalone solution for CDI diagnosis, although large studies of clinical performance and accuracy are lacking.

Characterizing anecdotal claims of groundwater contamination in shale energy basins

The increased societal monitoring of unconventional oil and gas development (UD) has brought forth tremendous scrutiny over the environmental stewardship and subsequent public health impacts of surface and sub-surface activities. Concerns over groundwater quality in shale energy basins have prompted concerned citizens into monitoring UD activities for a series of qualitative parameters, and even coordinating sampling efforts for chemical analysis. Here we present a list of analytical parameters, hierarchically structured to guide concerned citizens through an efficient and cost-effective monitoring program. Utilizing this multi-step testing regime, we assessed groundwater quality from 36 private water wells involved in 19 anecdotal claims of alleged UD-related contamination across the Barnett, Eagle Ford, Haynesville, and Marcellus Shale formations in the United States. Our analytical findings aligned with the landowners' accounts of their situation in only 5 of the 36 collected samples, with several cases revealing environmental abnormalities that were unbeknownst to the landowners but likely unrelated to UD activities. These data are some of the first to assess the relationship between landowner perception and analytical determination in a cohort of highly variable anecdotal cases of alleged groundwater contamination, revealing a notable disconnect that is likely attributable to a myriad of societal and environmental factors. The analytical modalities presented here also serve as a step-wise method in a weight of evidence approach to assess the presence or absence of anthropogenic contamination under the most variable hydrogeological conditions.

2363. Implementation of a Multi-Step Diagnostic Algorithm for C. difficile Infection

BackgroundThe diagnosis of C. difficile infection (CDI) in the hospital is challenging asymptomatic colonization rates vary between 3% and 26%. Guidelines recommend multistep testing for CDI diagnosis. On July 1, 2018 a two-step testing algorithm was implemented at our institution. Positive nucleic acid amplification test (NAAT) results reflexed to a toxin enzyme immunoassay (EIA) test. The EIA test result was then used for NHSN reporting; however, both test results were visible to the clinician. Updated guidance on the interpretation of the test and treatment of CDI was released to the medical staff in July. We compared the incidence of CDI lab ID events per 1000 patient-days and the rate of C. difficile antibiotic starts before and after the implementation of the testing algorithm.MethodsA retrospective observational study was performed at an 800 bed regional medical center. CDI lab ID events between January 1 and December 31, 2018 were reviewed. Antibiotic initiation of intravenous (IV) and oral (PO) metronidazole and PO vancomycin was collected for all hospitalized patients diagnosed with C. difficile. The incidence of hospital onset (HO) and community-onset (CO) lab ID events as well as the rate of antibiotic starts were compared before and after implementation of the algorithm using a two-sided z test for proportions with an alpha of 0.05.ResultsThe incidence of HO and CO lab ID events per 1000 patient-days decreased significantly from 0.56 to 0.16 (P < 0.0001) and 1.18 to 0.3 (P < 0.0001) after implementation of the testing algorithm (Figure 1). The CDI SIR decreased from 0.729 to 0.322, (P = 0.0048). The rate of antibiotic starts per 1,000 patient-days for IV and PO Metronidazole decreased significantly from 1.1 to 0.45 (P < 0.0001) and 0.86 to 0.35 (P < 0.0001), respectively. PO Vancomycinstarts decreased from 1.51 to 1.23 (P = 0.11) (Table 1).ConclusionA two-step algorithm for diagnosing CDI decreases the overall number of HO and CO C. difficile lab ID events and decreases overall antimicrobial use for CDI. Disclosures All authors: No reported disclosures.

1982. A Diagnostic Stewardship Intervention for Clostridioides difficile: Impact of Stool Toxin Testing on Treatment of Adult Inpatients

BackgroundTesting for Clostridioides difficile infection has been the subject of recent debate. Guidelines from the Infectious Diseases Society of America now support the addition of a stool toxin test to a positive nucleic acid amplification test (NAAT) as part of a multi-step testing algorithm. In November 2017, the University of Kentucky HealthCare system added stool toxin testing to any specimen positive for C. difficile by NAAT. This change was accompanied by face to face education with provider groups and clinical decision support in the form of interpretive verbiage added to the results that are reported into the electronic record. The objective of this study was to assess whether this diagnostic stewardship intervention made an impact on C. difficile treatmentMethodsWe performed a retrospective review of adult patients admitted to UK HealthCare from November 1, 2017 through October 31, 2018 who tested positive by NAAT but negative by stool toxin test to determine whether or not they were treated. We also assessed treatment by service line to see whether there were treatment differences among these groups. A cost analysis was also performed.ResultsA total of 300 adult inpatients were positive for C. difficile by NAAT during the study period with 71% (213 patients) having a negative stool toxin test. Of those, 58% (123) were never started on C. difficile therapy and an additional 14% (30) had their therapy stopped after 48 hours. Only 28% (60) of these patients received a full course of therapy. Hospital medicine had the highest rate of non-treatment at 82%. Conversely, our solid-organ and bone marrow transplant services had the lowest rate of non-treatment at 31%. Overall, this approach was associated with an estimated 1470 oral vancomycin days avoided (5,880 doses) and a cost savings of $6,278.ConclusionThe addition of stool toxin testing to NAAT combined with education and clinical decision support lead to a dramatic reduction of treatment for NAAT positive but toxin-negative patients. This form of diagnostic stewardship had a significant impact on therapy decisions and can be a powerful antimicrobial stewardship approach to decrease unnecessary treatment of C. difficile colonization.Disclosures All authors: No reported disclosures.