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Background Meningoencephalitis continues to be a source of morbidity and mortality in the US despite vaccine development. Traditional culture-based diagnosis is time-consuming and less sensitive than molecular methods. Meningitis-encephalitis PCR panel (MEP) testing of CSF allows for rapid detection of 14 culprit microorganisms. Methods A retrospective cohort study was performed at University of Massachusetts Chan Medical School-Baystate in Springfield, MA between May 15, 2015 and May 14, 2017 on encounters among 163 individuals ranging in age from neonates to geriatric patients before and after MEP introduction for clinical practice. One cohort reflected pre-MEP availability and relied on culture and gram stain while another cohort had the MEP available and gram stain/culture. The primary outcomes were (1) MEP effect on antimicrobial de-escalation and (2) total antimicrobial days defined as sum of days on antimicrobial therapy counting each antimicrobial agent separately. Secondary outcomes were (1) length of hospital stay, (2) rate of adverse events associated with antimicrobial use, and (3) determination if adult or pediatric age interplayed with interpretation of MEP results. Results Fifty-two percent of the population was 18 years-old or younger. The most common organisms identified were parechovirus and enterovirus. There were 26 positive MEP panels and nine encounters did not de-escalate antimicrobials. Seven of the nine did not de-escalate because there was concern for sepsis or blood culture was positive. The remaining two either started or continued acyclovir for a positive MEP of HSV-2 or VZV. When the MEP resulted positive for bacteria, antimicrobials were modified. Mean time antimicrobial use was less when MEP was available (3.1 vs. 4.8 days) and length of hospitalization was similar (6.1 vs. 6.9 days). Adverse events were minimal in both groups. Identified Organisms Microorganisms identified by MEP overall, pediatric, and adult. Total Antimicrobial Days and Length of Stay by Cohort Pre-MEP and MEP available cohort distribution on total antimicrobial days and length of stay in pediatric and adult populations. Conclusion The data did identify difference in management with interpretation of the MEP for pediatrics (≤ 18 y/o) when compared to adults. Fever in a neonate, or severely ill child led to a 48 hour blood culture rule out prior to any change in antibiotics. Overall, our study showed association of MEP use with early antimicrobial de-escalation that can potentially lead to decreased length of stay and savings in healthcare costs. Disclosures All Authors: No reported disclosures.

Introduction: The ARIES® HSV 1&2 Assay is a new FDA cleared real-time PCR test for detection and differentiation of HSV-1 and HSV-2 DNA from cutaneous and mucocutaneous lesions. The test is performed on the ARIES® System, an automated sample to answer real-time PCR instrument that provides a closed system and simple workflow for performing molecular testing.Areas covered: This article reports the clinical performance of the ARIES® HSV 1&2 Assay assessed on 1963 prospectively collected specimens. Assay sensitivities were 91.1–95% (cutaneous) and 97–98.5% (mucocutaneous), and specificities were 88.8–94.2% (cutaneous) and 93.2–95.4% (mucocutaneous), as compared to the ELVIS® HSV test system.Expert commentary: Detection of HSV DNA by PCR is rapid and more sensitive than traditional culture and immunoassay methods and is being widely adopted in many laboratory settings. Sample to answer molecular platforms like ARIES® will enable routine and non-molecular labs to perform sensitive and rapid molecular t...

BACKGROUND Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are comprehensive and specific with respect to the pathogen but are rapid in reporting the data. It has proven difficult to implement these requirements on a large scale while maintaining patient privacy. OBJECTIVE The aim of this study was to demonstrate the automated export, aggregation, and analysis of infectious disease diagnostic test results from clinical laboratories across the United States in a manner that protects patient confidentiality. We hypothesized that such a system could aid in monitoring the seasonal occurrence of respiratory pathogens and may have advantages with regard to scope and ease of reporting compared with existing surveillance systems. METHODS We describe a system, BioFire Syndromic Trends, for rapid disease reporting that is syndrome-based but pathogen-specific. Deidentified patient test results from the BioFire FilmArray multiplex molecular diagnostic system are sent directly to a cloud database. Summaries of these data are displayed in near real time on the Syndromic Trends public website. We studied this dataset for the prevalence, seasonality, and coinfections of the 20 respiratory pathogens detected in over 362,000 patient samples acquired as a standard-of-care testing over the last 4 years from 20 clinical laboratories in the United States. RESULTS The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks, and adenovirus and the bacterial pathogens show constant detection over the year. The dataset can also be considered in an ecological framework; the viruses and bacteria detected by this test are parasites of a host (the human patient). Interestingly, the rate of pathogen codetections, on average 7.94% (28,741/362,101), matches predictions based on the relative abundance of organisms present. CONCLUSIONS Syndromic Trends preserves patient privacy by removing or obfuscating patient identifiers while still collecting much useful information about the bacterial and viral pathogens that they harbor. Test results are uploaded to the database within a few hours of completion compared with delays of up to 10 days for other diagnostic-based reporting systems. This work shows that the barriers to establishing epidemiology systems are no longer scientific and technical but rather administrative, involving questions of patient privacy and data ownership. We have demonstrated here that these barriers can be overcome. This first look at the resulting data stream suggests that Syndromic Trends will be able to provide high-resolution analysis of circulating respiratory pathogens and may aid in the detection of new outbreaks.

Health-care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are pathogen-specific. We describe a system, FilmArray®Trend, for rapid disease reporting that is syndrome-based but pathogen-specific. Results from a multiplex molecular diagnostic test are sent directly to a cloud database.www.syndromictrends.compresents these data in near real-time. Trend preserves patient privacy by removing or obfuscating patient identifiers. We summarize the respiratory pathogen results, for 20 organisms from 344,000 patient samples acquired as standard of care testing over the last four years from 20 clinical laboratories in the United States. The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks and adenovirus and bacterial pathogens show constant detection over the year. Interestingly, the rate of pathogen co-detections, on average 7.7%, matches predictions based on the relative abundance of organisms present.

Background: Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are comprehensive and specific with respect to the pathogen but are rapid in reporting the data. It has proven difficult to implement these requirements on a large scale while maintaining patient privacy. Objective: The aim of this study was to demonstrate the automated export, aggregation, and analysis of infectious disease diagnostic test results from clinical laboratories across the United States in a manner that protects patient confidentiality. We hypothesized that such a system could aid in monitoring the seasonal occurrence of respiratory pathogens and may have advantages with regard to scope and ease of reporting compared with existing surveillance systems. Methods: We describe a system, BioFire Syndromic Trends, for rapid disease reporting that is syndrome-based but pathogen-specific. Deidentified patient test results from the BioFire FilmArray multiplex molecular diagnostic system are sent directly to a cloud database. Summaries of these data are displayed in near real time on the Syndromic Trends public website. We studied this dataset for the prevalence, seasonality, and coinfections of the 20 respiratory pathogens detected in over 362,000 patient samples acquired as a standard-of-care testing over the last 4 years from 20 clinical laboratories in the United States. Results: The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks, and adenovirus and the bacterial pathogens show constant detection over the year. The dataset can also be considered in an ecological framework; the viruses and bacteria detected by this test are parasites of a host (the human patient). Interestingly, the rate of pathogen codetections, on average 7.94% (28,741/362,101), matches predictions based on the relative abundance of organisms present. Conclusions: Syndromic Trends preserves patient privacy by removing or obfuscating patient identifiers while still collecting much useful information about the bacterial and viral pathogens that they harbor. Test results are uploaded to the database within a few hours of completion compared with delays of up to 10 days for other diagnostic-based reporting systems. This work shows that the barriers to establishing epidemiology systems are no longer scientific and technical but rather administrative, involving questions of patient privacy and data ownership. We have demonstrated here that these barriers can be overcome. This first look at the resulting data stream suggests that Syndromic Trends will be able to provide high-resolution analysis of circulating respiratory pathogens and may aid in the detection of new outbreaks.

Although evasion of apoptosis is thought to be required for the development of cancer, it is unclear which cell death pathways are evaded. We previously identified a novel epithelial cell death pathway that works in normal cells but is inactivated in tumor cells, implying that it may be targeted during tumor development. The pathway can be activated by the Fas-associated death domain (FADD) of the adaptor protein but is distinct from the known mechanism of FADD-induced apoptosis through caspase-8. Here, we show that a physiological signal (tumor necrosis factor-related apoptosis-inducing ligand) can kill normal epithelial cells through the endogenous FADD protein by using the novel FADD death domain pathway, which activates both apoptosis and autophagy. We also show that selective resistance to this pathway occurs when primary epithelial cells are immortalized and that this occurs through a mechanism that is independent of known events (telomerase activity, and loss of function of p53, Rb, INK4a, and ARF) that are associated with immortalization. These data identify a novel cell death pathway that combines apoptosis and autophagy and that is selectively inactivated at the earliest stages of epithelial cancer development.

Abstract 1471 Introduction: A variety of prognostic molecular markers have been proposed for risk stratification of intermediate-risk AML, which includes patients with normal cytogenetics (CN) and patients with cytogenetic abnormalities other than the recurrent prognostically informative cytogenetic aberrations (CA). Acquired mutations of FLT3 ITD, NPM1, and CEBPA have well-established prognostic significance, and have been incorporated into consensus classification schemes. In addition, several gene expression markers (WT1, ERG, BAALC, and MN1) have been proposed as prognostic indicators, but with less extensive validation. Whether these new gene expression markers should be incorporated into proposed “molecular risk scores” for AML has not been well refined. In this study, we have determined the transcript levels of WT1, ERG, BAALC, and MN1 in AML patients, and correlated these quantitative levels with other validated clinical and laboratory prognostic indicators. Methods: Diagnostic blood or bone marrow samples were analyzed from 56 pre-treatment AML patients from our institution (48% male; median age 59). Metaphase cytogenetics showed 4 patients with inv(16), 4 with a monosomal karyotype, 25 with a CN karyotype and 23 with a CA karyotype (intermediate-risk cytogenetics). The expression levels of WT1, ERG, BAALC, and MN1 were quantified with TaqMan real-time PCR and normalized to ABL. The FLT3 ITD, NPM1, DNMT3A R882, CEBPA, and MLL PTD mutations were detected with either HRM, direct sequencing, and/or PCR fragment analysis. The WT1 SNP rs16754 was determined with a TaqMan genotyping assay. Results: In the 56 AML patients, the prevalence of the FLT3 ITD, NPM1, MLL-PTD, and DNMT3A R882 mutations were similar to previously reported values at 37%, 27%, 6%, and 13%, respectively. The frequency of patients carrying the minor allele of the WT1 SNP (combined heterozygous and homozygous) was 30%. Compared with their expression level in 29 normal control individuals, all four genes were significantly over-expressed in the AML patients, with mean RNA level differences of 1.98-log for WT1 (P0.9). Consistent with its role as a prognostic risk marker, ERG transcript levels were significantly lower in CN-AML patients with the low-risk NPM+/FLT3- genotype than in those with other genotypes (0.42 log expression difference; P Disclosures: No relevant conflicts of interest to declare.