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1.
JMIR Public Health Surveill ; 4(3): e59, 2018 Jul 06.
Article in English | MEDLINE | ID: mdl-29980501

ABSTRACT

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.

2.
J Mol Diagn ; 16(2): 159-62, 2014 Mar.
Article in English | MEDLINE | ID: mdl-24457120

ABSTRACT

This Commentary highlights the article by Satterfield that describes a new class of primer technology-cooperative primers, which prevent primer-dimer amplification.


Subject(s)
DNA Primers/standards , Multiplex Polymerase Chain Reaction/methods , Multiplex Polymerase Chain Reaction/standards , Humans
3.
Diagn Microbiol Infect Dis ; 74(4): 349-55, 2012 Dec.
Article in English | MEDLINE | ID: mdl-22999332

ABSTRACT

Sepsis is a leading cause of death. Rapid and accurate identification of pathogens and antimicrobial resistance directly from blood culture could improve patient outcomes. The FilmArray® (FA; Idaho Technology, Salt Lake City, UT, USA) Blood Culture (BC) panel can identify >25 pathogens and 4 antibiotic resistance genes from positive blood cultures in 1 h. We compared a development version of the panel to conventional culture and susceptibility testing on 102 archived blood cultures from adults and children with bacteremia. Of 109 pathogens identified by culture, 95% were identified by FA. Among 111 prospectively collected blood cultures, the FA identified 84 (91%) of 92 pathogens covered by the panel. Among 25 Staphylococcus aureus and 21 Enterococcus species detected, FA identified all culture-proven methicillin-resistant S. aureus and vancomycin-resistant enterococci. The FA BC panel is an accurate method for the rapid identification of pathogens and resistance genes from blood culture.


Subject(s)
Bacteremia/diagnosis , Bacteria/drug effects , Bacteria/isolation & purification , Bacteriological Techniques/methods , Blood/microbiology , Multiplex Polymerase Chain Reaction/methods , Adult , Bacteremia/microbiology , Bacteria/genetics , Child , Child, Preschool , Drug Resistance, Bacterial , Humans
4.
PLoS One ; 6(10): e26047, 2011.
Article in English | MEDLINE | ID: mdl-22039434

ABSTRACT

The ideal clinical diagnostic system should deliver rapid, sensitive, specific and reproducible results while minimizing the requirements for specialized laboratory facilities and skilled technicians. We describe an integrated diagnostic platform, the "FilmArray", which fully automates the detection and identification of multiple organisms from a single sample in about one hour. An unprocessed biologic/clinical sample is subjected to nucleic acid purification, reverse transcription, a high-order nested multiplex polymerase chain reaction and amplicon melt curve analysis. Biochemical reactions are enclosed in a disposable pouch, minimizing the PCR contamination risk. FilmArray has the potential to detect greater than 100 different nucleic acid targets at one time. These features make the system well-suited for molecular detection of infectious agents. Validation of the FilmArray technology was achieved through development of a panel of assays capable of identifying 21 common viral and bacterial respiratory pathogens. Initial testing of the system using both cultured organisms and clinical nasal aspirates obtained from children demonstrated an analytical and clinical sensitivity and specificity comparable to existing diagnostic platforms. We demonstrate that automated identification of pathogens from their corresponding target amplicon(s) can be accomplished by analysis of the DNA melting curve of the amplicon.


Subject(s)
Respiratory Tract Infections/microbiology , Reverse Transcriptase Polymerase Chain Reaction/methods , Humans
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