Dataset Information

Smartphone-based pathogen diagnosis in urinary sepsis patients.

ABSTRACT:

Background

There is an urgent need for rapid, sensitive, and affordable diagnostics for microbial infections at the point-of-care. Although a number of innovative systems have been reported that transform mobile phones into potential diagnostic tools, the translational challenge to clinical diagnostics remains a significant hurdle to overcome.

Methods

A smartphone-based real-time loop-mediated isothermal amplification (smaRT-LAMP) system was developed for pathogen ID in urinary sepsis patients. The free, custom-built mobile phone app allows the phone to serve as a stand-alone device for quantitative diagnostics, allowing the determination of genome copy-number of bacterial pathogens in real time.

Findings

A head-to-head comparative bacterial analysis of urine from sepsis patients revealed that the performance of smaRT-LAMP matched that of clinical diagnostics at the admitting hospital in a fraction of the time (~1?h vs. 18-28?h). Among patients with bacteremic complications of their urinary sepsis, pathogen ID from the urine matched that from the blood - potentially allowing pathogen diagnosis shortly after hospital admission. Additionally, smaRT-LAMP did not exhibit false positives in sepsis patients with clinically negative urine cultures.

Interpretation

The smaRT-LAMP system is effective against diverse Gram-negative and -positive pathogens and biological specimens, costs less than $100 US to fabricate (in addition to the smartphone), and is configurable for the simultaneous detection of multiple pathogens. SmaRT-LAMP thus offers the potential to deliver rapid diagnosis and treatment of urinary tract infections and urinary sepsis with a simple test that can be performed at low cost at the point-of-care. FUND: National Institutes of Health, Chan-Zuckerberg Biohub, Bill and Melinda Gates Foundation.

SUBMITTER: Barnes L

PROVIDER: S-EPMC6197494 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Publications

Smartphone-based pathogen diagnosis in urinary sepsis patients.

Barnes Lucien L Heithoff Douglas M DM Mahan Scott P SP Fox Gary N GN Zambrano Andrea A Choe Jane J Fitzgibbons Lynn N LN Marth Jamey D JD Fried Jeffrey C JC Soh H Tom HT Mahan Michael J MJ

EBioMedicine 20180920

<h4>Background</h4>There is an urgent need for rapid, sensitive, and affordable diagnostics for microbial infections at the point-of-care. Although a number of innovative systems have been reported that transform mobile phones into potential diagnostic tools, the translational challenge to clinical diagnostics remains a significant hurdle to overcome.<h4>Methods</h4>A smartphone-based real-time loop-mediated isothermal amplification (smaRT-LAMP) system was developed for pathogen ID in urinary se ...[more]

PMID: 30245056

Similar Datasets

Project description:BackgroundEarly availability of pathogen identification in urinary tract infections (UTIs) has critical importance in disease management. Metagenomic next-generation sequencing (mNGS) has the potential to transform how acute and serious infections are diagnosed by offering unbiased and culture-free pathogen detection. However, clinical experience with application of the mNGS test is relatively limited.MethodsWe therefore established a MinION-based mNGS pathogens diagnostic platform and evaluated its potential for clinical implementation in UTIs with clinical samples. 213 urine samples from patients with suspected UTIs were included and subjected to mNGS testing using the MinION platform. mNGS results were compared to the gold standard of clinical culture and composite standard of combining clinical testing, confirmatory qPCR testing, and clinical adjudication by doctors.ResultsThe mNGS exhibited a sensitivity of 81.4% and a specificity of 92.3%, along with a positive predictive value of 96.6%, a negative predictive value of 64.9%, and an overall accuracy of 84.4%, all of which were determined based on the gold standard of routine culture results. When assessed against the composite standard, the sensitivity and specificity both increased to 89.9% and 100%, respectively, while the accuracy rose to 92.4%. Notably, the positive predictive value and negative predictive value also saw improvements, reaching 100% and 76.8%, respectively. Moreover, this diagnostic platform successfully identified dsDNA viruses. Among the 65 culture-negative samples, the viral detection rate reached 33.8% (22/65) and was subsequently validated through qPCR. Furthermore, the automatic bioinformatics pipeline we developed enabled one-click analysis from data to results, leading to a significant reduction in diagnosis time.ConclusionThese results demonstrate that the pathogen detection performance of mNGS is sufficient for diagnostic testing in clinical settings. As the method is generally unbiased, it can improve diagnostic testing of UTIs and other microbial infections.

Dataset Information

Smartphone-based pathogen diagnosis in urinary sepsis patients.

Background

Methods

Findings

Interpretation

Publications

Smartphone-based pathogen diagnosis in urinary sepsis patients.

Similar Datasets

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