Smartphone-based pathogen diagnosis in urinary sepsis patients.

TitleSmartphone-based pathogen diagnosis in urinary sepsis patients.
Publication TypeJournal Article
Year of Publication2018
AuthorsBarnes L, Heithoff DM, Mahan SP, Fox GN, Zambrano A, Choe J, Fitzgibbons LN, Marth JD, Fried JC, H Soh T, Mahan MJ
Date Published2018 Sep 08

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.

Alternate JournalEBioMedicine
PubMed ID30245056