Imagine having intense pelvic pain and a constant urge to pee. If you have a urinary tract infection (UTI), these symptoms can hit fast and with force.
But a urine culture, the standard lab test to diagnose a UTI, can take up to three days to yield results. For patients desperate for relief, doctors often prescribe antibiotics before getting the lab results back, and in doing so, may prescribe the wrong drug.
A new smartphone-based test called smaRT-LAMP, developed by researchers at UC Santa Barbara and Stanford University, could potentially cut out the need for a urine culture altogether. The test uses an app called Bacticount to analyze fluorescent light reflected from treated urine samples. In a study published in the journal EBioMedicine in September, the researchers reported that the app accurately identified and quantified pathogens in urine in just one hour—a far cry from the one to three days it can take for bacteria to grow in a urine culture.
“With a smartphone, we now potentially have a diagnostic tool that has no geographic or economic limitations, or certainly far fewer,” says Lynn Fitzgibbons, an infectious disease specialist who consulted on the project.
Urinary tract infections are one of the most common bacterial infections seen in primary care in the United States. In 2011, the CDC reported that, based on its 2007 survey of all outpatient visits to doctor's offices and hospitals, UTIs accounted for more than 8 million visits. Over 20 percent of those visits were to hospital emergency rooms.
Currently, the only rapid urine test available to doctors is urinalysis, which can indicate whether there is an infection but does not identify specific bacteria. Urinalysis also frequently shows false positive results, leading doctors to prescribe antibiotics to patients who don’t need them while they wait for more specific results from a urine culture.
“It’s a pretty big issue,” says Huma Farid, a gynecologist at Brigham and Women’s hospital. “If it’s a weekend, [the urine culture results] may not come back until Monday. By that point, a patient is three to four days into their antibiotic treatment.”
Taking the wrong antibiotic is probably not going to kill you. But if there are any bacteria in your body that are resistant to the drug, the antibiotic wipes out their competition, allowing the resistant bacteria to thrive. These fortified bacteria can then pass on their resistance to other species of bacteria. This means that if you truly need that antibiotic in the future, it may not work. The CDC estimates that approximately 23,000 people die from antibiotic-resistant infections each year.
This problem is particularly acute in low-resource settings where patients can’t afford lab tests, or where clinics don’t have access to advanced diagnostic facilities to begin with. The other risk in these settings is detecting a UTI too late, when it can cause a life-threatening condition like sepsis.
This is where the smaRT-LAMP system comes in. RT-LAMP is an acronym for an established method that has been demonstrated to provide fast, accurate, and inexpensive diagnosis of infectious diseases like the Zika virus in research settings. The study authors are taking RT-LAMP a step further by applying it to urinary tract infections for the first time, and pairing it with an app that will help less-experienced clinicians decipher the results.
With Zika, you just need to know whether or not the pathogen is present, explains Laura Lamb, a microbiologist at Beaumont Health in Michigan who has worked on Zika detection using RT-LAMP. When it comes to UTI infections, however, the concentration of pathogens is important.
"[The team is] looking at low, medium, high concentration. So that can be somewhat subjective,” she says. “And that's where I think it's nice that you have the smartphone paired with the [RT-LAMP] standard curve—to kind of evaluate where exactly you are on that low, medium to high concentration scale.”
To analyze a urine sample using smaRT-LAMP, a healthcare provider would prepare the urine with a treatment that will generate a fluorescent signal if bacteria are present. After heating the sample on a hot plate, they would cover it with a cardboard box lined with LED lights and record the reaction through a hole in the top with a smartphone. The Bacticount app analyzes the video to identify and count the pathogens. The app compares the reaction to the standard curve that Lamb mentioned, which is a map of the fluorescent light reflected for several known concentrations of pathogens, to approximate the number of pathogens in the test sample.
In the study, the researchers found that the app could identify several different pathogens in bacteria-spiked mouse urine. They also tested urine from 10 human patients who showed symptoms of sepsis. Bacticount accurately detected three different strains of bacteria and matched the culture results from the hospital’s microbiology lab in all 10 cases.
“This study was a head-to-head comparison with hospital diagnostics,” Michael Mahan, director of the study, said in an email. “The next step is to determine whether it works in local clinics that cannot afford to ‘ID’ the pathogen.”
The low-cost lab kit resembles a DIY project: All you need is a hot plate, a cardboard box, a strip of LED lights, and a tray to hold urine samples. The authors assert that the whole kit can be assembled for under $100, plus the cost of a smartphone.
But Jeong-yeol Yoon, a professor of biomedical engineering at the University of Arizona, who developed a test for Zika virus using RT-LAMP, is skeptical of the pricetag. “I think they are actually underestimating the labor,” Yoon says. In his experience, the technology requires a trained technician operating in a sterile environment to avoid contamination of the samples.
Lamb says that it just requires taking the right precautions: “They're going to have to test it at different sites and so if [contamination] is a concern, it will show up then.”
She’s optimistic that RT-LAMP has a future in clinics, and says that there are lots of potential applications for it. “The nice thing about this technology is that it’s really fast,” Lamb says. “Diseases where you have to make a decision really quickly about treatment, where you can’t wait—you can do this in one hour. That’s a huge advantage.”