Every year, hundreds of thousands of Americans acquire potentially life-threatening bacterial infections while in the hospital, nursing home, or other health-care settings . Such infections can be caused by a variety of bacteria, which may respond quite differently to different antibiotics. To match a patient with the most appropriate antibiotic therapy, it’s crucial to determine as quickly as possible what type of bacteria is causing his or her infection. In an effort to improve that process, an NIH-funded team is working to develop a point-of-care system and smartphone app aimed at diagnosing bacterial infections in a faster, more cost-effective manner.
The portable new system, described recently in the journal Science Advances, uses a novel light-based method for detecting telltale genetic sequences from bacteria in bodily fluids, such as blood, urine, or drainage from a skin abscess. Testing takes place within small, optical cubes that, when placed on an electronic base station, deliver test results within a couple of hours via a simple readout sent directly to a smartphone . When the system was tested on clinical samples from a small number of hospitalized patients, researchers found that not only did it diagnose bacterial infections about as accurately and more swiftly than current methods, but it was also cheaper. This new system can potentially also be used to test for the presence of antibiotic-resistant bacteria and contamination of medical devices.
Tags: antibiotic treatment, antibiotic-resistant bacteria, antibiotic-resistant infections, antibiotics, bacteria, bacterial contamination, detection system, diagnostics, genomics, health care, health care-acquired infections, hospital acquired infections, infection, nursing home, optical testing cubes, PAD, point-of-care diagnostics, point-of-care tests, Polarization Anisotropy Diagnostics, smartphone