ResApp Health announced that its investigative software, ResAppDx, has shown promise in the accurate and specific diagnosis of adult pneumonia and other respiratory conditions based on cough sounds.
ResApp is a smartphone application for the diagnosis and management of respiratory disease, and is based on machine-learning algorithms that use cough sounds to detect and measure the severity of respiratory complications without additional hardware. Clinical trials testing its efficacy in adults and children are still ongoing, but early results in adults demonstrate accuracy and specificity in the diagnosis of pneumonia, chronic obstructive pulmonary disease (COPD), asthma, and upper respiratory tract infection (URTI).
Recruiting is still ongoing for the adult trial at the Joondalup Health Campus (JHC) and the Wesley Hospital in Australia. For more information, visit the company website at www.resapphealth.com.au. The preliminary results were analyzed by a research team from the University of Queensland.
The trial includes 25 COPD patients (with non-infective exacerbation or emphysema), 43 patients diagnosed with acute or chronic asthma (some with concomitant URTI and allergic nasal obstructions), 71 patients with pneumonia (with or without URTI), and 20 patients diagnosed with URTI (with no clinically discernible lower respiratory tract involvement). The study also includes a control group of 27 smokers with no detectable respiratory disease at the time of measurement, and 57 lifelong non-smokers with no detectable respiratory disease at the time of measurement.
First results from the trial indicated that ResApp was able to detect the presence of the various respiratory diseases with high accuracy, sensitivity and specificity. Specifically, high levels of accuracy (91-100 percent) were seen in distinguishing patients with URTI, COPD, asthma, or pneumonia from trial participants without discernible respiratory disease. The app was also able to differentiate between asthma and COPD, pneumonia and asthma, and pneumonia and COPD with an accuracy range of 88 percent to 94 percent.
“We are pleased to again report high levels of accuracy in a significantly larger data set, which continues to build our clinical evidence base as we progress towards FDA submission,” said Tony Keating, ResApp’s CEO, in a company press release. “It is also excellent to note that once again our algorithms outperformed experienced clinicians by correctly detecting lower respiratory tract infection in patients initially diagnosed as clear.”
ResApp also detected lower respiratory tract disease in 84 percent of patients, who had been initially considered healthy by experienced clinicians using stethoscopes. The new diagnosis was then confirmed by additional testing, supporting the efficacy of the ResApp algorithms in the correct diagnosis of patients.
ResApp Health notes that these data are still preliminary and may change as the study develops.
The efficacy of the ResApp application will also be evaluated in children, in a U.S. study at three hospitals that is expected to start before the end of the year (called SMARTCOUGH-C).
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