ResApp Health announced additional positive results from its clinical study evaluating ResApp’s technology in adults with chronic obstructive respiratory disease (COPD), asthma, pneumonia, and upper respiratory tract infection (URTI).

ResApp is a smartphone application for the diagnosis and management of respiratory disease. The technology is based on machine-learning algorithms that use sound to diagnose and measure the severity of respiratory conditions without requiring additional hardware. ResApp is currently undergoing adult and pediatric clinical trials with preliminary results demonstrating promising accuracy in the diagnosis of COPD, asthma, pneumonia, and URTI.

An adult trial is now underway at Joondalup Health Campus (JHC) and the Wesley Hospital in Australia. This set of preliminary results was analyzed by a research team led by Udantha Abeyratne, associate professor at the University of Queensland.

The trial involved the following groups:

• Normal group: 27 smokers with no discernible respiratory disease at the time of measurement with a history of smoking, plus 57 nonsmokers with no discernible respiratory disease at the time of measurement and no history of smoking.
• COPD group: 25 patients with a diagnosis of COPD; COPD with non-infective exacerbation, or emphysema;
• Asthma group: 43 patients with a diagnosis of acute or chronic asthma; some subjects had concomitant URTI and allergic nasal obstructions.
• Pneumonia group: 71 patients with a diagnosis of pneumonia with or without URTI.
• URTI group: 20 patients with a diagnosis of URTI and no clinically discernible lower respiratory tract involvement.

Preliminary results demonstrated high levels of sensitivity and specificity of the ResApp in detecting the different lung diseases analyzed. Concerning the accuracy of the diagnosis, ResApp’s cough sound-based algorithms achieved high levels (between 91 and 100 percent) for distinguishing adult patients with COPD, asthma, URTI, or pneumonia from subjects with no discernible respiratory disorder.

“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,” ResApp CEO Tony Keating said in a 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.”

The differential diagnosis of asthma versus COPD, pneumonia versus asthma, and pneumonia versus previously unreported COPD was achieved with an accuracy around 88 percent to 94 percent.

The ResApp algorithms were also able to correctly detect lower respiratory tract disease in 84 percent of adult patients who were initially not given any disease diagnosis; these patients were finally diagnosed as having a lower respiratory tract disease after additional clinical testing.

ResApp highlights the fact that these results are preliminary and may change as the study develops. The study continues to enroll adult patients at JHC and the Wesley Hospital.

ResApp will also be assessed in an U.S. pediatric clinical trial (SMARTCOUGH-C), a multi-center, double-blind study that will determine the effectiveness of the app in the diagnosis of childhood pneumonia and other respiratory conditions based on cough sounds. This trial should begin later this year.

The algorithms for ResApp were initially developed at the University of Queensland with funding from the Bill and Melinda Gates Foundation.