Sleep Apnea Screening Tool May Help Lower Risks for Cardiovascular Patients

The new neural network-based screening tool diagnoses sleep apnea based on a patient’s answers to questions about body mass index, neck size, the presence of hypertension and other clinical characteristics.

Between 30 and 50 percent of cardiovascular patients are believed to suffer from this potentially life-threatening condition, which prevents sufficient air from getting into the lungs. Many of them are undiagnosed.

In heart patients, obstructive sleep apnea can trigger heart attacks, atrial fibrillation and stroke.

“It makes sense for us to screen cardiovascular patients for sleep apnea as early as possible so that if they are diagnosed with it, we can start treating them before they suffer another event,” says Ali A. El Solh, MD, UB professor of medicine and social and preventive medicine, who developed the screening tool with Brydon J. Grant, MD, professor emeritus of medicine.

El Solh is principal investigator of a study that examines how well the tool compares with an overnight sleep study, or polysomnography, considered the gold standard for diagnosing sleep apnea.

If the new tool is as accurate as polysomnography, it could provide clinicians with a much faster, more accessible way to identify sleep apnea, especially in high-risk patients.

“The importance of this grant is that it may give us a faster way to screen for sleep apnea in patients who are already at high risk but who are undiagnosed,” says El Solh.

The U.S. Department of Veterans Affairs is funding the study, which takes place at the Buffalo VA Medical Center. It will end in December, and data analysis is expected to be complete early next year.