CardioNet Announces Launch Of Clinical Indicator For Sleep Disorders

Main Category: Sleep / Sleep Disorders / Insomnia
Also Included In: IT / Internet / E-mail
Article Date: 18 May 2009 - 4:00 PDT

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CardioNet, Inc. (NASDAQ:BEAT) announced the launch of SomNet ™, a new clinical indicator available in the Company's existing Mobile Cardiac Outpatient Telemetry™ (MCOT™) system. Because many patients with cardiac disorders also suffer from common sleep disorders like sleep apnea, CardioNet believes that SomNet has the potential to identify patients with a high likelihood of such sleep disorders by measuring cyclic variation of heart rate (CVHR), a rhythm that is caused by repeated arousals from sleep due to such disorders. SomNet's utility is based on data presented at the Heart Rhythm Society's (HRS) 30th Annual Scientific Sessions in Boston.

"There is a high prevalence of sleep disorders like sleep apnea in the cardiovascular and arrhythmia population," said Randy Thurman, CEO of CardioNet. "The data collected by SomNet is extremely valuable information that can be captured from our existing MCOT ECG signal. If clinically appropriate, physicians may choose to refer patients with CVHR patterns to sleep centers for further diagnostic testing, to determine if they have sleep apnea or another serious sleep disorder."

In an 80-patient study presented today at HRS, Phyllis K. Stein, Ph.D., Research Associate Professor of Medicine at Washington University School of Medicine, found that automated identification of clinically relevant CVHR is feasible using CardioNet's MCOT system. The study compared MCOT automatic analysis of CVHR patterns versus a human expert's direct analysis of plots of HR patterns for measuring clear (large amplitude) CVHR. Findings showed similar specificity and positive predictive value measures between MCOT and human expert analysis, with slightly lower sensitivity measures for the automated analysis.

"Although slightly less sensitive than more labor intensive human overreading, the MCOT system and SomNet may provide a platform for efficiently identifying patients with severe sleep disorders, like sleep apnea, in a large population," said Dr. Stein.

Source
CardioNet, Inc.