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 Over the last 20 years, the sleep industry has seen a transition from paper recording and analogue filters to real-time data collection systems, but there has been little in the way of real innovation.
Embla recently introduced Cardio Pulmonary Coupling (CPC), a new tool that revolutionizes the diagnosis of sleep-disordered breathing and can predict the success or failure of treatment outcomes with only one channel of ECG data.
CPC generates a picture of sleep that can be easily interpreted and offers an instant overview of the study. In some cases, it can identify patients with complex sleep apnea prior to ventilation therapy titration, which allows the appropriate therapy to be initiated immediately, saving time, money and many unnecessary therapy attempts.
In addition, a 2007 database analysis showed the CPC Module can predict patient success or failure of positive airway pressure treatment with 90.9 percent accuracy.1 This level of accuracy can allow sleep labs to become more efficient by minimizing repeat PSG studies and choosing the appropriate therapy sooner to improve patient treatment compliance.
For sleep centers looking to evaluate prior studies, CPC analysis can be used to indentify patients who may not be compliant with PAP and may need to be restudied. The CPC module is available exclusively in both RemLogic and RemLogic-E so it also can be used in combination with an Embletta portable monitoring device. Uses include pre-treatment screening/diagnosis or tracking of CPAP treatment efficacy. The module can provide real-time data for online studies and also can analyze a previous PSG in less than one minute.
By complimenting PSG reports with a picture of sleep quality, referring physicians can easily understand PSG results. CPC analysis improves scoring accuracy, optimizes a sleep lab's staff efficiency, and maximizes cost-effectiveness in the lab. CPC technology represents a major advancement in sleep-disordered breathing diagnosis and offers a simple method for clinicians and technicians to correctly predict appropriate ventilation treatment.
Reference
1. Thomas RJ, Mietus JE, Peng CK, et al. Differentiating obstructive from central and complex sleep apnea using an automated electrocardiogram-based method. Sleep. 2007;30(12):1756-69.
Preetam Schramm, PhD, principal clinical specialist, Embla, Broomfield, Colo.
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