Cambridge, Mass., October 24, 2023 – Implicity, a leader in remote patient monitoring (RPM) and cardiac data management solutions, today announced the results of a clinical study published in the Cardiovascular Digital Health Journal.
The findings show Implicity’s proprietary algorithm significantly reduced the number of alerts related to transmissions by cardiac implantable electronic devices (CIEDs) in patients being remotely monitored for atrial fibrillation (AF) by filtering standard device notifications and automatically classifying episodes that meet the threshold for clinical relevance.
“For a patient with AF who is already anticoagulated, a single AF episode isn’t as important as established patterns or occurrences associated with arrhythmia progression and patient outcomes. This study proved Implicity’s algorithm can reduce AF alert fatigue by effectively detecting trends, both positive and negative, and categorizing events that require intervention or adjustments in treatment,” said Jagmeet P. Singh MD MMSc DPhil
The retrospective study analyzed real-life data from more than 4,000 recipients of Abbott, Biotronik, Boston Scientific, or Medtronic CIED who were being continuously monitored for AF. Implicity compared the incidence of standard CIED-transmitted alerts from device manufacturers with the incidence of events detected after filtering by Implicity’s algorithm. Results showed the algorithm broke down 67,883 AF burden-related alerts into 9,728 (14.3%) clinically relevant AF events, according to the European Society of Cardiology classification. Notably, the median number of alerts per patient year decreased by 57.9%.
“Sending physicians only clinically relevant alerts, based on the detection of distinct presentations of AF, can reduce the time electrophysiologists spend reviewing notifications that don’t require action by several hours. This will increase the efficiency and quality of care of patients with AF, save time for the medical staff, and help promote the adoption of RPM – leading to more meaningful remote monitoring and ultimately better outcomes,” said Dr. Arnaud Rosier, electrophysiologist, CEO, and co-founder of Implicity.
Continuous remote monitoring is critical for properly managing patients with AF. It allows providers to track patients’ heart rhythms for early intervention and treatment, reducing complications such as stroke and heart failure. Yet a previous study published in European Heart Journal showed that atrial arrhythmia episodes account to up to 51% of the events clinicians are expected to review, suggesting that tackling these alerts could significantly reduce the alert burden.
Implicity’s algorithm works with any device that collects atrial burden trends data and can classify the following scenarios in line with ESC recommendations:
- Paroxysmal AF
- Persistent AF
- Increasing paroxysmal AF
- Back to sinus rhythm
- Back to paroxysmal AF
About Implicity
Implicity is a digital MedTech software company dedicated to providing the best remote care to patients with cardiac implantable electronic devices and heart failure. Co-founded by cardiac electrophysiologist Arnaud Rosier, MD, PhD, the platform aggregates, normalizes, and standardizes data from any implantable cardiac device across all manufacturers, improving care for patients with cardiac implants and heart failure.
Implicity’s platform provides critical health information augmented by FDA-cleared AI algorithms, enabling healthcare providers to make more informed decisions for better patient outcomes. With access to the Health Data Hub**, one of the world’s largest databases of heart disease patients, Implicity is able to develop its AI solutions based on more robust data. The company is protecting more than 94,000 patients in over 195 medical facilities across the US and Europe. To learn more, visit www.implicity.com
*CE marked class I medical device (MDD); see the instructions for use for more information.
** Health Data Hub is a health data platform established by the French government to combine existing health patient databases and facilitate their usage for research and development purposes.