Abstract 12517: CardioSignal Smartphone Application Detects Atrial Fibrillation in Heart Failure Population
| Autor: | Juuso Blomster, Olli Lahdenoja, Kamal Jafarian Dehkordi, Matti Kaisti, Tero Tapiovaara, Kristiina Santalahti, Mikko Pankaala |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Circulation. 144 |
| ISSN: | 1524-4539 0009-7322 |
| DOI: | 10.1161/circ.144.suppl_1.12517 |
| Popis: | Introduction: The micro-electromechanical sensors of a common smartphone can be used to detect vibrations caused by cardiac motion when the smartphone is placed on chest. With commonly available CardioSignal application (App) the concept has been shown to detect atrial fibrillation (AFib) in clinical setting from a 60 second recording. The CardioSignal smartphone app is a certified CE IIa-class medical device and intended to detect AFib in adult population. AFib and heart failure (HF) frequently coexist and together can lead to increased morbidity. To address this subgroup of individuals with increased risk of Afib, we examined how CardioSignal solution performs in Afib detection in a population of recent HF decompensation. Methods: From a total of 83 HF patients (mean age 64, 70 % men) motion sensor signals were collected and analyzed with the CardioSignal solution. The signals were collected by placing a smartphone on the chest of the patients in supine position. From the recordings two 60 second strips were analyzed. A simultaneous 1-lead ECG data was collected with an ECG patch from the V4 position. The signals were analyzed for quality and rhythm diagnostics from the ECG recording was by a cardiologist blinded for the CardioSignal solution result. Finally a head-to-head comparison was conducted for CardioSignal result and the ECG data. A positive finding for Afib was concluded if both 60 second recordings detected Afib for each person. Results: From the 83 HF patients 166 measurements were recorded. Out of the 166 measurements, 163 passed the quality check for the sensor signals. The preliminary analyses showed sensitivity of the AFib detection algorithm of 80.7% (95% CI 62.5% to 92.6%) and the specificity of 100.0% (93.1% to 100.0%). The positive predictive value was 100.0% and the negative predictive value 89.7% (80.9% to 94.7%). The accuracy was 92.8% (84.9% to 97.3%). Conclusions: A smartphone-based recording and analysis with CardioSignal solution in HF patients appear to be an effective and reliable method to detect possible Afib. |
| Databáze: | OpenAIRE |
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