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| Name | Class |
|---|---|
| University Hospital Greifswald | OTHER |
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Prospective, blinded, multicenter international trial to test the Preventicus Heartbeats App in a prospective cohort.
Introduction This algorithm was validated earlier in a clinical trial with retrospective Data. The results were published accordingly.The algorithm is implemented in the commercial App Preventicus Heartbeats. DETECT AF is designed as prospective follow up trial.
Study design Prospective, blinded, multicenter international trial.
Methods
The subjects will be asked to position a smartphone on their index finger to allow their pulse curve to be recorded for five minutes. At the same time, an ecg will be recorded using an digital mobile ecg recorder as a reference.
Data will be collected on person-related information, comorbidities and medication (estimated overall duration/patient <20 min). No follow-up is planned. Analogous to predecessor studies, the pulse wave curve data are coded with the patient's identification number (ID) and externally analyzed at Preventicus; based on the results, the subjects will be assigned to SR/AF groups. After evaluation of all files, the grouped results will be aggregated, unblinded and evaluated under monitoring.
Primary target parameters are the app's sensitivity and specificity in correctly detecting atrial fibrillation compared to an automatically interpreted ECG.
Secondary target parameters include the proportion of non-evaluable recordings in the overall study.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| AF | Five minutes puls wave recording will be performed in patients in atrial fibrillation at time of recruitment |
| |
| SR | Five minutes puls wave recording will be performed in patients in sinus rhythm at time of recruitment |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Five minutes puls wave recording | Device | iPhone will be positioned on the index finger for five minutes to record a pulse wave |
|
| Measure | Description | Time Frame |
|---|---|---|
| Correct detection of atrial fibrillation | iPhone will be positioned on the index finger for five minutes to record a pulse wave; Algorithm should correctly differentiate between AF patients and SR patients | 5 minutes |
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Inclusion Criteria:
Exclusion Criteria:
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Patients at the University Hospital Basel
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| Name | Affiliation | Role |
|---|---|---|
| Jens Eckstein, MD, PhD | Universityhospital Basel | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Hospital Greifswald | Greifswald | 17475 | Germany | |||
| University Hospital Basel |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 27371660 | Result | Krivoshei L, Weber S, Burkard T, Maseli A, Brasier N, Kuhne M, Conen D, Huebner T, Seeck A, Eckstein J. Smart detection of atrial fibrillationdagger. Europace. 2017 May 1;19(5):753-757. doi: 10.1093/europace/euw125. | |
| 30085018 | Derived | Brasier N, Raichle CJ, Dorr M, Becke A, Nohturfft V, Weber S, Bulacher F, Salomon L, Noah T, Birkemeyer R, Eckstein J. Detection of atrial fibrillation with a smartphone camera: first prospective, international, two-centre, clinical validation study (DETECT AF PRO). Europace. 2019 Jan 1;21(1):41-47. doi: 10.1093/europace/euy176. |
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| ID | Term |
|---|---|
| D001281 | Atrial Fibrillation |
| ID | Term |
|---|---|
| D001145 | Arrhythmias, Cardiac |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D010335 | Pathologic Processes |
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| Basel |
| Canton of Basel-City |
| 4031 |
| Switzerland |
| D013568 |
| Pathological Conditions, Signs and Symptoms |