Acute aortic dissection is a rare but life-threatening condition with a lethality rate of 1 to 2% per hour after onset of symptoms in untreated patients. Therefore, its prompt and proper diagnosis is vital to increase a patient's chance of survival and to prevent grievous complications. Typical symptoms of acute aortic dissection include severe chest pain, hypotension or syncope and, hence, mimic acute myocardial infarction or pulmonary embolism. Advanced age, male gender, long-term history of arterial hypertension and the presence of aortic aneurysm confer the greatest population attributable risk. However, patients with genetic connective tissue disorders such as Marfan, Loeys Dietz or Ehlers Danlos syndrome, and patients with bicuspid aortic valves are at the increased risk of aortic dissection at a much younger age. Imaging provides a robust foundation for diagnosing acute aortic dissection, as well as for monitoring of patients at increased risk of aortic disease. As yet, easily accessible blood tests play only a small role but have the potential to make diagnosis and monitoring of patients simpler and more cost-effective.

Background: Smartphone manufacturers offer mobile health monitoring technology to their customers, including apps using the built-in camera for heart rate assessment. This study aimed to test the diagnostic accuracy of such heart rate measuring apps in clinical practice. Methods: The feasibility and accuracy of measuring heart rate was tested on four commercially available apps using both iPhone 4 and iPhone 5. 'Instant Heart Rate' (IHR) and 'Heart Fitness' (HF) work with contact photoplethysmography (contact of fingertip to built-in camera), while 'Whats My Heart Rate' (WMH) and 'Cardiio Version' (CAR) work with non-contact photoplethysmography. The measurements were compared to electrocardiogram and pulse oximetryderived heart rate. Results: Heart rate measurement using app-based photoplethysmography was performed on 108 randomly selected patients. The electrocardiogram-derived heart rate correlated well with pulse oximetry (r ¼ 0.92), IHR (r ¼ 0.83) and HF (r ¼ 0.96), but somewhat less with WMH (r ¼ 0.62) and CAR (r ¼ 0.60). The accuracy of app-measured heart rate as compared to electrocardiogram, reported as mean absolute error (in bpm AE standard error) was 2 AE 0.35 (pulse oximetry), 4.5 AE 1.1 (IHR), 2 AE 0.5 (HF), 7.1 AE 1.4 (WMH) and 8.1 AE 1.4 (CAR). Conclusions: We found substantial performance differences between the four studied heart rate measuring apps. The two contact photoplethysmography-based apps had higher feasibility and better accuracy for heart rate measurement than the two non-contact photoplethysmography-based apps.

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