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Feasibility of repeated on-demand smartphone app-based approximation of time spent with atrial fibrillation and symptoms in patients after catheter ablation: Data from the ISOLATION study

Posted by susan.d 
[www.heartrhythmjournal.com]

Results

A total of 191 patients (median age 65, 65% male) were included. Patient adherence (-7%, p=0.04) slightly declined over 12 months. Forty-five (24%) patients had AF recurrence and 136 (71%) symptom recurrence. In patients with high AF load and density at 3 months, 73% and 88% remained in the respective high class; in patients with low AF load and density, 0% remained in the low class. In patients with high symptom load and density, 94% and 75% remained in the respective high class; in patients with low symptom load and density, 0% remained in the low class. SRC was high, median 97% interquartile range 77-100%.

71% had system recurrence? 73% and 88% remained in the respective high class? Does that mean there was a low success rate?
Here is the full paper: [pmc.ncbi.nlm.nih.gov]

More details:

Quote

Patients were instructed to record a 60-s PPG recording through their smartphone’s built-in camera three times daily and when experiencing symptoms. Further, after completing a recording, patients had to specify if they encountered any of the following symptoms: no symptoms, palpitations, chest pain, dyspnoea, confusion, light-headedness, fatigue, and/or others. Patients received regular reminders to assess their heart rate/heart rhythm and to actively report the presence/absence of symptoms via pop-up notifications. Additionally, patients were given instructions on how to improve the quality of measurements

Quote

Smartphone app-based assessment of time spent with atrial fibrillation
The presence of AF during the respective PPG recording was determined by a validated PPG algorithm (FibriCheck®, Qompium, Hasselt, Belgium) with a sensitivity of 98.3% and a specificity of 99.9% for AF detection,21 followed by an additional overread by a certified technician. Time spent with AF was approximated using the four following definitions: (i) %AF recordings: proportion of AF recordings per all recordings; (ii) AF load: the proportion of time spent with AF to the total monitoring time (time spent with AF/total monitoring time). Time spent with AF respective total monitoring time are calculated as follows: time spent with AF = sum of time between the last PPG recording with non-AF and the first PPG recording with AF divided by two, plus time between the first and last consecutive PPG recording with AF, plus time between last PPG recording with AF and the first PPG recording with non-AF divided by two; total monitoring time = the time between the first and the last PPG recording during the monitoring period; (iii) %AF days: proportion of days with at least one recording with AF per all complete monitoring days (i.e. 6 days; the first and last day of monitoring was removed, as these were non-complete days); (iv) AF density is a measure of time spent with AF to total monitoring time, just like AF load, and the calculation is the same with the exception that in the sum of time spent with AF, only AF episodes with at least three consecutive PPG recordings with AF are included. We defined a low-density score <50% as ‘paroxysmal AF pattern’ and a high-density score ≥90% as ‘persistent AF pattern’. For more details, see Figure 1.

Figure 1: [pmc.ncbi.nlm.nih.gov]
Still a high load of either way. It’s a small study.
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