Key result
Wearable sensor algorithms using heart rate and pulse arrival time prospectively predict neurally mediated syncope.
Why the study?
Neurally mediated syncope is a common disorder resulting in falls and accidents, warranting prospective validation of wearable sensor prediction algorithms.
Does a prediction algorithm based on heart rate and pulse arrival time predict neurally mediated syncope during head-up tilt table testing in patients with unexplained syncope?
Observational (n=44)
Does a prediction algorithm based on heart rate and pulse arrival time predict neurally mediated syncope during head-up tilt table testing in patients with unexplained syncope?
Effect estimate: Sensitivity 81%, Specificity 85%
Algorithms based on heart rate and pulse arrival time can reliably predict neurally mediated syncope before loss of consciousness, offering potential for ambulatory warning devices.
Background: Neurally mediated syncope (NMS) is a common disorder resulting in falls and accidents. We previously developed a syncope warning system based on wearable sensor technologies in order to predict NMS. Herein, we prospectively validated the underlying algorithms based on heart rate (HR) and pulse arrival time (PAT). Methods: In 44 patients with a history of unexplained syncope 70° head-up tilt table testing (HUTT) was conducted during beat-to-beat analysis of HR and PAT. After initial adaption to tilting an individual syncope risk score was calculated and the predictive value of detecting the slope of HR and PAT changes tested. Combinations of two different methods of PAT calculation (R-wave to pulse wave onset vs R-wave to pulse wave peak) and two different prediction algorithms were compared. Results: In 21 (48%) patients syncope occured during HUTT and could be predicted in all cases (sensitivity: 100%, specificity: 55%) at 203±227s before loss of consciousness. In 15 (71%) of those patients syncope was predicted before the onset of any prodromal symptoms (222±318s). Optimized combination of PAT calculation and prediction algorithm yielded more balanced prediction characteristics (sensitivity: 81%, specificity: 85%). Conclusion: Changes in heart rate and pulse arrival time reliably predict NMS. This observation might pave the way for the development of ambulatory syncope prediction devices; a possible means to protect patients with recurring NMS.
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Eickholt et al. (2013) conducted an observational in Neurally mediated syncope (n=44). Syncope prediction algorithm based on heart rate and pulse arrival time was evaluated on Prediction of neurally mediated syncope during head-up tilt table testing (Sensitivity 81%, Specificity 85%). An optimized prediction algorithm based on heart rate and pulse arrival time predicted neurally mediated syncope during tilt testing with 81% sensitivity and 85% specificity.
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