Predicting vasovagal syncope from heart rate and blood pressure: A prospective study in 140 subjects

Heart Rhythm. 2018 Sep;15(9):1404-1410. doi: 10.1016/j.hrthm.2018.04.032. Epub 2018 Apr 30.

Abstract

Background: We developed a vasovagal syncope (VVS) prediction algorithm for use during head-up tilt with simultaneous analysis of heart rate (HR) and systolic blood pressure (SBP). We previously tested this algorithm retrospectively in 1155 subjects, showing sensitivity 95%, specificity 93%, and median prediction time 59 seconds.

Objective: The purpose of this prospective, single-center study of 140 subjects was to evaluate this VVS prediction algorithm and to assess whether retrospective results were reproduced and clinically relevant. The primary endpoint was VVS prediction: sensitivity and specificity >80%.

Methods: In subjects referred for 60° head-up tilt (Italian protocol), noninvasive HR and SBP were supplied to the VVS prediction algorithm: simultaneous analysis of RR intervals, SBP trends, and their variability represented by low-frequency power-generated cumulative risk, which was compared with a predetermined VVS risk threshold. When cumulative risk exceeded threshold, an alert was generated. Prediction time was duration between first alert and syncope.

Results: Of the 140 subjects enrolled, data were usable for 134. Of 83 tilt-positive subjects (61.9%), 81 VVS events were correctly predicted by the algorithm, and of 51 tilt-negative subjects (38.1%), 45 were correctly identified as negative by the algorithm. Resulting algorithm performance was sensitivity 97.6% and specificity 88.2%, meeting the primary endpoint. Mean VVS prediction time was 2 minutes 26 seconds ± 3 minutes 16 seconds (median 1 minute 25 seconds). Using only HR and HR variability (without SBP), mean prediction time reduced to 1 minute 34 seconds ± 1 minute 45 seconds (median 1 minute 13 seconds).

Conclusion: The VVS prediction algorithm is a clinically relevant tool and could offer applications, including providing a patient alarm, shortening tilt-test time, and triggering pacing intervention in implantable devices.

Trial registration: ClinicalTrials.gov NCT02140567.

Keywords: Autonomic nervous system; Blood pressure; Heart rate; Syncope Prediction Study; Tilt test; Vasovagal syncope.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms*
  • Autonomic Nervous System / physiopathology*
  • Blood Pressure / physiology*
  • Electrocardiography*
  • Female
  • Follow-Up Studies
  • Heart Rate / physiology*
  • Humans
  • Male
  • Predictive Value of Tests
  • Prospective Studies
  • Syncope, Vasovagal / physiopathology*
  • Tilt-Table Test
  • Young Adult

Associated data

  • ClinicalTrials.gov/NCT02140567