Vasovagal Syncope
Conditions
Brief summary
The purpose of this study is to perform a prospective evaluation of the vasovagal syncope prediction algorithm, called Tilt Test Analyzer, during head up tilt testing tests in one center in the United Kingdom.
Detailed description
Vasovagal syncope (VVS) is a form of neurally-mediated reflex syncope, which is marked by a sudden fall in blood pressure with an associated fall in heart rate often resulting in syncope, head-up tilt (HUT) testing is commonly used to bring information about VVS using ECG and blood pressure monitoring with medical observation. We developed an algorithm, called Tilt Test Analyzer, to predict VVS during HUT based on the simultaneous analysis of heart rate (RR interval), systolic blood pressure (SBP) and an indicator of autonomic modulation represented by heart rate and blood pressure variability (HRV and BPV). The primary objective of this study is to evaluate the VVS prediction algorithm in a prospective cohort of patients in the tilt laboratory The primary endpoint is the VVS prediction algorithm performance by means of measuring the sensitivity and specificity values. The study is designed to test if the prospective analysis of tilt-test patients can reproduce the results previously obtained in the published retrospective analysis on 1155 patients with a similar clinically relevant sensitivity and specificity.
Interventions
None listed
Sponsors
Study design
Eligibility
Inclusion criteria
* Patients referred to the center with vasovagal syncope for tilt testing. * The patient is willing and able to cooperate with the study procedures. * The subject or legal guardian is able to provide written informed consent
Exclusion criteria
* Patients under 18 years or over 90 years old. * Women who are currently pregnant or have a positive pregnancy test. * Patients who had a prior tilt test. * Patients enrolled in another device or drug study.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity of the Syncope Prediction Algorithm | Tilt Test with average duration of 1 hour | Number of tilt-positive participants predicted in the right way by the syncope prediction algorithm |
| Specificity of the Syncope Prediction Algorithm | Tilt Test with average duration of 1 hour | Number of tilt-negative participants identified as negative by the syncope prediction algorithm |
Countries
United Kingdom
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| Syncope Prediction Enrolled participants who performed tilt test and were included in efficacy analysis | 134 |
| Total | 134 |
Withdrawals & dropouts
| Period | Reason | FG000 |
|---|---|---|
| Overall Study | Problems with recording equipment | 6 |
Baseline characteristics
| Characteristic | Syncope Prediction |
|---|---|
| Age, Continuous | 37.2 years STANDARD_DEVIATION 15.1 |
| Sex: Female, Male Female | 92 Participants |
| Sex: Female, Male Male | 42 Participants |
Adverse events
| Event type | EG000 affected / at risk |
|---|---|
| deaths Total, all-cause mortality | 0 / 140 |
| other Total, other adverse events | 0 / 140 |
| serious Total, serious adverse events | 0 / 140 |
Outcome results
Sensitivity of the Syncope Prediction Algorithm
Number of tilt-positive participants predicted in the right way by the syncope prediction algorithm
Time frame: Tilt Test with average duration of 1 hour
Population: Number of participants with positive tilt-test
| Arm | Measure | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|
| Syncope Prediction (Sensitivity) | Sensitivity of the Syncope Prediction Algorithm | True positive | 81 Participants |
| Syncope Prediction (Sensitivity) | Sensitivity of the Syncope Prediction Algorithm | False negative | 2 Participants |
Specificity of the Syncope Prediction Algorithm
Number of tilt-negative participants identified as negative by the syncope prediction algorithm
Time frame: Tilt Test with average duration of 1 hour
Population: Number of participants with negative tilt-test
| Arm | Measure | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|
| Syncope Prediction (Sensitivity) | Specificity of the Syncope Prediction Algorithm | True negative | 45 Participants |
| Syncope Prediction (Sensitivity) | Specificity of the Syncope Prediction Algorithm | False positive | 6 Participants |