Screening of Valvular Heart Disease Using Single-channel Electrocardiogram
- Conditions
- Valvular Heart Disease Stenosis and RegurgitationValvular Heart Disease
- Registration Number
- NCT07099417
- Brief Summary
It is a prospective, controlled, single-center, observational, non-randomized study. The study is planned to include at least 1000 patients over 18 years old in the training sample and 200 patients over 18 years old in the test sample (the total number of patients is at least 1200 people).
All patients will undergo an echocardiography examination with a comprehensive analysis of the function of the valves and other structures of the heart according to current recommendations by two independent experts.
Registration of electrocardiogram will be performed immediately after echocardiography using a single lead ECG monitor (in I standard lead) for 1 minutes.
The obtained data will be stored in the remote monitoring center of Sechenov University without being linked to the personal data of patients.
A spectral analysis of the electrocardiogram will be performed using a continuous wavelet transform.
The result of this study will be the identification of ECG parameters that will correlate with valvular heart disease.
- Detailed Description
The aim of the study: to create and evaluate the diagnostic efficiency of a method for screening valvular heart disease based on data obtained from the analysis of a single-channel electrocardiogram.
It is a prospective, controlled, single-center, observational, non-randomized study. The study is planned to include at least 1000 patients over 18 years old in the training sample and 200 patients over 18 years old in the test sample (the total number of patients is at least 1200 people).
All subjects will undergo echocardiography with a comprehensive analysis of the function of the valves and other structures of the heart according to current recommendations by two independent experts.
Immediately after echocardiography, ECG registration will be performed in lead I for 1 minute with subsequent spectral analysis of the obtained data, which will be stored in the remote monitoring center of Sechenov University without reference to the personal data of the patients.
Single-channel ECG will be recorded using the portable single-lead ECG monitor CardioQvark. It is designed as an iPhone cover. It is registered with the Federal Service for Health Supervision on February 15, 2019. RZN No. 2019/8124.
If pathology is detected during echocardiography or ECG, the patient will be given a recommendation on the need to consult a cardiologist.
The patient's personal data (last name, first name, patronymic, date of birth, contact information) will not be transferred or taken into account. Each patient is assigned an individual number that is not associated with his/her personal data.
Then a spectral analysis of the electrocardiogram will be performed using a continuous wavelet transform, the principles of which are based on the Fourier transform.
The analysis involves the evaluation of the following parameters (the parameters listed below will be calculated as the median of the tact-cycle):
* TpTe - time from peak to end of the T-wave
* VAT - time from the beginning of the QRS to the R-peak
* QTc - corrected QT interval.
* QT / TQ - the ratio of QT length to TQ length (from the end of T to the beginning of the QRS of the next complex).
* QRS_E - the total energy of the QRS wave based on the wavelet transform
* T_E - T-wave total energy based on wavelet transform
* TP_E- energy of the main tooth of the T-wave based on the wavelet transform
* BETA, BETA_S - T-wave asymmetry coefficients (simple and smooth versions)
* BAD_T - flag of T-wave quality (whether expressed in the current lead
* QRS_D1_ons - energy of the leading edge of the R-wave (based on the "first derivative" wavelet transform)
* QRS_D1_offs - energy of the trailing edge of the R-wave (based on the "first derivative" wavelet transform)
* QRS_D2 - peak energy of the R-wave (based on the "second derivative" wavelet transform)
* QRS_Ei (i = 1,2,3,4) - QRS-wave energy in 4 frequency ranges (2-4-8-16-32 Hz) based on wavelet transform
* T_Ei (i = 1,2,3,4) - T-wave energy in 4 frequency ranges (2-4-6-8-10 Hz) based on wavelet transform
* HFQRS - the amplitude of the RF components of the QRS wave
Additionally used parameters:
* TpTe, VAT, QTc - are duplicated to control the correctness of the record processing (the value of the UCC should be approximately equal to the median of the tick-by-bar).
* QRSw - QRS width.
* RA, SA, TA - the amplitudes of the R, S, T-waves, respectively, are used to normalize the parameters listed above.
Statistical analysis and modeling will be performed using Python V3.8.8 and R V.4.0 programming languages, as well as SPSS v.17 software. The correlation between various combinations of time, amplitude and frequency parameters of ECG and the presence and degree of valvular heart defects will be analyzed. Certain parameters will be included in various multivariate analysis models: Lasso regression, Random Forest, Multilayer Perceptron, Support Vector Machine and Decision Tree. The model with the highest diagnostic accuracy will be selected, on which the algorithm will be tested.
The result of this study will be the development and testing of an algorithm for identifying valvular heart disease based on the analysis of single-channel ECG parameters. With the subsequent possibility of determining the degree of valvular heart disease.
Study endpoints:
* parameters of single-channel ECG that have a reliable correlation with the presence of valvular heart defects;
* sensitivity, specificity and diagnostic accuracy of multivariate models for analyzing single-channel electrocardiogram data;
* diagnostic accuracy of the algorithm when tested on a test sample of patients.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 1200
- The presence of written informed consent of the patient to participate in the study
- Age from 18 years
- Outpatient treatment and / or hospitalization in a research center
- Reluctance of the patient to participate in the study
- Poor quality ECG recording on a single-channel ECG monitor
- Poor visualization of the heart during echocardiographic study
- Acute psychotic reactions that arose during research
- An exacerbation of chronic diseases requiring treatment tactics for the patient and preventing his further participation in the study.
Non-inclusion criteria:
- Poor quality ECG recording on a single-channel ECG monitor
- Conditions that can impair ECG recording quality (Parkinson's disease, essential tremor)
- Mental illness
- Patients with a pacemaker installed
- Patients with prosthetic valves
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Parameters of single-channel ECG that have a reliable correlation with the presence of valvular heart defects through study completion, an average of 2 years comparison of the presence of valvular heart defects detected by the results of an echocardiographic study with the results of the presence of valvular heart defects obtained using the mathematical model of a single-channel ECG monitor
Determination of sensitivity of valvular heart defects of multivariate models for analyzing single-channel electrocardiogram data through study completion, an average of 2 years Comparison of the presence of valvular heart defects detected by the results of an echocardiographic study with the results of the presence of valvular heart defects obtained using the mathematical model of a single-channel ECG monitor
Determination of specificity of valvular heart defects of multivariate models for analyzing single-channel electrocardiogram data through study completion, an average of 2 years Comparison of the presence of valvular heart defects detected by the results of an echocardiographic study with the results of the presence of valvular heart defects obtained using the mathematical model of a single-channel ECG monitor
Determination of diagnostic accuracy of valvular heart defects of multivariate models for analyzing single-channel electrocardiogram data through study completion, an average of 2 years Comparison of the presence of valvular heart defects detected by the results of an echocardiographic study with the results of the presence of valvular heart defects obtained using the mathematical model of a single-channel ECG monitor
- Secondary Outcome Measures
Name Time Method Significance of the parameter TpTe on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter VAT on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter QTc on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter QT / TQ on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter QRS_E on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter TA on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter TP_E on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter BETA on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter SBETA on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter RonsF on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter RoffsF on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter PpeakP on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter QRS_Ei on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter T_Ei on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter HFQRS on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter PpeakN on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter Tenergy on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter Tpeak on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter Tons on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
significance of the parameter Toffs on the ECG in the determination of valvular heart defects through study completion, an average of 2 years an ECG spectral analysis will be performed using the Fourier Transform
Trial Locations
- Locations (1)
I.M. Sechenov First Moscow State Medical University (Sechenov University)
🇷🇺Moscow, Russian Federation
I.M. Sechenov First Moscow State Medical University (Sechenov University)🇷🇺Moscow, Russian Federation