Predicting Severe Cardiac Arrhythmias in the Perioperative Period Using AI-ECG

In study, the investigators plan to identify single-channel and 12-lead ECG parameters that correlate significantly with the occurrence of atrial fibrillation and life-threatening cardiac arrhythmias and conduction disturbances in the perioperative period after high-risk cardiac interventions.

A prospective, non-randomized, observational, controlled, single-center study consisting of two consecutive stages is being conducted.

The first stage involves identifying single-channel and 12-lead ECG parameters that correlate significantly with the onset of atrial fibrillation and life-threatening cardiac arrhythmias and conduction disorders in the perioperative period after interventions with high cardiac risk. Participants who meet the inclusion criteria will undergo the following during preoperative preparation: recording of a digital single-channel ECG using the CardioQVARK software and hardware complex (CardioQVARK medical device (Electrocardiograph) issued by Roszdravnadzor (Federal Service for Surveillance in Healthcare) P3H 2024/22855, issued on June 5, 2024); a digital 12-lead ECG; an extended echocardiographic examination; and 24-hour Holter ECG monitoring.

The single-channel ECG will be recorded for 3 minutes at rest in a sitting position. The participants leans back against the back of the chair, legs uncrossed, arms resting on the knees or on the table. Standard lead I is recorded using the CardioQVARK software and hardware complex.

Next, the parameters of single-channel and 12-channel ECG are identified that have a reliable correlation with the occurrence of atrial fibrillation and life-threatening arrhythmias and conduction disorders in the perioperative period after interventions with high cardiac risk, followed by the creation of a machine learning model and/or or neural network analysis with deep learning support for predicting the occurrence of atrial fibrillation and life-threatening arrhythmias and conduction disorders.

The second stage will involve testing using a test sample of the algorithm, taking into account the ECG parameters which, according to the statistical analysis performed in the first stage, had the highest sensitivity and specificity in predicting the onset of atrial fibrillation and life-threatening cardiac arrhythmias and conductions disorders.

Inclusion criteria

• Patients over 18 years of age;
• Scheduled surgery with high cardiac risk
• Informed consent was given to participate in the study

Exclusion criteria

• Cancellation of the surgery for any reason;
• The patient's unwillingness to continue participating in the study;
• Poor quality of the ECG recording on a single-channel ECG monitor.