[Algorithm for the management of patients with stable coronary artery disease and high-grade ventricular arrhythmias]

Area of Science:

• Cardiology
• Clinical Medicine
• Medical Algorithms

Background:

• Stable coronary artery disease (CAD) with high-grade ventricular arrhythmias (VA) poses a significant risk.
• Left ventricular systolic function (LVSF) influences management strategies.
• Autonomic dysregulation and psychological factors can contribute to VA genesis.

Purpose of the Study:

• To introduce an original, step-by-step algorithm for managing patients with stable CAD and high-grade VA.
• To emphasize comprehensive assessment, including arrhythmia nature, autonomic involvement, and psychological status.
• To guide treatment policy selection and prevent sudden cardiac death (SCD).

Main Methods:

• Detailed clinical case assessment.
• Determination of arrhythmia characteristics.
• Evaluation of autonomic regulation's role in VA.
• Topical diagnosis of VA.
• Identification of psychological disorders.
• Utilizing up-to-date diagnostic techniques.

Main Results:

• The proposed algorithm provides a structured approach to patient management.
• It integrates diverse diagnostic findings for a holistic patient view.
• The algorithm prioritizes preventing sudden cardiac death.

Conclusions:

• The novel algorithm offers a systematic method for managing complex cardiovascular cases.
• Integrating arrhythmia specifics, autonomic status, and psychological factors is crucial.
• The algorithm aims to improve patient outcomes by reducing SCD risk.