Differential diagnostic algorithm for diseases manifested with heart murmurs syndrome

Area of Science:

• Cardiology
• Medical Diagnostics
• Clinical Decision Support

Background:

• Heart murmur auscultation is a critical diagnostic skill, yet prone to significant interpretation errors.
• Current diagnostic approaches often follow a nosological (disease-first) principle, which diverges from practical clinical workflows.
• These diagnostic inaccuracies result in substantial clinical, educational, and organizational issues.

Observation:

• The traditional diagnostic method, starting with a disease name and then identifying symptoms, is counterintuitive to clinical practice.
• Clinicians typically encounter symptoms first and then proceed to differential diagnosis to establish a definitive diagnosis.
• This discrepancy highlights a need for a more practical diagnostic framework.

Findings:

• A novel diagnostic algorithm based on the syndromic principle (signs-to-diagnosis) has been developed.
• This algorithm effectively facilitates the reliable diagnosis of 35 distinct conditions presenting with heart murmurs.
• The syndromic approach aligns with the practical realities of clinical auscultation.

Implications:

• Implementing this syndromic diagnostic algorithm can significantly reduce errors in heart murmur interpretation.
• It offers a more intuitive and effective method for training medical professionals in cardiac auscultation.
• The algorithm supports improved patient care by enabling more accurate and timely diagnoses of cardiac conditions.