If an abnormal S2 sound on cardiac exam is detected, which of the following findings has the strongest evidence according to McGee (2022)?
The correct answer and explanation is:
Correct Answer: Wide splitting of S2 during inspiration and expiration
According to McGee (2022), the presence of an abnormally split second heart sound (S2), particularly if it persists during both inspiration and expiration (wide and fixed splitting), is a significant auscultatory finding that may indicate underlying cardiac pathology. S2 normally splits during inspiration because of delayed closure of the pulmonic valve due to increased venous return. However, when this splitting is exaggerated or persistent throughout the respiratory cycle, it suggests an abnormality in the cardiac cycle.
The strongest evidence supports wide or fixed splitting of S2 as a finding associated with conditions such as atrial septal defect (ASD) or right bundle branch block (RBBB). These conditions delay right ventricular systole or pulmonic valve closure regardless of respiratory cycle. McGee emphasizes that fixed splitting of S2 has a high likelihood ratio for ASD, meaning that its presence significantly raises the probability of that diagnosis.
Other conditions that can produce abnormal S2 include pulmonary hypertension and pulmonary stenosis, which can delay pulmonic valve closure. Paradoxical splitting of S2, where the split occurs during expiration rather than inspiration, may suggest left-sided conduction delays such as left bundle branch block or aortic stenosis.
Clinical detection of S2 splitting requires careful auscultation at the left upper sternal border (the pulmonic area). Proper technique and a quiet environment are essential, and timing of the sounds with the respiratory cycle helps in characterizing the nature of the splitting.
In summary, wide or fixed splitting of S2 provides strong diagnostic evidence, especially for conditions like ASD. McGee (2022) identifies this finding as having one of the highest clinical values in physical diagnosis based on likelihood ratios and diagnostic utility in bedside medicine.