Reliability of bedside evaluation in determining left ventricular function: correlation with left ventricular...

Area of Science:

• Cardiology
• Medical Imaging
• Clinical Prediction Models

Background:

• Chronic coronary artery disease (CAD) significantly impacts left ventricular function.
• Accurate assessment of left ventricular ejection fraction (LVEF) is crucial for managing CAD.
• Predicting LVEF using traditional clinical data is an ongoing area of research.

Purpose of the Study:

• To evaluate the reliability of historical, physical, electrocardiographic, and radiologic data in predicting LVEF in patients with chronic CAD.
• To determine the accuracy of clinical assessments in differentiating normal, mildly reduced, and severely reduced LVEF.
• To identify the most significant clinical predictors of LVEF in this population.

Main Methods:

• Prospective evaluation of 99 patients with chronic CAD.
• Classification of patients into groups based on LVEF measured by radionuclide angiography (normal ≥50%, abnormal <50%, severe <30%).
• Stepwise linear regression analysis to identify predictive clinical variables.

Main Results:

• Clinical data accurately predicted the presence of abnormal LVEF (85%) but struggled to predict the degree of dysfunction (53% for moderate, 47% for severe).
• Cardiomegaly on chest roentgenography was the single most predictive variable (R²=0.52).
• A combination of four variables (cardiomegaly, myocardial infarction on ECG, dyspnea, rales) explained only 61% of LVEF variability.

Conclusions:

• While clinical, radiographic, and electrocardiographic data are useful for identifying abnormal LVEF in chronic CAD, they have limitations in quantifying the severity of ventricular dysfunction.
• Radionuclide ventriculography provides significant additional discriminatory power for assessing ventricular function compared to clinical parameters alone.
• Further research may explore integrating advanced imaging or biomarkers to improve prediction of LVEF severity in CAD.