Prognostic value of diastolic filling parameters derived using a novel image processing technique in patients ≥70 years of age with congestive heart failure

• Published in: The American journal of cardiology Vol. 84; no. 1; pp. 82 - 86
• Main Authors: Rich, Michael W., Stitziel, Nathan O., Kovács, Sándor J.
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 01.07.1999; Elsevier
• Subjects: Aged; Biological and medical sciences; Cardiovascular system; Diastole - physiology; Echocardiography, Doppler; Female; Heart Failure - diagnostic imaging; Heart Failure - mortality; Heart Failure - physiopathology; Humans; Image Processing, Computer-Assisted - methods; Investigative techniques, diagnostic techniques (general aspects); Male; Medical sciences; Mitral Valve - diagnostic imaging; Mitral Valve - physiopathology; Models, Theoretical; Predictive Value of Tests; Ultrasonic investigative techniques; Ventricular Dysfunction, Left - diagnostic imaging; Ventricular Dysfunction, Left - mortality; Ventricular Function, Left - physiology; Sonography; Human; Doppler ultrasound study; Heart failure; Prognosis; Diastole; Cardiovascular disease; Exploration; Automated processing; Analysis method; Heart disease; Technique; Predictive factor; Left ventricle performance; Elderly
• ISSN: 0002-9149; 1879-1913
• DOI: 10.1016/S0002-9149(99)00196-4

Conventional echocardiographic characterization of diastolic function requires manual analysis of Doppler E- and A-wave amplitudes, deceleration times, isovolumic relaxation times, and pulmonary venous flow patterns. Mathematic modeling of the suction pump activity of the heart permits characterization of diastolic function through model-based image processing, which relies solely on transmitral Doppler images. This automated method uniquely specifies the entire E-wave contour using 3 parameters (x o, k, and c) that determine E-wave amplitude, width, and rate of decay. Moreover, the index β = c 2 − 4k, reflecting the balance between chamber viscosity and stiffness/recoil, represents a novel parameter for characterizing diastolic function. We analyzed Doppler E waves from 39 patients (mean age 79 years, 61% women, mean ejection fraction 47%) using the model-based image processing technique. A value of β <−900 was selected as indicative of severe diastolic dysfunction. Of 17 subjects with β <−900, 8 (47%) were no longer alive at 1 year. Of 22 subjects with β >−900, all were alive (p = 0.001). The index β, dichotomized at <−900, had a predictive accuracy of 0.769 (30 of 39), a negative predictive value of 1.0 (22 of 22 alive), and a positive predictive value of 0.471 (8 of 17 deceased) for 1-year vital status. Of 14 subjects with deceleration time ≤160 ms, 5 (36%) were deceased at 1 year, whereas for deceleration time >160 ms, 22 of 25 patients were alive (p = NS). Of 16 subjects with ejection fraction <45%, 6 (38%) were deceased at 1 year. Of 23 subjects with ejection fraction >45%, 21 were alive at 1 year (p = 0.074). On multivariate analysis, β dichotomized at −900 was the strongest independent predictor of 1-year mortality. We conclude that evaluation of diastolic function using model-based image processing provides valuable prognostic information in elderly patients with heart failure.