The relation between the etiology of cardiomyopathy and the function of the right ventricle (RV) has not been well described in the current era of 3-dimensional cardiac imaging. New advances in cardiac imaging with computed tomography (CT) have allowed accurate measurements of ejection fraction (EF), often a challenging task considering the unique RV shape. We evaluated 130 patients at the Loma Linda Veterans Affairs Healthcare System with cardiomyopathy and a left ventricular (LV) EF ≤40%. Etiology of cardiomyopathy was determined by CT angiography as ischemic (n = 56) or nonischemic (n = 74). RV volumes and RVEF were calculated based on 3-dimensional data set from CT images. Baseline LVEF was similar with a mean LVEF of 28% (±6%) in the ischemic group and 28% (±9%) in the nonischemic group (p = 0.46). RV function and volumes were moderately decreased in both cohorts, without significant difference between the groups (mean RVEF 34 ± 11% in ischemic group and 32 ± 10% in nonischemic group, p = 0.26). In conclusion, most patients with LV dysfunction also have RV dysfunction. The degree of RV dysfunction is not dependent on the etiology of cardiomyopathy.
Cardiomyopathy associated with a low left ventricular (LV) ejection fraction (EF) is a common condition with known adverse prognosis. In practice, the etiology of cardiomyopathy is characterized as either ischemic or nonischemic based on the presence or absence of coronary artery disease. Patients with depressed LV systolic function often have depressed right ventricular (RV) systolic function, although the extent of dysfunction has not been well characterized in different types of cardiomyopathy. Earlier studies have suggested that RV function is more depressed in patients with idiopathic dilated cardiomyopathy compared with ischemic cardiomyopathy. However, these studies were limited by small sample sizes and by a lack of accurate RV measurement methods. Newer, 3-dimensional imaging modalities have greatly improved the accuracy of RV evaluation. Both cardiac magnetic resonance imaging and cardiac computed tomography (CT) have now been shown to accurately measure RV volumes and EF. The purpose of this study was to investigate RV function in a cohort of patients with both ischemic and nonischemic cardiomyopathy using cardiac CT to accurately evaluate RV volumes and RVEF.
Methods
We conducted a single-center, cross-sectional cohort study at the Loma Linda Veterans Affairs Healthcare System located in Loma Linda, California. Study protocol was approved by the institutional review board. Patients were included in the study if they had pre-existing LV dysfunction and had a cardiac CT angiography study at the Loma Linda Veterans Affairs Hospital between 2005 and 2011. Cardiomyopathy was determined to be either ischemic or nonischemic in etiology based on data obtained from cardiac CT angiography. Inclusion criteria dictated that subjects have (1) LVEF of ≤40% confirmed by cardiac CT, (2) cardiac CT image quality adequate to evaluate for the presence or absence of flow-limiting coronary artery disease, and (3) adequate image quality for LV and RV volume analysis. Patients who did not have cardiac CT angiography images available for evaluation through the Veterans Affairs computer system were excluded from the study.
Cardiac CT images were obtained using a Toshiba Aquilion 16-slice before September 2007 (Toshiba America Medical Systems, Tustin, California) and Siemens Definition 64-slice dual-source scanner after September 2007 (Siemens AG, Erlangen, Germany). The cardiac CT images were then evaluated for coronary artery stenosis and cardiac chamber sizing using a Vitrea 2 software and analysis package as part of usual care (Vital Images, Minnetonka, Minnesota). LV volumes were evaluated from gated 3-dimensional data sets by automated LV volume measurements, with manual corrections when needed. RV volumes were determined later as part of this research study by manually tracing the RV endocardial surface in the short-axis view at peak systole and at peak diastole from pre-existing CT data sets. From these measurements RVEF was calculated. This technique of using 16- and 64-slice CT images for RV volume assessment has been previously shown to be a reliable method compared with cardiac magnetic resonance, the gold standard for cardiac chamber volume assessment.
Etiology of cardiomyopathy was determined by standard criteria based on coronary imaging on the same data set. Patients found to have a ≥70% stenotic lesion in a proximal or midsection of at least one major epicardial coronary artery evident on CT angiography were classified as having ischemic cardiomyopathy. Patients with no coronary disease evident on CT angiography, coronary disease with stenotic lesions of <70%, or coronary disease with a ≥70% stenotic lesion limited to a branch vessel were classified as having nonischemic cardiomyopathy. Analysis of coronary arteries on CT angiography was performed by a CT-qualified cardiologist at the Loma Linda Veterans Affairs Hospital. Demographic and clinical data were collected by patient phone calls and chart review from a computerized health record.
Descriptive statistics included means and standard deviations for continuous variables and frequencies for ordinal and categorical variables. Between-group comparisons (ischemic and nonischemic cardiomyopathy) were evaluated by group means ( t -statistic with unequal variance assumed) and cross tables (chi-square statistic with appropriate continuity corrections). p ≤0.05 was considered significant. Associations between RVEF and demographic and clinical variables were estimated using generalized linear models, with adjusted estimates for age and LVEF.
Results
One hundred thirty patients were included in the study. Baseline demographic and clinical variables in nonischemic cardiomyopathy cohort (n = 74) and ischemic cardiomyopathy cohort (n = 56) are presented in Table 1 . CT data describing the extent of coronary artery disease are presented in Table 2 . LV and RV variables in nonischemic and ischemic groups are presented in detail in Table 3 . LVEF was similar in both groups with a mean LVEF of 29% in the ischemic group and 28% in the nonischemic group (p = 0.46). Despite the similarity in EF, LV end-diastolic volume and LV mass were significantly higher in the nonischemic group (p = 0.04 and p = 0.002, respectively), possibly representing a higher percentage of hypertensive cardiomyopathy in this cohort. Almost all patients in the study also had decreased RV function, with only 8 patients (6%) presenting with a normal RVEF ≥50%. RVEF or RV volumes did not differ significantly between the ischemic and nonischemic cohorts.
| Variable | Nonischemic (n = 74) | Ischemic (n = 56) | t – Test, (χ 2 test) ∗ | p – Value |
|---|---|---|---|---|
| Age (years) | 60 ± 9 | 64 ± 9 | 2.18 | 0.03 |
| Body mass index (kg/m 2 ) | 30 ± 8 | 29 ± 5 | -0.76 | 0.35 |
| Hypertension | 65 % | 61 % | 0.09 | 0.71 |
| Dyslipidemia | 53 % | 73 % | 4.83 | 0.02 |
| Chronic obstructive pulmonary disease | 27 % | 29 % | 0.00 | 0.85 |
| Obstructive sleep apnea | 15 % | 5 % | 2.09 | 0.09 |
| Diabetes mellitus type 2 | 46 % | 43 % | 0.03 | 0.86 |
| Chronic kidney disease | 15 % | 5 % | 3.22 | 0.09 |
| Atrial fibrillation | 16 % | 18 % | 0.06 | 0.82 |
| Smoking | 22 % | 21 % | 0.00 | 1.00 |
| Alcohol | ||||
| Never used | 18 % | 34 % | 5.6 | 0.35 |
| Former user | 38 % | 34 % | ||
| Use ≤7 drinks per week | 35 % | 27 % | ||
| Use >7 drinks per week | 10 % | 5 % | ||
| Extent of Coronary Artery Disease | n (%) |
|---|---|
| Three-vessel disease | 8 (14%) |
| Two-vessel disease | 24 (43%) |
| One-vessel disease with proximal involvement of left anterior descending artery | 6 (11%) |
| Other one-vessel disease with history of myocardial infarction | 20 (35%) |
| Other one-vessel disease without history of myocardial infarction | 3 (5%) |
| Variable | Nonischemic | Ischemic | t –Test | p– Value |
|---|---|---|---|---|
| Left ventricular ejection fraction | 28 ± 9 | 28 ± 6 | 0.75 | 0.46 |
| Left ventricular end-diastolic volume (mL) | 246 ± 77 | 221 ± 54 | – 2.09 | 0.04 |
| Left ventricular end-systolic volume (mL) | 177 ± 78 | 155 ± 50 | – 1.92 | 0.06 |
| Left ventricle mass (g) | 251 ± 60 | 219 ± 56 | – 3.16 | 0.002 |
| Right ventricular ejection fraction | 32 ± 10 | 34 ± 12 | 1.13 | 0.26 |
| Right ventricular end-diastolic volume (mL) | 233 ± 77 | 228 ± 90 | – 0.33 | 0.74 |
| Right ventricular end-systolic volume (mL) | 162 ± 69 | 156 ± 88 | – 0.40 | 0.69 |
Correlation between demographic and clinical variables and RV function in univariate and adjusted regression analysis is presented in Table 4 . In both univariate and adjusted analysis, RVEF was correlated with LVEF. Poor RVEF was associated with younger age. Of clinical variables, only the presence of chronic obstructive pulmonary disease was found to be negatively correlated with RVEF (p = 0.046). This correlation remained significant after adjusting for LVEF and age. When controlled for age and LVEF, RVEF did not correlate with the presence of coronary artery disease (p = 0.44) or with the presence of right coronary artery disease (p = 0.55). Additional correlation analyses performed in the ischemic and nonischemic subgroups did not yield any other significant variable correlations.
| Variable | Unadjusted | Adjusted ∗ | ||||||
|---|---|---|---|---|---|---|---|---|
| β | 95% CI | χ 2 | p – Value | β | 95% CI | χ 2 | p – Value | |
| Age (years) | 0.32 | 0.12 – 0.54 | 9.16 | 0.002 | 0.25 | 0.06 – 0.45 | 6.50 | 0.01 |
| Left ventricular ejection fraction | 0.62 | 0.39 – 0.84 | 28.4 | <0.001 | 0.57 | 0.34 – 0.80 | 22.92 | <0.001 |
| Coronary artery disease | 2.31 | – 1.65 – 6.27 | 1.30 | 0.25 | 1.38 | – 2.10 – 4.87 | 0.60 | 0.44 |
| Right coronary artery disease | 2.15 | – 1.95 – 6.26 | 1.06 | 0.30 | 1.10 | – 2.52 – 4.72 | 0.36 | 0.55 |
| Hypertension | 1.41 | – 2.81 – 5.69 | 0.43 | 0.51 | – 0.68 | – 4.56 – 3.20 | 0.12 | 0.73 |
| Chronic obstructive pulmonary disease | – 4.49 | – 8.90 – (-0.07) | 3.97 | 0.046 | – 4.87 | – 8.88 – (-0.86) | 5.67 | 0.017 |
| Obstructive sleep apnea | – 1.13 | – 5.47 – 3.21 | 0.26 | 0.61 | – 2.65 | – 7.50 – 2.19 | 1.15 | 0.28 |
| Smoking | – 0.33 | – 4.52 – 3.85 | 0.03 | 0.87 | 1.05 | – 2.88 – 4.98 | 0.27 | 0.60 |
| Alcohol use † | 6.31 | 0.28 | 7.83 | 0.17 | ||||
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