Background
Sickle cell anemia (SCA) is associated with cardiac abnormalities and premature death. The aims of this study were to identify early markers of cardiac dysfunction through ventricular strain and ventricular twist and determine the relationships between these measures and other markers of cardiovascular risk.
Methods
Forty patients with SCA (mean age, 23.5 ± 9.3 years; 24 male patients) and 40 age- and sex-matched healthy individuals were compared. All subjects participated in structured interviews, and blood samples were collected. Standard echocardiography with subsequent offline evaluations using left ventricular (LV) and right ventricular systolic strain and rotational analyses of the left ventricle using two-dimensional speckle-tracking echocardiography were performed.
Results
There were no differences in LV ejection fraction, global LV strain (longitudinal, circumferential, and radial), and global right ventricular longitudinal strain between patients and controls; however, LV twist was significantly lower in the patient group (mean, 7.4 ± 1.2° vs 10.7 ± 1.8°; P < .0001). Several variables were strongly related to LV twist, including the clinical severity index (ρ = −0.97, Z score = −6.05, P < .0001), E/e′ ratio ( r = 0.78, P < .0001), LV end-diastolic volume index ( r = 0.81, P < .0001), and pulmonary artery systolic pressure ( r = 0.72, P < .0001).
Conclusions
LV twist is altered in patients with SCA. There were strong correlations between left ventricular twist and clinical severity index, E/e′ ratio, LV end-diastolic volume index, and pulmonary artery systolic pressure. These data suggest that decreased LV twist may indicate a subgroup of patients with SCA at greater cardiac risk.
Sickle cell disease (SCD) is the most prevalent hereditary hematologic condition, affecting nearly 5 million people in the world and approximately 100,000 individuals in the United States. Sickle cell anemia (SCA) is the most serious form of the disease, as it is characterized by pronounced hemolysis and microvascular occlusion. This can lead to endothelial dysfunction, vascular proliferation, and oxidative and inflammatory stress. Given the multitude of tissues that are affected, SCA is considered a multisystemic disease that is typified by chronic and diffuse ischemia and generalized tissue injury. The cardiac changes associated with this condition have been attributed to adaptive reactions to the chronic anemic state and injuries to the cardiovascular system, which are a direct manifestation of SCD. The cardiovascular impairments most associated with SCA include cardiomegaly, pulmonary hypertension, and left ventricular (LV) diastolic dysfunction.
Changes in cardiac preload and afterload are common sequelae of anemia, making conventional echocardiography inadequate to evaluate ventricular systolic function. Given the lack of effective measurement techniques, there is no consensus as to the actual right ventricular (RV) and LV function in patients with SCA. Recently, two-dimensional speckle-tracking has been suggested to be a viable alternative to measure myocardial deformation and ventricular function, regardless of filling conditions or ventricular geometry. Despite the potential of this technique, previous investigations have limitations that have precluded definitive conclusions as to the clinical viability of speckle-tracking in the SCA population, and the results are somewhat controversial.
The purpose of this study was to investigate ventricular function using myocardial strain and LV twist, as obtained by two-dimensional speckle-tracking, in a well-defined population of patients with SCA. We hypothesized that speckle-tracking imaging in patients with SCA would identify changes in myocardial contractility that were not detectable using conventional echocardiographic techniques. The secondary aim of this study was to identify individuals with higher cardiovascular risk. We hypothesized that individuals with SCA would present with intrinsic and incipient changes in the ventricular myocardium that are correlated with clinical and laboratory markers of cardiac risk.
Methods
Study Population
Forty patients with SCA who attended at the Bloodcenter at Marilia Medical School were recruited and evaluated for this study ( Figure 1 ). The Bloodcenter serves as a major treatment center for patients with SCA in São Paulo State, Brazil. Subjects included in this report had SCA that was confirmed by hemoglobin electrophoresis. Subjects were excluded from the study if they were <14 years of age, had structural heart disease or systemic conditions that could affect cardiac function (including hypertension, diabetes, alcohol or drug abuse, pregnancy, chronic obstructive lung disease, rheumatic heart disease, or other substantial cardiomyopathies), had received any blood transfusions in the past 3 months, or had diagnosed venous occlusions within the previous 4 weeks. The study was approved by the institutional research ethics committee of the Marilia Medical School and the Dante Pazzanese Institute of Cardiology. Written informed consent was obtained from all patients.
Clinical Evaluation
Patients with SCA exhibit a wide range of clinical manifestations; however, some risk factors for disease complications can be used for predicting global disease severity. For the purposes of this study, we chose to use the modified El-Hazmi index to measure clinical severity of the disease ( Table 1 ). This index score is derived from a structured interview that includes a questionnaire about number of painful crises, blood transfusions, and ulcers in the preceding 12 months. A score ≤ 2 indicates mild severity, a score of 3 to 5 indicates moderate severity, and a score ≥ 6 indicates significant severity. After this questionnaire, transthoracic echocardiography was performed, and blood samples were obtained. The laboratory analysis included hemoglobin, hematocrit, total leukocyte count, platelet count, creatinine, C-reactive protein, reticulocytes, ferritin, serum iron, total bilirubin, direct bilirubin, indirect bilirubin, total protein, globulin, albumin, and N-terminal pro–brain natriuretic peptide. Median hemoglobin values were calculated from three monthly laboratory tests. Laboratory values were excluded if obtained during an SCA crisis or period of complication. A sex- and age-matched control individual was recruited for each individual in the test patient population.
| Finding | Score |
|---|---|
| Hemoglobin (g/dL) | |
| >11 | 0 |
| 9–11 | 1 |
| 7–9 | 2 |
| <7 | 3 |
| Chronic pain (bone, joints, abdominal, headache) | 1 |
| Painful crisis (hand-foot syndrome, bone, abdominal) | 0–12x |
| Aseptic necrosis (head of femur, humerus) | 1 |
| Osteomyelitis | 1 |
| Leg ulcers | 1 |
| Priapism | 1 |
| Pneumonia | 1 |
| Cerebrovascular accidents | 1 |
| Deep vein thrombosis | 0–12x |
| Blood transfusion | 0–12x |
| Hospitalization | 0–12x |
Echocardiographic Study
Doppler echocardiography with color flow mapping was performed using a Vivid 7 device (GE Vingmed Ultrasound AS, Horton, Norway) equipped with a multifrequency probe. Parameters measured by the M-mode and two-dimensional echocardiography were LV diastolic and systolic diameters, LV end-diastolic and end-systolic diameters (absolute values and those corrected for body surface area), diastolic thickness of the septum and posterior wall of the left ventricle, and left atrial volume index. All evaluations were performed by a single echocardiographer according to standards published by the American Society of Echocardiography.
LV end-systolic and end-diastolic volumes and LV ejection fraction were analyzed offline using a semiautomatic measurement tool for global ejection fraction evaluation (see “Speckle-Tracking Strain Analysis and Twisting”). LV mass was calculated by using the American Society of Echocardiography’s cube method according to the Deveureux modification and normalized for body surface area. Tricuspid annular plane systolic excursion was measured in the four-chamber view using M-mode echocardiography.
LV outflow velocity integrals and right ventricular outflow were also collected as surrogate measures of systemic and pulmonary flow, respectively. Systolic pulmonary pressure, on the basis of the velocity of the tricuspid regurgitation jet, was calculated using a modified Bernoulli equation and an estimation of right atrial pressure. To observe the mean pressure of the right atrium, the size and spontaneous respiratory variation of the inferior vena cava was evaluated using the subcostal plane.
LV diastolic function was assessed by pulsed Doppler of the mitral inflow and by Doppler tissue imaging measurements, obtained at the medial and lateral border of the mitral annulus in the apical four-chamber view. Systolic tissue Doppler velocity (S′) and early (e′) and late (A′) diastolic tissue velocities were acquired, and the ratio of the mitral E velocity to mean e′ was calculated (E/e′). RV tissue Doppler imaging was performed at the lateral tricuspid annulus in the apical four-chamber view, where peak systolic (S′) and early (e′) and late (A′) diastolic velocities were measured. Measurements were averaged over three beats.
Speckle-Tracking Strain Analysis and Twisting
Two-dimensional images used to evaluate myocardial deformation and rotation were obtained using parasternal and apical approaches. Care was taken to ensure that the basal short-axis planes contained the mitral valve and that the apical plane was acquired distally to the papillary muscles. In each short-axis acquisition, the LV cross section was made as circular as possible. At each plane, three consecutive cardiac cycles were acquired and digitally stored on a hard disk for offline analysis.
The time interval between the peak of the R wave on the electrocardiogram and aortic valve opening and closure, and the time from the R wave to mitral valve opening and closure, was measured using pulsewave Doppler from the LV outflow and inflow, respectively. End-systole was defined as the point of aortic valve closure. Frame rates ranged between 50 and 70 Hz, as recommended by the American, European and Japanese societies of echocardiography.
The left ventricle was divided into 18 segments using commercially available software (EchoPAC PC version 7.0.X; GE Healthcare, Fairfield, CT). A semiautomatic system of myocardial delineation was used, although the endocardial border and areas of interest were manually adjusted. In evaluating deformation, only those segments whose tracking quality was considered adequate by both the automatic analysis system and visual inspection were used in the analysis. Subsequent to the validation process, the system calculated ventricular volumes and ejection fraction according to two-dimensional Simpson’s formula.
LV longitudinal strain was assessed in all six LV walls in the three-chamber apical view. RV longitudinal strain was also measured in a four-chamber view, using the same software. Radial and circumferential strains were assessed in the six LV walls in the parasternal LV short-axis view at the levels of the papillary muscles and mitral valve. Global longitudinal, radial, and circumferential strains were obtained by dividing the sum of the strain from all LV walls segments by the number of segments.
To assess LV rotation, the endocardial border was traced in end-diastole, and the software then automatically detected the region of interest from the epicardial to the endocardial layer. LV twist was automatically calculated as the net difference between the rotation of the apex and the rotation of the base in systole. Time to peak rotation of the apex was included in the analysis.
Offline Analysis
Digital images were obtained digital cine-loop format for offline analysis in EchoPAC PC version 7.0.X. The images were analyzed at Dante Pazzanese Institute of Cardiology, in São Paulo, Brazil. Global longitudinal LV and RV strain, global LV circumferential and radial strain, and LV twist were measured using two-dimensional strain software.
Statistical Analysis
Continuous variables are expressed as mean ± SD. Nominal variables were expressed as absolute values, as well as frequencies and/or percentages as appropriate. The data were compared between groups (patients vs controls) using a one-way analysis of variance. Linear and binomial regressions were applied to determine independent clinical and laboratory predictors of ventricular contractility. Spearman correlations were used to quantify the relationship between ventricular twist and measures of clinical severity. Statistical calculations and preparation of the tables were performed using Microsoft Excel 2000 (Microsoft Corporation, Redmond, WA) and StatView version 5.0 (SAS Institute Inc, Cary, NC).
Intraobserver and interobserver variability for the three types of LV strain, RV strain, and LV twist were assessed in all 40 patients and 40 controls using the Bland-Altman approach. Mean bias (average difference between measurements) and the lower and upper limits of agreement (95% limits of agreement of the mean bias) were calculated for this analysis. In addition, the coefficient of variation (SD of the difference of paired samples divided by the average of the paired samples) and the intraclass correlation coefficient were assessed. To measure reproducibility, the first examiner analyzed the echocardiographic images at the workstation without knowledge of the individual or group being analyzed. To determine the intraobserver variability, the same examiner evaluated the images 2 months later without knowledge of the initial results. At this follow-up session, a second examiner, who was not aware of the first examiner’s results, performed a concurrent analysis to establish interobserver variability.
Results
Clinical Characteristics and Laboratory Studies
A total of 48 patients with SCA who were referred to the Bloodcenter of the Marilia Medical School were initially considered for the study. Eight patients were subsequently excluded from the study ( Figure 1 ). A total of 40 patients with SCA, genotype HbSS, ranging from 14 to 45 years of age, were included. The control group consisted of 40 age- and gender-balanced control subjects ( Table 2 ). The majority of the sample was male (60%), with an average age of 23 years. Body surface areas and blood pressures were lower in the patients with SCA, while heart rates were similar to those in controls ( Table 2 ).
| Variable | Patients ( n = 40) | Controls ( n = 40) | P |
|---|---|---|---|
| Male sex | 24 (60%) | 24 (60%) | |
| Age (y) | 23.5 ± 9.3 | 23.6 ± 9.3 | .98 |
| Body surface area (m 2 ) | 1.6 ± 0.17 | 1.8 ± 0.2 | <.0001 |
| Heart rate (beats/min) | 81.9 ± 6.0 | 78.3 ± 6.8 | .0145 |
| Systolic blood pressure (mm Hg) | 102.0 ± 10.9 | 114.2 ± 9.8 | <.0001 |
| Diastolic blood pressure (mm Hg) | 66.0 ± 6.3 | 76.5 ± 4.8 | <.0001 |
On the modified El-Hazmi index, no patients were classified as mild severity (score ≤ 2) and 5% were classified as moderate severity (scores of 3–5). The large majority (95%) were classified as having significant clinical symptoms (score ≥ 6), suggesting that the most of the patients had severe SCA disease. The mean score on the modified El-Hazmi index was 15 in our sample. There was also a large frequency of abnormal laboratory values, which is consistent with the SCA population ( Table 3 ).
| Variable | Mean ± SD | Reference values † |
|---|---|---|
| Hemoglobin (g/dL) | 8.4 ± 1.3 | 13.5–17.5 (men), 12–16 (women) |
| Hematocrit (%) | 25.3 ± 4.0 | 41–53 (men), 36–46 (women) |
| Leukocyte count (×1,000/μL) | 11.3 ± 2.8 | 4.5–11 |
| Platelet count (×1,000) | 472.5 ± 169.4 | 150–350 |
| Reticulocytes (%) | 20.9 ± 5.9 | 0.5–2.5 |
| Creatinine (mg/dL) | 0.5 ± 0.2 | <1.5 |
| C-reactive protein (mg/L) | 11.6 ± 21.6 | 0.08–3.1 |
| Ferritin (ng/mL) | 880.4 ± 882.6 | 30–300 (men), 10–200 (women) |
| Iron (μg/dL) | 131.7 ± 65.5 | 30–160 |
| Total bilirubin (mg/dL) | 4.0 ± 3.0 | 0.3–1 |
| Direct bilirubin (mg/dL) | 0.4 ± 0.3 | 0.1–0.3 |
| Indirect bilirubin (mg/dL) | 3.6 ± 2.9 | 0.2–0.7 |
| Albumin (g/dL) | 4.3 ± 0.4 | 3.5–5.5 |
| NT-proBNP (pg/mL) | 119.5 ± 94.9 | <167 ‡ |
∗ Measured in 40 patients with sickle cell anemia.
† Reference laboratory range values.
Echocardiographic Measurements in Patients and Controls
Structural echocardiographic data of the SCA patient and control groups can be found in Table 4 . The patient group had significantly higher values than the control group for all parameters related to chamber mass and volume with ( P < .0001). There was no difference between groups for LV ejection fraction, as measured by the biplane Simpson’s method ( P = .097) ( Table 5 ). There was also no significant difference between groups for tricuspid annular plane systolic excursion, which is a measure of RV systolic function ( P = .43). However, systemic velocity-time integral, which is a surrogate parameter of stroke volume, was significantly higher in the SCA compared with the control group ( P < .0001). The indirect measurement of pulmonary flow (pulmonary velocity-time integral) was also significantly higher in the SCA group ( P < .0001). Similarly, estimates of pulmonary artery systolic pressure were significantly greater in the SCA patient group compared with the control subjects (35.9 ± 5.5 vs 22.9 ± 5.9 mm Hg, P < .0001).
| Variable | Patients ( n = 40) | Controls ( n = 40) | P |
|---|---|---|---|
| LVEDV (mL) | 128.3 ± 20.3 | 80.4 ± 18.8 | <.0001 |
| LVEDV index (ml/m 2 ) | 80.4 ± 15.6 | 44.2 ± 9.3 | <.0001 |
| LV mass (g) | 218.8 ± 18.1 | 128.1 ± 17.7 | <.0001 |
| LV mass index (g/m 2 ) | 137.1 ± 19.6 | 70.7 ± 9.9 | <.0001 |
| LAVi (mL/m 2 ) | 32.7 ± 5 | 18.7 ± 4 | <.0001 |
| LVEF (%) | 64.9 ± 2.7 | 62.8 ± 3.8 | .097 |
| TAPSE (cm) | 2.6 ± 0.2 | 2.6 ± 0.2 | .43 |
| VTI systemic | 30.4 ± 4.5 | 25.0 ± 3.2 | <.0001 |
| VTI pulmonary | 41.3 ± 21.4 | 23.5 ± 5.3 | <.0001 |
| PASP(mm Hg) | 35.9 ± 5.5 | 22.9 ± 5.9 | <.0001 |
| Variable | Patients ( n = 40) | Controls ( n = 40) | P |
|---|---|---|---|
| E peak velocity (cm/sec) | 124.2 ± 11.0 | 109.3 ± 10.8 | <.0001 |
| S septal (cm/sec) | 7.1 ± 0.79 | 7.0 ± 0.6 | .54 |
| e septal (cm/sec) | 11.1 ± 1.2 | 14.6 ± 0.7 | <.0001 |
| A septal (cm/sec) | 6.9 ± 0.6 | 6.8 ± 0.5 | .29 |
| S lateral (cm/sec) | 9.0 ± 0.8 | 9.0 ± 0.6 | .97 |
| e lateral (cm/sec) | 10.7 ± 1.9 | 12.3 ± 1.8 | .0002 |
| A lateral (cm/sec) | 8.4 ± 0.5 | 8.0 ± 0.6 | .007 |
| E/e septal | 11.4 ± 1.9 | 7.5 ± 0.8 | <.0001 |
| E/e lateral | 12.1 ± 3.1 | 9.0 ± 1.4 | <.0001 |
| E/e ratio mean | 11.7 ± 2.3 | 8.3 ± 0.9 | <.0001 |
| S lateral RV (cm/sec) | 14.4 ± 0.6 | 14.0 ± 0.60 | .006 |
| e lateral RV (cm/sec) | 12.4 ± 1.7 | 12.2 ± 1.4 | .52 |
| A lateral RV (cm/sec) | 9.8 ± 0.7 | 9.5 ± 0.5 | .05 |
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
