Added value of speckle tracking in the evaluation of cardiac
function in patients with sickle cell disease
Speckle tracking echocardiography is a new means of evalu-ating cardiac function. The principle of speckle tracking is to measure myocardial strain, based on local shortening, length-ening and thicklength-ening of the muscles.
It has been proposed that the left ventricle global longitu-dinal strain (LV-GLS) could be a useful tool for the detection of early systolic dysfunction in patients under cardiotoxic chemotherapy (Thavendiranathan et al, 2014). Moreover, the high reproducibility of the LV-GLS represents an advantage over the left ventricle ejection fraction (LVEF) (King et al, 2016; Medvedofsky et al, 2017). Compared to the LVEF, the LV-GLS is less affected by changes in loading conditions, which makes it a potentially useful tool in patients with sickle cell disease (SCD), due to the chronic overload associ-ated with SCD. However, in this population, studies are rare and results are conflicting (Ahmad et al, 2012; Sengupta et al, 2012; Barbosa et al, 2014; Hammoudi et al, 2014).
The primary aim of our study was to determine whether the LV-GLS was abnormal in a monocentric population of adults with SCD, compared to a matched population of healthy individuals. The secondary aim was to investigate correlations between the echocardiographic parameters and the biological and clinical evaluations of patients with SCD. The institutional Ethics Committee approved the protocol. All patients provided informed consent.
We prospectively included 37 patients with SCD and 34 healthy, age- and sex-matched controls. The patient and con-trol groups were similar in age (31 10 years vs. 32 10 years, respectively).
The LVEF was significantly lower in the SCD group than in the control group (Teicholz: 618% vs. 676%; P = 005; Simpson: 619% vs. 693%; P < 005; Table I). However, only one patient had a Simpson LVEF< 50%. The left ventricular (LV) mass and LV end diastolic diameter (LVEDD) were higher in the patient group (LV mass: 107 g/m2vs. 70 g/m2, P < 005 and LVEDD: 53 mm vs. 46 mm; P < 005). The myocardial performance index was higher (higher values indicate impaired LV function) in the patient group com-pared to the control group (038 vs. 027; P < 005). The LV-GLS was significantly lower in the SCD group than in the control group (194% vs. 224%; P < 005), and it was abnormal (strain > 18%) in 8 (21%) patients of the SCD group. Diastolic function was abnormal in three SCD patients (8%), but normal in the entire control group. The tricuspid regurgitation velocity was higher in the SCD group
than in the control group (224 m/s vs. 196 m/s, P < 005). However, no patient had pulmonary hypertension.
The multivariate analysis results (Table II) showed that only the LV-GLS and LVEDD remained significantly different between groups.
Among patients with SCD, the mean Hb was 94 g/l (range: 61–122 g/l) and the mean HbF was 127% (range: 1– 286%). The mean ferritin level was 644 lg/l (range: 13– 7267lg/l). Iron overload, defined as a ferritin level greater than 1000lg/l, was observed in five patients. The mean N-terminal pro b-type natriuretic peptide (NTproBNP) level was 154 pg/ml (range 12–1685 pg/ml). The mean patient walking distance was 66% of the predicted value (range: 33–88%).
Table I. Univariate analysis results show differences between SCD and healthy controls.
Parameter Control SCD P LVEF-Teicholz (%) 676 69 618 62 <005 LVEF-Simpson (%) 693 53 619 72 <005 LVEF< 50% 0 1 (27%) MPI 027 008 038 12 <005 LV-GLS (%) 224 28 194 24 <005 LV-GLS< 18% 0 8 (21%) TRV (m/s) 196 021 224 025 <005 E/A 163 035 157 04 NS E0(m/s) 016 003 015 004 NS E/E0 564 134 644 176 NS (0054) DT (ms) 187 36 194 37 NS Diastolic dysfunction 0 3 (8%) NS LVEDD (mm) 46 49 53 51 <005 LV mass (g/m2) 70 28 107 45 <005 LVH 0 18 (48%) <005 Results are expressed as the mean standard deviation.
DT, deceleration time of E mitral wave; E0, early diastolic mitral annular tissue Doppler velocity; E/A, early peak diastolic velocity of the mitral inflow/late peak diastolic velocity of the mitral inflow; E/ E0, ratio between peak velocities of mitral E wave and early-diastolic mitral annulus; LV mass, left ventricular mass; LV-GLS, left ventricle global longitudinal strain; LVEDD, left ventricular end-diastolic diameter; LVEF, left ventricular ejection fraction; LVH, left ventricu-lar hypertrophy; MPI, myocardial performance index; NS, not signif-icant; SCD, sickle cell disease; TRV, maximal tricuspid regurgitation velocity.
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A correlation was found between the ferritin level and the LVEF (P= 004) and the LVEF and LV-GLS (P = 0027). No correlation was found between NTproBNP level and LVEF (P= 0569) NTproBNP and LV-GLS (P = 0859), walking distance test and LVEF (P= 02) and walking distance test and LV-GLS (P= 0106).
Our study showed that GLS was a more powerful index of systolic function than LVEF in patients with SCD. Indeed, the GLS was abnormal in 8 (21%) of 37 patients; in contrast, the LVEF was abnormal in only one of these patients. We could not find a correlation between LV-GLS and the walk-ing distance test or the NTproBNP level. The small number of patients included in the study might explain these results.
Furthermore, walking distance test can also be influenced by anaemia, as could be NTproBNP level (Karakoyun et al, 2017).
We conclude that the LV-GLS, an emerging sensitive and reproducible parameter of systolic function, appeared to be an effective tool for the detection of early systolic dysfunc-tion in patients with SCD.
However, the clinical impact of an altered LV-GLS in patients with SCD remains to be assessed: larger studies, with a longer follow-up, should be conducted to confirm our results and to evaluate whether LV-GLS might have prognos-tic implications and whether it should be recommended in routine evaluations of these patients.
Author’s contributions
MM, MAA, and AE designed the study; MM and TBH per-formed the research; MM and JCR analysed the data; MM and JCR wrote the paper. All authors were involved in manuscript preparation and approved the final version of the manuscript.
Conflict of interest disclosure
None.
Marielle Morissens1 Jose Castro Rodriguez1 Marie-Agnes Azerad2 Tatiana Besse-Hammer3 Andre Efira2
1Departement de cardiologie, service de Medecine Interne, CHU
Brug-mann,2Departement d’hemato-oncologie, service de Medecine Interne, CHU-Brugmann, and3Departement de recherche Clinique, CHU Brugmann, Bruxelles, Belgium.
E-mail: marielle.morissens@chu-brugmann.be
Keywords: sickle cell disease, speckle tracking, longitudinal strain, systolic function
First published online 19 June 2018 doi: 10.1111/bjh.15398
References
Ahmad, H., Gayat, E., Yodwut, C., Abduch, M.C., Patel, A.R., Weinert, L., Desai, A., Tsang, W., Gar-cia, J.G., Lang, R.M. & Mor-Avi, V. (2012) Evalu-ation of myocardial deformEvalu-ation in patients with sickle cell disease and preserved ejection fraction using three-dimensional speckle tracking echocar-diography. Echocardiography, 29, 962–969. Barbosa, M.M., Vasconcelos, M.C., Ferrari, T.C.,
Fernandes, B.M., Passaglia, L.G., Silva, C.M. & Nunes, M.C. (2014) Assessment of ventricular function in adults with sickle cell disease: role of two-dimensional speckle-tracking strain. Journal
of the American Society of Echocardiography, 27, 1216–1222.
Hammoudi, N., Arangalage, D., Djebbar, M., Sto-janovic, K.S., Charbonnier, M., Isnard, R., Girot, R., Michel, P.L. & Lionnet, F. (2014) Subclinical left ventricular systolic impairment in steady state young adult patients with sickle-cell ane-mia. International Journal of Cardiovascular Imaging, 30, 1297–1304.
Karakoyun, I., Colak, A., Arslan, F. D., Asturk, A.G. & Duman, K. (2017) Anemia considera-tions when assessing natriuretic peptide levels in ED patients. American Journal of Emergency Medicine, 35, 1677–1681.
King, A., Thambyrajah, J., Leng, E. & Stewart, M.J. (2016) Global longitudinal strain: a useful every-day measurement? Echo Research and Practice, 3, 85–93.
Medvedofsky, D., Kebed, K., Laffin, L., Stone, J., Addetia, K., Lang, R.M. & Mor-Avi, V. (2017) Reproducibility and experience dependence of echocardiographic indices of left ventricular function: side-by-side comparison of global longitudinal strain and ejection fraction. Echocardiography, 34, 365– 370.
Sengupta, S.P., Jaju, R., Nugurwar, A., Caracciolo, G. & Sengupta, P.P. (2012) Left ventricular
Table II. Multivariate analysis results show factors significantly related to SCD.
Factors Control SCD P multivariate LVEF-Teicholz (%) 676 69 61. 8 62 NS LVEF-Simpson (%) 693 53 619 72 NS MPI 027 008 038 12 NS LV-GLS (%) 224 28 194 24 <005 TRV (m/s) 196 021 224 025 NS E/A 163 035 157 04 NS E0(m/s) 016 003 015 004 NS E/E0 564 134 644 176 NS DT (ms) 187 36 194 37 NS LVEDD (mm) 46 49 53 51 <005 LV mass (g/m²) 70 28 107 45 NS LVH 0 18 (48%) NS Diastolic dysfunction 0 3 (8%)
Results are expressed as the mean standard deviation.
DT, deceleration time of E mitral wave; E0, early diastolic mitral annular tissue Doppler velocity; E/A, early peak diastolic velocity of the mitral inflow/late peak diastolic velocity of the mitral inflow; E/ E0, ratio between peak velocities of mitral E wave and early-diastolic mitral annulus; LV mass, left ventricular mass; LV-GLS, left ventricle global longitudinal strain; LVEDD, left ventricular end-diastolic diameter; LVEF, left ventricular ejection fraction; LVH, left ventricu-lar hypertrophy; MPI, myocardial performance index; NS, not signif-icant; SCD, sickle cell disease; TRV, maximal tricuspid regurgitation velocity.
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myocardial performance assessed by 2-dimen-sional speckle tracking echocardiography in patients with sickle cell crisis. Indian Heart Jour-nal, 64, 553–558.
Thavendiranathan, P., Poulin, F., Lim, K.D., Plana, J.C., Woo, A. & Marwick, T.H. (2014) Use of myocardial strain imaging by echocardiography for the early detection of cardiotoxicity in
patients during and after cancer chemotherapy. A systematic review. Journal of the American College of Cardiology, 63, 2751–2768.
A significant proportion of children of African descent with
HbS
b
0
thalassaemia are inaccurately diagnosed based on
phenotypic analyses alone
Two sickle cell disease (SCD) phenotypes, HbSS and HbSb0 thalassaemia, are believed to be so similar in disease severity that all major paediatric National Institute of Health ran-domized controlled trials include both (Wang et al, 2011; DeBaun et al, 2014; Brousseau et al, 2015). However, data from our group and others suggest the two diagnoses are associated with different clinical courses (Serjeant et al, 1979; Zago et al, 1980), highlighting the importance of accurately distinguishing the two. In a cross-sectional study, we tested two hypotheses: (i) a subset of phenotypic diagnoses of HbSb0 thalassaemia and HbSS are discordant with their genotypic diagnoses; and (ii) phenotypic misclassification of HbSb0thalassaemia is associated with alpha-chain deletions.
We used data from the multicentre Silent Cerebral Infarct Transfusion (SIT) Trial (DeBaun et al, 2014). Individuals aged 5–15 years with HbSS or HbSb0 thalassaemia by prior high-performance liquid chromatography (HPLC), isoelectric focusing (IEF), or DNA sequencing were eligible. Two Texas sites incorporated DNA sequencing into routine state new-born screening, while the other 27 sites used HPLC/IEF with laboratory parameters. At all sites, red blood cell (RBC) indices (mean cell volume [MCV] measurements and RBC counts) and HbA2 percentages were obtained at screening. DNA sequencing was performed or repeated on all samples at the Centers for Disease Control and Prevention (CDC) (Bean et al, 2014). All samples were run on an ABI 3730 DNA Analyzer, and sequences were reviewed using Sequenc-ing Analysis 5.2 (Applied Biosystems, Inc., Foster City, CA, USA). Polymerase chain reaction techniques (Bean et al, 2012) determined the number of alpha-chain deletions on all participants. Informed consent and Institutional Review Board approval were obtained.
We defined “phenotypic diagnosis” as a diagnosis through HPLC/IEF with laboratory parameters (RBC indices and HbA2 percentages). We defined “genotypic diagnosis” as a diagnosis through DNA sequencing, and “phenotypic misclas-sification” as discordant phenotypic and genotypic diagnoses.
We performed two analyses: (i) phenotypic diagnoses at study entry were compared to diagnoses from CDC genotyp-ing; (ii) newborn genotypic diagnoses from Texas sites were compared to CDC genotypic diagnoses. Diagnoses with and
without phenotypic misclassification were compared to par-ticipant characteristics with Mann-Whitney U-tests. An exact McNemar test assessed the paired phenotypic diagnosis of
Table I. Comparison of those with and without phenotypic misclas-sification of HbSb0thalassaemia (n= 53) and HbSS (n = 698) based
on the number of alpha-chain deletions and blood indices. Phenotypic diagnosis matches genotypic diagnosis P-value No Yes Beta-globin phenotype HbSS 6 (09%) 692 (991%) <0001* HbSb0thalassaemia 39 (736%) 14 (264%) HbSb0thalassaemia phenotype
Alpha chain deletions 0119‡ 2 alpha-chain deletions 11 (282%) 1 (71%) 1 alpha-chain deletion 13 (333%) 5 (357%) 0 alpha-chain deletions 15 (385%) 8 (571%) Totals 39 14 Blood indices†
Mean cell volume 7200 (1250) 7035 (530) 0793‡ HbA2percentage 438 (100) 470 (125) 0639‡
Red blood cell count 330 (110) 390 (095) 0005‡ HbSS phenotype
Alpha chain deletions 0628‡ 2 alpha-chain deletions 0 (00%) 28 (40%) 1 alpha-chain deletion 2 (333%) 262 (379%) 0 alpha-chain deletions 4 (667%) 402 (581%) Totals 6 692 Blood indices†
Mean cell volume 696 (3173) 839 (950) 0173‡ HbA2percentage 45 (350) 30 (100) 0067‡
Red blood cell count 335 (125) 27 (068) 0039‡ *Exact McNemar test.
†Median (interquartile range) for each value given. ‡Mann-Whitney U-Test.
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