Skip to main content
Download PDF

Evaluation of the efficacy of signal-averaged electrocardiogram testing in the cardiac assessment of beta-thalassemia major patients

BMC Cardiovascular Disorders volume 22, Article number: 534 (2022) Cite this article

Abstract

Background

More than 70% of thalassemia’s major mortality is due to the cardiac complications of this syndrome, mostly consequent to myocardial Iron overload; therefore, evaluation of such complications is of utmost importance. T2*MRI is used to assess hepatic and myocardial Iron load in thalassemia patients, which is not always available. Signal-Averaged Electrocardiography is a rather easy method of evaluating major thalassemia patients regarding their risk for sudden cardiac death.

Methods and materials

In this cross-sectional study, 48 patients with thalassemia major underwent evaluation with electrocardiography, signal-averaged electrocardiography, echocardiography, T2*MRI, and ferritin level. The association of the existence of ventricular late potentials in SAECG and other cardiac variables was evaluated. Moreover, the association between myocardial and hepatic Iron load and cardiac characteristics was assessed.

Results

48 patients with a mean age of 30.31 ± 7.22 years old entered the study. 27 (56.3%) of the patients had ventricular late potentials, which were associated with myocardial dry Iron weight (P = 0.011). Nonspecific ST-T changes and premature atrial and ventricular contractions were seen more frequently in patients with late potentials (P = 0.002, 0.031, and 0.031, respectively). Patients with higher myocardial and hepatic Iron loads had longer QTc in their 12-lead surface electrocardiograms.

Conclusion

Patients with ventricular late potentials assessed by SAECG had a higher myocardial Iron load. Higher myocardial Iron load is associated with higher cardiac complications in patients with beta-thalassemia major; therefore, SAECG can be used as a screening test for cardiac complications in beta-thalassemia major patients.

Peer Review reports

Introduction

Major beta-thalassemia is an inherited hypoproliferative anemic syndrome characterized by hypochromia, microcytosis, and a substantial decline in β chain synthesis that acts as a major concern in healthcare systems around the world [1]. Patients with major thalassemia present with jaundice, dysmorphic musculoskeletal structures, and growth retardation, and they need to receive a tremendous amount of blood transfusions during their lifetime [2]. Long-term infusion of blood products puts the patients at higher risk for Iron overload that deposits in various tissues such as the liver and the heart [3].

Excessive Iron overload in cardiac tissues in major beta-thalassemia patients results in various cardiac complications such as dilated cardiomyopathy, arrhythmias, and congestive heart failure [4]. Such cardiac complications of major thalassemia impose significant risks of morbidity and mortality on the patients to a level that more than 70% of major thalassemia patients die due to cardiac complications of this disease [5, 6].

Hepatic and cardiac Iron overload in major thalassemia patients can be assessed using imaging modalities such as T2* magnetic resonance imaging (T2*MRI) [7]. T2*MRI conduction time has been shown to be indicative of cardiac diastolic function and serum ferritin level [8, 9]. Therefore, T2*MRI can be used to detect cardiovascular complications of major thalassemia. However, this imaging modality is not always accessible and is an expensive diagnostic method.

The Signal-Averaged electrocardiogram is a rather easy method of evaluating major thalassemia patients regarding their risk for sudden cardiac death [10]. Electrophysiologic abnormalities in this population prompt appropriate treatment implementation based on novel findings using modalities such as SAECG, which has long been neglected [11, 12]. Though in this article, we assessed the cardiac function in beta-thalassemia patients with echocardiography and twelve-lead surface electrocardiogram, and we aimed to evaluate the association of SAECG findings in these patients with T2*MRI as an indication of Iron overload.

Methods and materials

Ethical statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Committee of ethics in biomedical research of Shiraz University of Medical sciences by the code IR.SUMS.MED.REC.1400.235. A written consent form was obtained from the patients or their legal guardians.

Study population

Based on a similar study conducted by Aggarwal et al. considering a type I error of 0.05 and a study power of 80%, using MedCalc Software, the minimal sample size for the study to be statistically significant was 46. The samples were chosen among Major Thalassemia patients referred to the Genetic Research Center of Shahid Dastgheib Hospital affiliated with Shiraz University of Medical Sciences with a random convenience method. The recruitment of the participants lasted from August 2020 to March 2022.

Eligibility criteria

The inclusion criteria of our study were 10–45-year-old Major Beta-Thalassemia patients who required repeated blood transfusions and Iron chelators from their childhood. The exclusion criteria of our study were: being afflicted with hypertension, diabetes mellitus, gout, ischemic heart disease, cardiac or vascular anomalies (congenital heart disease and valvular disease, among others), and history of active cigarette smoking, any present inflammatory symptoms such as rhinorrhea, cough, pharyngitis, fever, and rhinorrhea, any history of inflammatory diseases such as rheumatoid arthritis and inflammatory bowel disease, the unwillingness of the patients or their legal guardians to participate in the study, and being younger than 10 years old or older than 45 years old.

Study design

This study followed a descriptive cross-sectional protocol involving 48 MT patients referred to the Genetic Research Center of Shahid Dastgheib Hospital, affiliated with Shiraz University of Medical Sciences. 48 patients with major thalassemia requiring repeated blood transfusions aged between 10–45 years old entered the study. The sampling followed a randomized convenience method.

In this study, a checklist was filled out for each patient after obtaining the written consent form from the patients or their legal guardians. The checklist consisted of five sections. First, demographic information such as age, sex, the frequency of packed cell transfusions, the interval between transfusions, the total number of transfused packed cells, and age at the time of first blood transfusion. The second part of the checklist was attributed to the past medical history of the patients, such as the history of diabetes mellitus, hypothyroidism, adrenal insufficiency, and history of splenectomy, as well as drug history (including Deferiprone, Desfonac, Osfera, and Deferoxamine). The third section involved the information obtained from echocardiography and cardiac Magnetic Resonance Imaging of the patients, such as left ventricular systolic and diastolic function, cardiac chamber sizes, and iron loading state in T2* mapping of liver and heart besides the dry weight of Iron in the heart and the liver. The fourth section of the checklist included the biochemical lab data of the patients as serum ferritin level (Enzyme Immunoassay method, WHO Ferritin 80/602 First International Standard, reference range 15–300 ng/dL), Calcium, 25(OH) Vitamin D3, and average pre-transfusion hemoglobin level. The fifth part of the checklist was allocated to electrocardiographic findings (P-wave duration, T-wave duration, P-Q interval, and QTc) in a six-minute ECG. Signal Averaged Electrocardiographic findings (Filterd QRS duration, LAS-40, RMS-40) were included in this section.

Variables and data measurement

Signal‐averaged electrocardiography (SAECG) records low‐amplitude electrical activity in the myocardium. It is used to detect the depolarization of ventricular areas with slow consequences to Iron overload manifested as late potentials (LPs). LPs are described by the duration of the terminal portion of the QRS complex that displays slow amplitude signals (less than 40 μV, known as LAS‐40) and indirectly by the total duration of the filtered QRS complex. Their magnitude is measured by the root mean square voltage of the terminal 40 ms of the filtered QRS complex (RMS‐40). The criteria for diagnosis of LPs proposed in 1991 include (i) filtered QRS duration ≥ 114 ms, (ii) RMS‐40 < 20 μV, and (iii) LAS‐40 > 38 ms [25]. Importantly, these measurements were validated under the strict requirement for the presence of narrow QRS complexes in a standard 12‐lead ECG, thereby excluding a large proportion of patients with right or left bundle branch block or with wide QRS complexes and nonspecific intraventricular conduction defects. To overcome this limitation, modified criteria have been suggested in such patients, encompassing longer duration and lower amplitude of LPs; specifically, (i) filtered QRS ≥ 145 ms, (ii) RMS‐40 < 17.5 μV, and (iii) LAS‐40 > 50 ms can be applied in cases of wide QRS complexes [26]. LPs are generally considered to present when at least 2 of 3 conventional or modified criteria are met.

All of the SAECGs were obtained with “late potential ECG” software from Biomedical Systems revision 5. 0. 3 with an HP Filter of 40–250 Hz and an average beat of 250. HF Noise of less than 0.5 microvolts were considered acceptable. Conventional twelve-lead ECG was also obtained from all patients.

Cardiovascular Magnetic Resonance (CMR) imaging is used as a noninvasive method to evaluate the amount of iron in the heart. MRI examinations were performed with a 1.5 Tesla (T) Magnetom Avanto scanner (Siemens, Erlangen, Germany). The scans included measurement of the liver R2 value and the myocardial T2* value. The scan duration was 45 min. The T2* of the heart was assessed by a cardiac gated single breath-hold multi-echo technique. T2* analysis was conducted using Thalassemia Tools via CVI42 software from Circle company, Calgary, Canada. A full-thickness region of interest (ROI) was drawn in the mid-interventricular septum. The signal intensity of this region for each echo time was measured and plotted as an exponential signal decay curve. Post-processing of acquired images was done by plotting signal intensities and using the curve fitting technique by the CMR42 workstation.

The lower limit of normal for T2* in the detection of myocardial iron deposition has been reported as 20 ms, and this value was used as the cut-off in this study [10]. Patients were divided into 3 groups based on their T2*duration; patients with T2* > 20 ms were considered to be free of cardiac Iron overload, where patients with T2* ≤ 20 ms were deemed to have cardiac Iron overload, and patients with T2* between 10–20 ms were considered to have a moderate Iron overload. Liver MRI scans and cardiac MRI examinations were performed on the same day.

Statistical analyses

The data were entered into IBM SPSS version 22.0 (Chicago, Illinois, USA). The qualitative data were reported as frequency and percentages, and the quantitative variables were reported as Mean ± SD. T2* was shown as a geometric mean (a log transformation was performed to normalize the data). Correlations between the myocardial T2* value, liver T2* value, echocardiographic parameters, and the serum ferritin level were assessed by Spearman’s rank test. The parameters observed at different levels of T2* and late potentials were compared using one-way ANOVA (analysis of variances). For the comparison of categorical variables, chi-square and Fisher’s exact tests were used, while an independent two-sample T-test was applied for continuous variables. P-values less than 0.05 were considered statistically significant.

Results

A total of 48 patients with major thalassemia entered the study. 64.6% (31) of the patients were male, and 35.4% (17) were female. The mean age of the participants was 30.31 ± 7.22 years old. The mean age at which transfusions were initiated was 14.94 ± 15.90 months old. The interval between transfusions varied between 14 to 30 days. The mean number of total transfused packed cells in patients was 1077.08 ± 360.30. the average serum ferritin level of the patients was 4020.94 ± 4132.31 ng/ml ranging from 155 to 15,387 ng/ml.

T2* MRI results

Myocardial and hepatic Iron load were assessed using T2* MRI. In this study, the mean myocardial T2* and hepatic T2* conduction times were 20.29 ± 12.44 and 6.45 ± 6.26 ms, respectively. The findings were equivalent to 2.74 ± 2.55 and 13.99 ± 15.49 mg/g dry Iron weight.

In this study, 25 (52.1%) of the patients had a normal myocardial Iron load (T2*MRI > 20 ms), 6 (12.5%) had moderate myocardial Iron overload (T2*MRI 10–20 ms), and 15 (35.4%) had severe myocardial Iron overload (T2*MRI < 10 ms). 10 (20.8%) patients had a normal hepatic Iron load (T2*MRI > 11.4 ms), while 18 (37.5%) had moderate hepatic Iron overload (T2*MRI 3.3–11.3 ms), and 20 (41.7%) had severe hepatic Iron overload (T2*MRI < 3.3 ms).

SAECG parameters

All of the patients underwent cardiac assessment by SAECG, six minutes12-lead surface ECG, and Echocardiography. 27 (56.3%) of the patients had ventricular late potentials in their SAECG. 18 (37.5%) of the patients had filtered QRS duration > 114 ms, 16 (33.3%) of the patients had terminal QRS root means square (RMS) voltage < 20 µV, and 27 (56.3%)of the patients had last amplitude (< 40 µV) signal duration of longer than 38 ms.

Table 1 summarizes the demographic, echocardiographic, electrocardiographic, and T2* features of the patient with and without late potentials in their SAECG.

Table 1 Comparison of patients with and without ventricular late potentials in their SAECG
Full size table

Various abnormalities were found in the electrocardiograms and echocardiograms of the patients. The association between abnormalities such as diastolic dysfunction, premature atrial contractions, and early repolarization, among others, with the existence of Late potentials in the SAECG, are summarized in Table 2. Such associations were assessed by Fisher’s exact test.

Table 2 The association of ECG and echocardiographic abnormalities with SAECG late potentials
Full size table

As can be deducted from Tables 1 and 2, major thalassemia patients with late potentials in their SAECG had higher rates of myocardial Iron overload, nonspecific ST-T changes, PACs, and PVCs. Consequently, SAECG late potentials can be used as a prognostic factor for myocardial Iron overload.

T2*MRI parameters

Cardiac and hepatic Iron overload was investigated using T2*MRI, and the Iron dry weight of both organs was estimated using this method. Patients were divided into three groups regarding their myocardial Iron load and three groups regarding their hepatic Iron load (normal, moderate, overload, and severe overload). Various electrocardiographic, SAECG, and echocardiographic findings were compared in these groups, which are summarized in Table 3.

Table 3 Demographic information, electrocardiographic, echocardiographic and SAECG data of both groups
Full size table

Pearson’s correlation test was used to assess the relationship between echocardiographic, electrocardiographic, T2*MRI, and SAECG findings. Myocardial and hepatic dry Iron weight had significantly positive correlations with QTc (r = 0.368, P = 0.010, and r = 0.317, P0.028, respect. Therefore, myocardial and hepatic T2*MRI conduction times had significant inverse relationships with QTc (r = −0.574, P < 0.001, and r = −0.358, P = 0.012, respectively). Ferritin level had a significant correlation with hepatic dry Iron weight (r = 0.421, P = 0.003) but not myocardial dry Iron weight (r = 0.257, P = 0.078). among SAECG findings, myocardial dry Iron weight had a significant direct correlation with LAS-40 (r = 0.304, P = 0.036). moreover, the duration of the filtered QRS wave and P–R interval showed a significant and direct correlation (r = 0.297, P = 0.040). the results of Pearson’s correlation tests are summarized in Table 4.

Table 4 Assessment of the correlations between SAECG, T2*MRI, electrocardiographic, and echocardiographic findings
Full size table

Discussion

In this study performed on 48 major thalassemia patients, we found that the mean hepatic and myocardial T2*MRI conduction times were 20.29 ± 12.44 and 6.45 ± 6.26 ms, respectively. Patients with ventricular late potentials in their SAECG tended to have lower myocardial T2*MRI conduction times and, thus, have higher myocardial Iron loads. Patients with ventricular late potentials in their SAECG also had higher rates of non-specific ST-T changes, Premature atrial contraction, and Premature ventricular contractions. Moreover, patients with higher myocardial and hepatic Iron load had longer QTc. The application of T2* MRI in defining tissue Iron load in thalassemia patients has long been proven [13, 14]. Therefore, in this study, we used this relatively novel method in defining the Iron load of the cardiac and hepatic tissues in beta-thalassemia major patients to see if iron overload is related to changes in electrocardiography, SAECG, and echocardiography of the patients.

Daar et al. have found that lower cardiac T2* in thalassemia major patients is associated with higher mortality; consequently, further evaluation of patients with lower cardiac T2* is of great importance [15]. Moreover, since T2* MRI is not readily available in most institutes, finding proper substitutes for this modality is also essential.

In our study, although ferritin level was associated with hepatic Iron load, it did not have any association with the cardiac Iron load. This finding was in line with the findings of a study performed by Khadivi Heris et al. on 58 thalassemia major patients [16]. They also found that cardiac Iron load was associated with higher Alanine Aminotransferase levels, which was not evaluated in our study. On the other hand, in a study by Wahidiyat et al., they found that ferritin level was associated with cardiac and hepatic T2*MRI conduction times [17].

In a study by Dursun et al., the authors found that lower cardiac T2* MRI conduction time was associated with a larger interventricular septum and higher left ventricular mass, which can be due to iron deposition in the cardiac tissue [18]. However, no association was found between T2* MRI conduction time and left ventricular ejection fraction. However, in our study, patients with higher myocardial iron load had lower left ventricular ejection fractions and were more in danger of congestive heart failure, which shows that iron overload in cardiac tissues induces systolic and diastolic dysfunction.

In a study by Aggarwal and colleagues performed on 48 thalassemia major patients, higher cardiac Iron overload was associated with longer QTc in the patients [19]. This finding was in line with the results of our study, indicating that a higher Iron load in beta-thalassemia major patients is accompanied by higher cardiovascular mortality.

In a study by Hayıroğlu et al., they used a formula devised from 12-lead ECG findings to predict the existence of diastolic dysfunction in patients. Such findings can also be extremely useful in the population of patients with major thalassemia since most of the patients with cardiac Iron overload have diastolic dysfunction, which might end in further complications such as heart failure with preserved ejection fraction and ultimately sudden cardiac death [20].

In this study, we also assessed the patients using signal-averaged electrocardiography since T2* MRI is not always available, but recording SAECG is a rather easy way of ventricular function assessment. In our study, patients with ventricular late potentials assessed by SAECG were found to have higher cardiac Iron load and, thus, lower cardiac T2* MRI conduction time. However, the parameters that were significantly different among patients with variable degrees of cardiac Iron load, such as, QTc, did not differ in patients with and without ventricular late potentials. This might indicate that ventricular late potentials have higher sensitivity and lower specificity for cardiac abnormalities such as QT prolongation; therefore, this method can be used as a screening tool for cardiac complications of beta thalassemia major.

In our study, myocardial and hepatic dry Iron weight had direct and significant correlations with QTc and T duration, which indicates the prolongation of the ventricular repolarization phase. Since QTc prolongation is associated with higher mortality, further studies to understand the underlying mechanism of this finding and its importance seem essential [21].

In a study conducted by Patsourakos et al., the existence of ventricular late potentials in SAECG was associated with longer QRS duration, longer QT interval, larger left ventricular end-diastolic diameter, larger left atrial volume index, and higher pulmonary artery systolic pressure, all indicating more severe cardiac complications of beta thalassemia major [11]. In our study, non-specific ST-T changes, premature atrial contractions, and premature ventricular contractions were seen more often in patients with ventricular late potentials, however, left atrial size and left ventricular end-diastolic volume did not have a significant association with ventricular late potentials. Since the patients in Patsourakos’ study were older than our subjects, these findings might indicate that patients with ventricular late potentials are at higher risk for mentioned complications, such as left atrial enlargement, ventricular hypertrophy, and diastolic dysfunction in the long term.

In a study by Franzoni et al., thalassemia major patients underwent Holter ECG monitoring, and patients with ventricular late potentials showed higher rates of ventricular tachycardia, which shows that this method can be used as a screening method for cardiac complications of beta thalassemia major. This is in line with the results of our study that patients with ventricular late potentials in their SAECG need further cardiac evaluations [22].

Isma’eel et al. also evaluated 26 patients with beta-thalassemia major for seven years and assessed them with SAECG. In this period, ferritin levels were correlated with QRS duration and RMS voltage. Therefore, they concluded that these two SAECG parameters could be used as an indicator of Iron overload and cardiac complications [12].

In our study, filtered QRS duration was significantly correlated with the P–R interval. Although atrioventricular blocks are rare in thalassemia major patients and only a few case reports exist in this matter [23], prolonged filtered QRS in the patients might act as a prognostic factor for the development of this complication. Animal studies have revealed the effect of Iron overload in slowing the conduction of impulses in cardiomyocytes which prompts further research into this matter [24].

Conclusion

In our study, we found that patients with ventricular late potentials assessed by SAECG had a higher myocardial Iron load, and a higher myocardial Iron load is associated with higher cardiac complications in patients with beta-thalassemia major. However, the changes in cardiac function occur in a long term. Consequently, SAECG can be used as a screening test for cardiac complications in beta-thalassemia major patients.

Availability of data and materials

All the data analysed during the current study are included in the published article. The dataset generated and analyzed during the current study are not publicly available due to the patient’s privacy, but are available upon reasonable request from the corresponding author.

Abbreviations

T2*MRI:

T2* magnetic resonance imaging

CMR:

Cardiovascular magnetic resonance

ECG:

Electrocardiography

SAECG:

Signal‐averaged electrocardiography

LPS:

Late potentials

ms:

Milliseconds

References

  1. Esmaeilzadeh F, Ahmadi B, Vahedi S, Barzegari S, Rajabi A. Major Thalassemia, screening or treatment: an economic evaluation study in Iran. Int J Health Policy Manag. 2022;11(7):1112–9.

    Google Scholar 

  2. Galanello R, Origa R. Beta-thalassemia. Orphanet J Rare Dis. 2010;5:11.

    Article  Google Scholar 

  3. Koohi F, Kazemi T, Miri-Moghaddam E. Cardiac complications and iron overload in beta thalassemia major patients-a systematic review and meta-analysis. Ann Hematol. 2019;98(6):1323–31.

    Article  CAS  Google Scholar 

  4. Marengo-Rowe AJ. The thalassemias and related disorders. Proc (Bayl Univ Med Cent). 2007;20(1):27–31.

    Google Scholar 

  5. Sakha K, Samadi M, Rezamand A. Cardiac involvement of major thalassemia and evaluation of total serum creatine kinase and creatine kinase-mB isoenzyme and cardiac troponinI in these patients. Pak J Biol Sci. 2008;11(7):1059–62.

    Article  CAS  Google Scholar 

  6. Borgna-Pignatti C, Cappellini MD, De Stefano P, Del Vecchio GC, Forni GL, Gamberini MR, et al. Survival and complications in thalassemia. Ann N Y Acad Sci. 2005;1054:40–7.

    Article  CAS  Google Scholar 

  7. Menacho K, Abdel-Gadir A, Moon JC, Fernandes JL. T2* Mapping techniques: iron overload assessment and other potential clinical applications. Magn Reson Imaging Clin N Am. 2019;27(3):439–51.

    Article  Google Scholar 

  8. Djer MM, Anggriawan SL, Gatot D, Amalia P, Sastroasmoro S, Widjaja P. Correlation between T2* cardiovascular magnetic resonance with left ventricular function and mass in adolescent and adult major thalassemia patients with iron overload. Acta Med Indones. 2013;45(4):295–301.

    Google Scholar 

  9. Eghbali A, Taherahmadi H, Shahbazi M, Bagheri B, Ebrahimi L. Association between serum ferritin level, cardiac and hepatic T2-star MRI in patients with major β-thalassemia. Iran J Ped Hematol Oncol. 2014;4(1):17–21.

    CAS  Google Scholar 

  10. Isma’eel H, Taher A, Shamseddeen W, Khoury M, Gharzuddine W, Arnaout MS, et al. SAECG parameters and left ventricular chamber sizes: Lesson from anemia conditions in thalassemia major patients. Int J Cardiol. 2006;113(3):E102–4.

    Article  Google Scholar 

  11. Patsourakos D, Gatzoulis KA, Aggeli C, Delicou S, Dimitroglou Y, Xydaki K, et al. Twelve-lead and signal-averaged electrocardiographic parameters among beta-thalassemia major patients. J Arrhythm. 2020;36(5):920–8.

    Article  Google Scholar 

  12. Isma’eel H, Shamseddeen W, Taher A, Gharzuddine W, Dimassi A, Alam S, et al. Ventricular late potentials among thalassemia patients. Int J Cardiol. 2009;132(3):453–5.

    Article  Google Scholar 

  13. Pennell DJ. T2* magnetic resonance and myocardial iron in thalassemia. Ann N Y Acad Sci. 2005;1054:373–8.

    Article  CAS  Google Scholar 

  14. Farhangi H, Badiei Z, Moghaddam HM, Keramati MR. Assessment of heart and liver iron overload in thalassemia major patients using T2* magnetic resonance imaging. Indian J Hematol Blood Transfus. 2017;33(2):228–34.

    Article  Google Scholar 

  15. Daar S, Al Khabori M, Al Rahbi S, Hassan M, El Tigani A, Pennell DJ. Cardiac T2* MR in patients with thalassemia major: a 10-year long-term follow-up. Ann Hematol. 2020;99(9):2009–17.

    Article  CAS  Google Scholar 

  16. KhadiviHeris H, Nejati B, Rezazadeh K, Sate H, Dolatkhah R, Ghoreishi Z, et al. Evaluation of iron overload by cardiac and liver T2* in β-thalassemia: correlation with serum ferritin, heart function and liver enzymes. J Cardiovasc Thorac Res. 2021;13(1):54–60.

    Article  Google Scholar 

  17. Wahidiyat PA, Liauw F, Sekarsari D, Putriasih SA, Berdoukas V, Pennell DJ. Evaluation of cardiac and hepatic iron overload in thalassemia major patients with T2* magnetic resonance imaging. Hematology. 2017;22(8):501–7.

    CAS  Google Scholar 

  18. ErsoyDursun F, Açıksarı G, Özkök S, İncealtın O. Evaluation of electrocardiography, echocardiography and cardiac T2* for cardiac complications in beta thalassemia major. Int J Cardiovasc Imaging. 2022;38(3):533–42.

    Article  Google Scholar 

  19. Aggarwal P, Kumar I, Jain A, Verma A, Gupta V. Relation between cardiac T2* values and electrocardiographic parameters in children with transfusion-dependent thalassemia. J Pediatr Hematol Oncol. 2020;42(7):e610–4.

    Article  CAS  Google Scholar 

  20. Hayıroğlu M, Çınar T, Çiçek V, Asal S, Kılıç Ş, Keser N, et al. A simple formula to predict echocardiographic diastolic dysfunction-electrocardiographic diastolic index. Herz. 2021;46(Suppl 2):159–65.

    Article  Google Scholar 

  21. Mantri N, Lu M, Zaroff JG, Risch N, Hoffmann T, Oni-Orisan A, et al. QT interval dynamics and cardiovascular outcomes: a cohort study in an integrated health care delivery system. J Am Heart Assoc. 2021;10(19): e018513.

    Article  Google Scholar 

  22. Franzoni F, Galetta F, Di Muro C, Buti G, Pentimone F, Santoro G. Heart rate variability and ventricular late potentials in beta-thalassemia major. Haematologica. 2004;89(2):233–4.

    Google Scholar 

  23. Nakou E, Simantirakis E, Chrysostomakis S, Vardas P. A case report of hemosiderosis-induced ventricular pacing exit block. Int J Cardiol. 2013;168:4912–4.

    Article  CAS  Google Scholar 

  24. Laurita KR, Chuck ET, Yang T, Dong W-Q, Kuryshev YA, Brittenham GM, et al. Optical mapping reveals conduction slowing and impulse block in iron-overload cardiomyopathy. J Lab Clin Med. 2003;142(2):83–9.

    Article  CAS  Google Scholar 

  25. Breithardt G, Cain ME, el-Sherif N, Flowers NC, Hombach V, Janse M, Simson MB, Steinbeck G. Standards for analysis of ventricular late potentials using high-resolution or signal-averaged electrocardiography. A statement by a Task Force Committee of the European Society of Cardiology, the American Heart Association, and the American College of Cardiology. Circulation. 1991;83(4):1481–8. https://doi.org/10.1161/01.cir.83.4.1481.

  26. Gatzoulis KA, Carlson MD, Biblo LA, Rizos I, Gialafos J, Toutouzas P, Waldo AL. Time domain analysis of the signal averaged electrocardiogram in patients with a conduction defect or a bundle branch block. Eur Heart J. 1995;16(12):1912–9. https://doi.org/10.1093/oxfordjournals.eurheartj.a060847.

Download references

Acknowledgements

We sincerely appreciate the participation of the patients and their families in the current research.

Funding

This research received no external funding.

Author information

Authors and Affiliations

  1. Department of Cardiology, Shiraz University of Medical Sciences, Shiraz, Iran

    Maryam Bahmani Jahromi, Mohammad Kasaei, Zahra Hooshanginezhad, Amir Aslani & Shahdad Khosropanah

  2. School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

    Amir Hossein Hassani & Mohammad Mortezaie

  3. Hematology Research Center, Shiraz University of Medical Sciences, Nemazee Hospital, Shiraz, Iran

    Omidreza Zekavat

Authors
  1. Maryam Bahmani Jahromi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amir Hossein Hassani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohammad Kasaei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zahra Hooshanginezhad
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Amir Aslani
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Omidreza Zekavat
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mohammad Mortezaie
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Shahdad Khosropanah
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MBJ: Conceptualization, methodology, software, validation, investigation, data curation, resources, writing—original draft, article review and editing; AHH: Conceptualization, investigation, data curation, resources, writing—original draft, review and editing; MK: Validation, data curation, review and editing; zh: validation, data curation, resources, writing—original draft, review and editing; AA: Conceptualization, investigation, data curation, resources; ORZ: Data curation, resources, article review and editing; MM: Investigation, data curation, resources, review; SK: Conceptualization, methodology, validation, investigation, data curation, resources, writing—original draft, review and editing, supervision. All authors have read and agreed to the published version of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Shahdad Khosropanah.

Ethics declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Shiraz University of Medical Sciences by the code IR.SUMS.MED.REC.1400.235. a written consent form was obtained from the patients or their legal guardians.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Bahmani Jahromi, M., Hassani, A.H., Kasaei, M. et al. Evaluation of the efficacy of signal-averaged electrocardiogram testing in the cardiac assessment of beta-thalassemia major patients. BMC Cardiovasc Disord 22, 534 (2022). https://doi.org/10.1186/s12872-022-02984-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12872-022-02984-0

Keywords

  • Thalassemia major
  • SAECG
  • T2*MRI

BMC Cardiovascular Disorders

ISSN: 1471-2261

Contact us