International Journal of Cardiology 187 (2015) 78–79
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Letter to the Editor
ECG score correlates with myocardial fibrosis assessed by magnetic resonance: A study in Chagas heart disease H. Rodríguez-Zanella a,⁎, G. Meléndez-Ramírez b, A. Meave b, E. Alexanderson c a b c
Department of Echocardiography, National Institute of Cardiology, “Ignacio Chávez” Mexico City, Mexico Department of Cardiovascular Magnetic Resonance, National Institute of Cardiology, “Ignacio Chávez” Mexico City, Mexico Department of Nuclear Cardiology, National Institute of Cardiology, “Ignacio Chávez” Mexico City, Mexico
a r t i c l e
i n f o
Article history: Received 19 March 2015 Accepted 21 March 2015 Available online 23 March 2015 Keywords: Chagas disease Sudden cardiac death QRS score
Chagas disease has an estimated prevalence of 8 million in Latin America [1] where it represents the most common cause of nonischemic cardiomyopathy, with an estimated world prevalence of 16– 18 million. Related mortality is explained by heart failure and sudden cardiac death (SCD). There are a number of prognostic factors that have shown a poor performance without substantial value in the clinical scenario [2]. Interestingly, patients with a better NYHA functional class are more prone to suffer SCD in contrast to patients with non-Chagas' cardiomyopathy. This was demonstrated in a subanalysis of the RHEMADE Trial [3], in which left ventricular ejection fraction (LVEF) was not a risk factor for SCD. Several trials have reported a reduced mortality in patients who received Implantable Cardioverter Defibrillator (ICD) devices [4] and current guidelines recommend ICD implantation in patients with EF ≤35%, NYHA class II or III symptoms while receiving optimal medical therapy. However a post hoc analysis of MADIT II trial reported that only 35% of patients with an ICD received appropriate therapy at 3 years [5] and patients with aborted SCD have a LVEF above guideline thresholds, suggesting the possibility that patients at risk, with higher LVEF, will not benefit from this therapeutic strategy. Myocardial fibrosis, assessed through cardiac magnetic resonance (CMR), represents an independent predictor for mortality, ICD appropriate device therapy and ventricular tachycardia (VT) inducibility. Late gadolinium enhancement (LGE) has been studied in Chagas heart disease with promising results, although limited by its cost and avail⁎ Corresponding author. E-mail address: [email protected] (H. Rodríguez-Zanella).
http://dx.doi.org/10.1016/j.ijcard.2015.03.337 0167-5273/© 2015 Elsevier Ireland Ltd. All rights reserved.
ability. QRS score has been shown to correlate with CMR LGE and may be useful for risk stratification. There is still scarce information regarding the relationship between the QRS score and myocardial fibrosis detected by CMR in patients with Chagas heart disease [6]. We retrospectively included 52 patients with Chagas disease referred for a CMR study in our institution between 2012 and 2014, with a good quality ECG with a time between difference of less than 12 months. Patients with coronary artery disease (CAD) were excluded. 42 patients were analyzed. Our institution's ethics committee approved the protocol. ECG analysis was performed blinded to CMR data. The technical details of QRS score may be consulted elsewhere [7]. In brief, age and gender were used for adjustment, conduction defect types (if any) were determined and points assigned accordingly. Each point accounts for 3% fibrosis, yielding a maximum of 36 points or 96% fibrosis. CMR was performed using a 1.5 Tesla Siemens scanner. Steady state free precession sequence was used to evaluate ventricular function. LGE was analyzed to evaluate myocardial fibrosis, using 0.1 mmol/kg of dimeglumine gadopentate (Magnevist, Schering, Germany), Echo spin inversion recovery sequences were performed 10–15 min after contrast injection. All measures were done using Argus software, and fibrosis was measured in grams and as percentage of LV mass using CMR 42 (Circle, Canada). Kolmogorov–Smirnov test was performed to evaluate normal distribution of the variables. Pearson correlation coefficient was used to analyze the relation between QRS score and CMR-LGE size. Receiver operating characteristic (ROC) curves were built to define optimal cut off points to identify: presence of CMR-LGE, CMR-LGE ≥6%, CMR-LGE ≥20%, LVEF ≤50%, ventricular tachycardia (VT), NYHA class N1. A two tailed p-value b0.05 was considered statistically significant. All statics were done using IBM SPSS, statics 22.0. Baseline characteristics are summarized in Table 1. Only 9 patients were asymptomatic, and only one patient had 3 CAD risk factors, but had normal coronary arteries. Mean QRS score was 6 ± 3. Mean CMR fibrosis was 36 ± 19. We found a significant correlation between QRS Score and CRM fibrosis r = 0.73 (p b 0.001). Using a Bland–Altman plot we determined that the QRS score systematically underestimated fibrosis by 16%. Table 2 shows the area under the ROC curve to predict stated outcomes. A QRS score b3 was the optimal cut-off point to predict absence
H. Rodríguez-Zanella et al. / International Journal of Cardiology 187 (2015) 78–79 Table 1 Baseline characteristics. Variable
Value
Age (years) Male sex Stage Indeterminate Subclinical Chagas heart disease Ventricular tachycardia Heart failure Angina Sudden death NYHA functional class Class I Class II Class III Class IV Coronary anatomy Normal Ectasia Coronary risk factors in patients with unknown coronary anatomy Diabetes mellitus Hypertension Dyslipidemia Smokers Number of risk factors 0 1 2 3 QRS score RBBB RBB LAFB LVH LBBB LVEF LVEDV RVEF CMR-LGE Fibrosis (%)
56 ± 12 6 (62%) 5 (12%) 4 (10%) 33 (78%) 15 (45%) 15 (45%) 3 (9%) 12% (5) 12 (28%) 23 (55%) 3 (7%) 4 (10%) 27 26 1 2 (13%) 5 (33%) 6 (40%) 2 (13%) 4 (27%) 8 (53%) 2 (13%) 1 (7%) 6±3 16% 21% 12% 7% 37 ± 18% 180 ± 87 37 ± 14% 37 (88%) 36 ± 19
of fibrosis. QRS score ≥3 predicted N 6% of myocardial fibrosis. The optimal cut-off point to predict VT was a QRS score ≥7. This study demonstrates that QRS score correlates with CMR fibrosis, and can be used to predict the absence of fibrosis, and identify a history of ventricular tachycardia and reduced LVEF. Even though a greater degree of fibrosis is seen with progression of Chagas heart disease, there is no defined cut-off point for prediction of mortality, SCD or VT. Neilan et al. [9] studied 162 patients with nonischemic cardiomyopathy. Major adverse cardiovascular events (MACE) occurred in 47 patients with LGE (24%/year) and 4 without it (2%/year). They also found that LGE has a negative predictive value of 95% for MACE. They identified 6.1% of LGE CMR fibrosis as the optimal value to predict the development of MACE. Iles et al. [10] studied a group of ischemic and non-ischemic patients. Interestingly; none of the patients without LGE experienced ICD discharges. Chagas heart disease has a worse prognosis than other causes of heart failure and current treatment, including ICD, is not supported by clinical trials.
79
Previous studies have reported that QRS score may overestimate CMR fibrosis [8]. However, in patients with greater degree of fibrosis it underestimated CMR-measured fibrosis, a finding that is supported by our study. A previous study evaluated QRS score for prediction of similar outcomes. The authors found that a QRS score ≥2 predicted the presence of LGE, N10% of LGE and a LVEF b 50%. They included patients with lower LGE 11 ± 12 and higher LVEF 52 ± 17. Most patients had no ECG confounders (57%) and no patients with left bundle branch block. More data is needed to establish a definite cut off for prediction of LGE. QRS score significantly correlates with myocardial fibrosis evaluated with CMR-LGE, and is useful to predict the absence of LGE, decreased LVEF, and a history of VT. Further prospective studies are warranted to assess the role of the QRS score for prediction of MACE, and risk stratification for primary prevention with ICD.
Conflict of interest The authors report no relationships that could be construed as a conflict of interest.
References [1] Pan-American Health Organization, Quantitative Estimation of Chagas Disease in America, PHO, Monte- video, Uruguay, 2006. (Report no. OPS/HDM/CD/425–06). [2] A. Rassi Jr., A. Rassi, W. Little, S. Xavier, S. Rassi, A. Rassi, G. Rassi, A. HasslocherMoreno, A. Sousa, I. Scanavacca, Development and validation of a risk score for predicting death in Chagas' heart disease, N Engl. J. Med. 355 (2006) 799–808. [3] S. Ayub-Ferreira, S. Mangini, V. Issa, F. Cruz, F. Bacal, G. Guimaraes, G. ConceicaoSouza, F. Marcondes-Braga, E. Bochi, Mode of death of Chagas heart disease. Comparison with other etiologies. A subanalysis of the REMADHE trial, PLoS Negl. Trop. Dis. 7 (4) (Apr 25 2013) e2176. [4] G.H. Bardy, K.L. Lee, D.B. Mark, J.E. Poole, D.L. Packer, R. Boineau, M. Domanski, C. Troutman, J. Anderson, G. Johnson, S.E. McNulty, N. Clapp- Channing, L.D. Davidson-Ray, E.S. Fraulo, D.P. Fishbein, R.M. Luceri, J.H. Ip, Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure, N. Engl. J. Med. 352 (2005) 225–237. [5] A.J. Moss, H. Greenberg, R.B. Case, W. Zareba, W.J. Hall, M.W. Brown, J.P. Daubert, S. McNitt, M.L. Andrews, A.D. Elkin, Long-term clinical course of patients after termination of ventricular tachyarrhythmia by an implanted defibrillator, Circulation 110 (2004) 3760–3765. [6] C.E. Rochitte, P.F. Oliveira, J.M. Andrade, B.M. Ianni, J.R. Parga, L.F. Avila, R. Kalil-Filho, C. Mady, J.C. Mehenghetti, J.A. Lima, J.A. Ramires, Myocardial delayed enhancement by magnetic resonance imaging in patients with Chagas' disease: a marker of disease severity, J. Am. Coll. Cardiol. 46 (2005) 1553e8. [7] Z. Loring, S. Chelliah, R.H. Selvester, G. Wagner, D.G. Strauss, A detailed guide for quantification of myocardial scar with the Selvester QRS score in the presence of electrocardiogram confounders, J. Electrocardiol. 44 (5) (2011) 544–554. [8] D.G. Strauss, S. Cardoso, J.A. Lima, C.E. Rochitte, K.C. Wu, ECG scar quantification correlates with cardiac magnetic resonance scar size and prognostic factors in Chagas' disease, Heart 97 (2011) 357–361. [9] T.G. Neilan, O.R. Coelho-Filho, S.B. Danik, R.V. Shah, J.A. Dodson, D.J. Verdini, M. Tokuda, C.A. Daly, U.B. Tedrow, W.G. Stevenson, M. Jerosch-Herold, B.B. Ghoshhajra, R.Y. Kwong, CMR quantification of myocardial scar provides additive prognostic information in nonischemic cardiomyopathy, JACC Cardiovasc. Imaging 6 (9) (Sep 2013) 944–954. [10] L. Iles, H. Pfluger, L. Lefkovits, M.J. Butler, P.M. Kistler, D.M. Kaye, A.J. Taylor, Myocardial fibrosis predicts appropriate device therapy in patients with implantable cardioverter-defibrillators for primary prevention of sudden cardiac death, J. Am. Coll. Cardiol. 57 (7) (Feb 15 2011) 821–828.
Table 2 ROC AUC for outcome prediction. Outcome
EF b50%
NYHA N1
VT
No fibrosis
Fibrosis N6%
Fibrosis N20%
AUC QRS score Sensitivity Specificity
0.84 (IC 0.70–0.98) ≥4 90.3% 72%
0.9 (IC 0.62–0.98) ≥5 80% 75%
0.72 (IC 0.56–0.87). ≥7 80% 63%
0.94 (IC 0.86–1). b3 91% 80%
0.95 (0.89–1) ≥3 89% 100%
0.88 (IC 0.75–1) ≥5 83% 83%
QRS score cut points, useful to predict the presence of high risk features, obtained from ROC curve construction.
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Letter to the Editor
ECG score correlates with myocardial fibrosis assessed by magnetic resonance: A study in Chagas heart disease H. Rodríguez-Zanella a,⁎, G. Meléndez-Ramírez b, A. Meave b, E. Alexanderson c a b c
Department of Echocardiography, National Institute of Cardiology, “Ignacio Chávez” Mexico City, Mexico Department of Cardiovascular Magnetic Resonance, National Institute of Cardiology, “Ignacio Chávez” Mexico City, Mexico Department of Nuclear Cardiology, National Institute of Cardiology, “Ignacio Chávez” Mexico City, Mexico
a r t i c l e
i n f o
Article history: Received 19 March 2015 Accepted 21 March 2015 Available online 23 March 2015 Keywords: Chagas disease Sudden cardiac death QRS score
Chagas disease has an estimated prevalence of 8 million in Latin America [1] where it represents the most common cause of nonischemic cardiomyopathy, with an estimated world prevalence of 16– 18 million. Related mortality is explained by heart failure and sudden cardiac death (SCD). There are a number of prognostic factors that have shown a poor performance without substantial value in the clinical scenario [2]. Interestingly, patients with a better NYHA functional class are more prone to suffer SCD in contrast to patients with non-Chagas' cardiomyopathy. This was demonstrated in a subanalysis of the RHEMADE Trial [3], in which left ventricular ejection fraction (LVEF) was not a risk factor for SCD. Several trials have reported a reduced mortality in patients who received Implantable Cardioverter Defibrillator (ICD) devices [4] and current guidelines recommend ICD implantation in patients with EF ≤35%, NYHA class II or III symptoms while receiving optimal medical therapy. However a post hoc analysis of MADIT II trial reported that only 35% of patients with an ICD received appropriate therapy at 3 years [5] and patients with aborted SCD have a LVEF above guideline thresholds, suggesting the possibility that patients at risk, with higher LVEF, will not benefit from this therapeutic strategy. Myocardial fibrosis, assessed through cardiac magnetic resonance (CMR), represents an independent predictor for mortality, ICD appropriate device therapy and ventricular tachycardia (VT) inducibility. Late gadolinium enhancement (LGE) has been studied in Chagas heart disease with promising results, although limited by its cost and avail⁎ Corresponding author. E-mail address: [email protected] (H. Rodríguez-Zanella).
http://dx.doi.org/10.1016/j.ijcard.2015.03.337 0167-5273/© 2015 Elsevier Ireland Ltd. All rights reserved.
ability. QRS score has been shown to correlate with CMR LGE and may be useful for risk stratification. There is still scarce information regarding the relationship between the QRS score and myocardial fibrosis detected by CMR in patients with Chagas heart disease [6]. We retrospectively included 52 patients with Chagas disease referred for a CMR study in our institution between 2012 and 2014, with a good quality ECG with a time between difference of less than 12 months. Patients with coronary artery disease (CAD) were excluded. 42 patients were analyzed. Our institution's ethics committee approved the protocol. ECG analysis was performed blinded to CMR data. The technical details of QRS score may be consulted elsewhere [7]. In brief, age and gender were used for adjustment, conduction defect types (if any) were determined and points assigned accordingly. Each point accounts for 3% fibrosis, yielding a maximum of 36 points or 96% fibrosis. CMR was performed using a 1.5 Tesla Siemens scanner. Steady state free precession sequence was used to evaluate ventricular function. LGE was analyzed to evaluate myocardial fibrosis, using 0.1 mmol/kg of dimeglumine gadopentate (Magnevist, Schering, Germany), Echo spin inversion recovery sequences were performed 10–15 min after contrast injection. All measures were done using Argus software, and fibrosis was measured in grams and as percentage of LV mass using CMR 42 (Circle, Canada). Kolmogorov–Smirnov test was performed to evaluate normal distribution of the variables. Pearson correlation coefficient was used to analyze the relation between QRS score and CMR-LGE size. Receiver operating characteristic (ROC) curves were built to define optimal cut off points to identify: presence of CMR-LGE, CMR-LGE ≥6%, CMR-LGE ≥20%, LVEF ≤50%, ventricular tachycardia (VT), NYHA class N1. A two tailed p-value b0.05 was considered statistically significant. All statics were done using IBM SPSS, statics 22.0. Baseline characteristics are summarized in Table 1. Only 9 patients were asymptomatic, and only one patient had 3 CAD risk factors, but had normal coronary arteries. Mean QRS score was 6 ± 3. Mean CMR fibrosis was 36 ± 19. We found a significant correlation between QRS Score and CRM fibrosis r = 0.73 (p b 0.001). Using a Bland–Altman plot we determined that the QRS score systematically underestimated fibrosis by 16%. Table 2 shows the area under the ROC curve to predict stated outcomes. A QRS score b3 was the optimal cut-off point to predict absence
H. Rodríguez-Zanella et al. / International Journal of Cardiology 187 (2015) 78–79 Table 1 Baseline characteristics. Variable
Value
Age (years) Male sex Stage Indeterminate Subclinical Chagas heart disease Ventricular tachycardia Heart failure Angina Sudden death NYHA functional class Class I Class II Class III Class IV Coronary anatomy Normal Ectasia Coronary risk factors in patients with unknown coronary anatomy Diabetes mellitus Hypertension Dyslipidemia Smokers Number of risk factors 0 1 2 3 QRS score RBBB RBB LAFB LVH LBBB LVEF LVEDV RVEF CMR-LGE Fibrosis (%)
56 ± 12 6 (62%) 5 (12%) 4 (10%) 33 (78%) 15 (45%) 15 (45%) 3 (9%) 12% (5) 12 (28%) 23 (55%) 3 (7%) 4 (10%) 27 26 1 2 (13%) 5 (33%) 6 (40%) 2 (13%) 4 (27%) 8 (53%) 2 (13%) 1 (7%) 6±3 16% 21% 12% 7% 37 ± 18% 180 ± 87 37 ± 14% 37 (88%) 36 ± 19
of fibrosis. QRS score ≥3 predicted N 6% of myocardial fibrosis. The optimal cut-off point to predict VT was a QRS score ≥7. This study demonstrates that QRS score correlates with CMR fibrosis, and can be used to predict the absence of fibrosis, and identify a history of ventricular tachycardia and reduced LVEF. Even though a greater degree of fibrosis is seen with progression of Chagas heart disease, there is no defined cut-off point for prediction of mortality, SCD or VT. Neilan et al. [9] studied 162 patients with nonischemic cardiomyopathy. Major adverse cardiovascular events (MACE) occurred in 47 patients with LGE (24%/year) and 4 without it (2%/year). They also found that LGE has a negative predictive value of 95% for MACE. They identified 6.1% of LGE CMR fibrosis as the optimal value to predict the development of MACE. Iles et al. [10] studied a group of ischemic and non-ischemic patients. Interestingly; none of the patients without LGE experienced ICD discharges. Chagas heart disease has a worse prognosis than other causes of heart failure and current treatment, including ICD, is not supported by clinical trials.
79
Previous studies have reported that QRS score may overestimate CMR fibrosis [8]. However, in patients with greater degree of fibrosis it underestimated CMR-measured fibrosis, a finding that is supported by our study. A previous study evaluated QRS score for prediction of similar outcomes. The authors found that a QRS score ≥2 predicted the presence of LGE, N10% of LGE and a LVEF b 50%. They included patients with lower LGE 11 ± 12 and higher LVEF 52 ± 17. Most patients had no ECG confounders (57%) and no patients with left bundle branch block. More data is needed to establish a definite cut off for prediction of LGE. QRS score significantly correlates with myocardial fibrosis evaluated with CMR-LGE, and is useful to predict the absence of LGE, decreased LVEF, and a history of VT. Further prospective studies are warranted to assess the role of the QRS score for prediction of MACE, and risk stratification for primary prevention with ICD.
Conflict of interest The authors report no relationships that could be construed as a conflict of interest.
References [1] Pan-American Health Organization, Quantitative Estimation of Chagas Disease in America, PHO, Monte- video, Uruguay, 2006. (Report no. OPS/HDM/CD/425–06). [2] A. Rassi Jr., A. Rassi, W. Little, S. Xavier, S. Rassi, A. Rassi, G. Rassi, A. HasslocherMoreno, A. Sousa, I. Scanavacca, Development and validation of a risk score for predicting death in Chagas' heart disease, N Engl. J. Med. 355 (2006) 799–808. [3] S. Ayub-Ferreira, S. Mangini, V. Issa, F. Cruz, F. Bacal, G. Guimaraes, G. ConceicaoSouza, F. Marcondes-Braga, E. Bochi, Mode of death of Chagas heart disease. Comparison with other etiologies. A subanalysis of the REMADHE trial, PLoS Negl. Trop. Dis. 7 (4) (Apr 25 2013) e2176. [4] G.H. Bardy, K.L. Lee, D.B. Mark, J.E. Poole, D.L. Packer, R. Boineau, M. Domanski, C. Troutman, J. Anderson, G. Johnson, S.E. McNulty, N. Clapp- Channing, L.D. Davidson-Ray, E.S. Fraulo, D.P. Fishbein, R.M. Luceri, J.H. Ip, Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure, N. Engl. J. Med. 352 (2005) 225–237. [5] A.J. Moss, H. Greenberg, R.B. Case, W. Zareba, W.J. Hall, M.W. Brown, J.P. Daubert, S. McNitt, M.L. Andrews, A.D. Elkin, Long-term clinical course of patients after termination of ventricular tachyarrhythmia by an implanted defibrillator, Circulation 110 (2004) 3760–3765. [6] C.E. Rochitte, P.F. Oliveira, J.M. Andrade, B.M. Ianni, J.R. Parga, L.F. Avila, R. Kalil-Filho, C. Mady, J.C. Mehenghetti, J.A. Lima, J.A. Ramires, Myocardial delayed enhancement by magnetic resonance imaging in patients with Chagas' disease: a marker of disease severity, J. Am. Coll. Cardiol. 46 (2005) 1553e8. [7] Z. Loring, S. Chelliah, R.H. Selvester, G. Wagner, D.G. Strauss, A detailed guide for quantification of myocardial scar with the Selvester QRS score in the presence of electrocardiogram confounders, J. Electrocardiol. 44 (5) (2011) 544–554. [8] D.G. Strauss, S. Cardoso, J.A. Lima, C.E. Rochitte, K.C. Wu, ECG scar quantification correlates with cardiac magnetic resonance scar size and prognostic factors in Chagas' disease, Heart 97 (2011) 357–361. [9] T.G. Neilan, O.R. Coelho-Filho, S.B. Danik, R.V. Shah, J.A. Dodson, D.J. Verdini, M. Tokuda, C.A. Daly, U.B. Tedrow, W.G. Stevenson, M. Jerosch-Herold, B.B. Ghoshhajra, R.Y. Kwong, CMR quantification of myocardial scar provides additive prognostic information in nonischemic cardiomyopathy, JACC Cardiovasc. Imaging 6 (9) (Sep 2013) 944–954. [10] L. Iles, H. Pfluger, L. Lefkovits, M.J. Butler, P.M. Kistler, D.M. Kaye, A.J. Taylor, Myocardial fibrosis predicts appropriate device therapy in patients with implantable cardioverter-defibrillators for primary prevention of sudden cardiac death, J. Am. Coll. Cardiol. 57 (7) (Feb 15 2011) 821–828.
Table 2 ROC AUC for outcome prediction. Outcome
EF b50%
NYHA N1
VT
No fibrosis
Fibrosis N6%
Fibrosis N20%
AUC QRS score Sensitivity Specificity
0.84 (IC 0.70–0.98) ≥4 90.3% 72%
0.9 (IC 0.62–0.98) ≥5 80% 75%
0.72 (IC 0.56–0.87). ≥7 80% 63%
0.94 (IC 0.86–1). b3 91% 80%
0.95 (0.89–1) ≥3 89% 100%
0.88 (IC 0.75–1) ≥5 83% 83%
QRS score cut points, useful to predict the presence of high risk features, obtained from ROC curve construction.
