Regression of Left Ventricular Hypertrophy and Diastolic Dysfunction in Patients on Nocturnal Home Hemodialysis as Assessed by Echocardiography and Cardiac Magnetic Resonance Imaging

2013 ◽  
Vol 29 (10) ◽  
pp. S272-S273
Author(s):  
T. Friesen ◽  
M. Zhu ◽  
F. Eng ◽  
E. Karlstedt ◽  
S. Premecz ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Left Ventricular Hypertrophy ◽  
Diastolic Dysfunction ◽  
Cardiac Magnetic Resonance Imaging ◽  
Ventricular Hypertrophy ◽  
Left Ventricular ◽  
Resonance Imaging ◽  
Home Hemodialysis

Abstract MP31: Left Ventricular Hypertrophy by Electrocardiogram versus Cardiac Magnetic Resonance Imaging as a Predictor for Heart Failure: The MESA Study

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Abdullahi O Oseni ◽  
Waqas T Qureshi ◽  
Mohammed F Almahmoud ◽  
Alain Bertoni ◽  
David A Bluemke ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Heart Failure ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Left Ventricular Hypertrophy ◽  
Cardiac Magnetic Resonance Imaging ◽  
Ventricular Hypertrophy ◽  
Predictive Ability ◽  
Left Ventricular ◽  
Resonance Imaging

Background: Left ventricular hypertrophy (LVH) is an established risk factor for heart failure (HF). However, it is unknown whether LVH detected by electrocardiogram (ECG-LVH) is equivalent to LVH ascertained by cardiac magnetic resonance imaging (MRI-LVH) in terms of prediction of incident HF using risk prediction models like the Framingham Heart Failure Risk Score (FHFRS). Methods: This analysis included 4745 (mean age 61+10 years, 53.5% women, 61.7% non-whites) from the Multi-Ethnic Study of Atherosclerosis who were free of cardiovascular disease at the time of enrollment. ECG-LVH was defined using Cornell’s criteria while MRI-LVH was derived from left ventricular (LV) mass measured by cardiac MRI. Cox proportional hazard regression was used to examine the association between ECG-LVH and MRI-LVH with incident HF. Harrell’s concordance C-index was used to estimate the predictive ability of the FHFRS when either ECG-LVH or MRI-LVH were included as one of its components. The added predictive ability of ECG-LVH and MRI-LVH were investigated using integrated discrimination improvement (IDI) index and relative IDI. Results: ECG-LVH was present in 291(6.1%) while MRI-LVH was present in 499 (10.5%) of the participants. Over a median follow up of 10.4 years, 140 participants developed HF. Both ECG-LVH [HR (95% CI): 2.25(1.38-3.69)] and MRI-LVH [HR (95% CI): 3.80(1.56-5.63)] were associated with an increased risk of HF in multivariable adjusted models (Table 1). The ability of FHFRS to predict HF was improved with MRI-LVH (C-index 0.871, 95% CI: 0.842-0.899) when compared with ECG-LVH (C-index 0.860, 95% CI: 0.833-0.888) (p < 0.0001). To assess the potential clinical utility of using LVH-MRI instead of ECG-LVH, we calculated several measures of reclassification (Table 1), which were consistent with the statistically significantly improved C-statistic with MRI-LVH. Conclusion: Both ECG-LVH and MRI-LVH are predictive of HF when used in the FHFRS. Substituting MRI-LVH for ECG-LVH improves the predictive ability of the FHFRS.

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