Why the study?
The study evaluated the prognostic value of multiparametric cardiovascular magnetic resonance (CMR) for predicting death from heart failure in patients with thalassemia major.
Does multiparametric CMR predict death from heart failure in patients with thalassemia major?
Does multiparametric CMR predict death from heart failure in patients with thalassemia major?
The presence of four specific CMR markers (myocardial iron overload, ventricular dysfunction, ventricular dilation, and replacement myocardial fibrosis) strongly predicts heart failure death in patients with thalassemia major.
May refine HF death risk stratification in TM; hypothesis-generating and needs prospective validation before practice change.
We assessed the prognostic value of multiparametric cardiovascular magnetic resonance (CMR) in predicting death from heart failure (HF) in thalassemia major (TM). We considered 1398 white TM patients (30.8 ± 8.9 years, 725 women) without a history of HF at baseline CMR, which was performed within the Myocardial Iron Overload in Thalassemia (MIOT) network. Iron overload was quantified by using the T2* technique, and biventricular function was determined with cine images. Late gadolinium enhancement (LGE) images were acquired to detect replacement myocardial fibrosis. During a mean follow-up of 4.83 ± 2.05 years, 49.1% of the patients changed the chelation regimen at least once; these patients were more likely to have significant myocardial iron overload (MIO) than patients who maintained the same regimen. Twelve (1.0%) patients died from HF. Significant MIO, ventricular dysfunction, ventricular dilation, and replacement myocardial fibrosis were identified as significant univariate prognosticators. Based on the presence of the four CMR predictors of HF death, patients were divided into three subgroups. Patients having all four markers had a significantly higher risk of dying for HF than patients without markers (hazard ratio (HR) = 89.93; 95%CI = 5.62–1439.46; p = 0.001) or with one to three CMR markers (HR = 12.69; 95%CI = 1.60–100.36; p = 0.016). Our findings promote the exploitation of the multiparametric potential of CMR, including LGE, for better risk stratification for TM patients.
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Meloni et al. (2023) studied this question.
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