ECG-based score estimates the probability to detect Fabry Disease cardiac involvement

Stefano Figliozzi, Antonia Camporeale, Sara Boveri, Federico Pieruzzi, Maurizio Pieroni, Paola Lusardi, Marco Spada, Renzo Mignani, Alessandro Burlina, Francesca Graziani, Silvia Pica, Lara Tondi, Andrea Bernardini, Kelvin Chow, Mehdi Namdar, Massimo Lombardi

Research output: Contribution to journalArticlepeer-review


OBJECTIVES: To elaborate an ECG-based nomogram estimating the probability to detect cardiac involvement by cardiac magnetic resonance (CMR) in Fabry Disease (FD).

METHODS: 119 FD patients and 26 healthy controls underwent ECG and CMR. Test (n = 88, 60%) and validation cohorts (n = 57, 40%) were randomly derived. Cardiac involvement was defined as the presence of low myocardial T1 value, a CMR-surrogate of myocardial glycosphingolipid storage. ECG changes associated with low T1 value were identified in the test cohort, included in the nomogram and then tested in the validation cohort.

RESULTS: Sokolow-Lyon index (AUC = 0.769), ratio between P-wave and PR-segment durations (Pwave/PRsegment) (AUC = 0.778), QRS duration (AUC = 0.703), QT (AUC = 0.769) duration were independently associated with the presence of low T1 on CMR at multivariate analysis. An ECG-based nomogram including these four parameters was accurate in identifying patients with CMR evidence of glycosphingolipid storage (c-index of the derived-nomogram = 0.90 in the test group; 0.81 in the validation group).

CONCLUSION: We propose a practical ECG-based nomogram accurately estimating the probability to detect low T1 values by CMR in FD patients. The application of this tool in clinical practice could improve early detection of FD cardiac involvement.

Original languageEnglish
Pages (from-to)110-117
Number of pages8
JournalInt. J. Cardiol.
Publication statusPublished - Sept 15 2021


  • Cross-Sectional Studies
  • Early Diagnosis
  • Electrocardiography
  • Fabry Disease/diagnostic imaging
  • Humans
  • Magnetic Resonance Imaging, Cine
  • Myocardium
  • Predictive Value of Tests
  • Probability


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