67 ECG changes in Fabry disease ECG and CMR characteristics in FD patients To assess the relation between ECG parameters and cardiac imaging parameters, CMR data (left ventricular mass indexed to body surface area (LVMi) and the presence of late gadolinium enhancement (LGE)) were extracted from the patients records for the date closest to the last included ECG (maximum 1 year earlier or later). Cardiovascular events in FD patients Cardiac events from birth to last outpatient clinic visit were recorded in FD patients (the majority of the patients included in the current study were also included in our recently published study on cardiovascular events in FD [14]). Recorded cardiac events were major cardiovascular events (MACE) (combined endpoint including cardiovascular death, heart failure hospitalization, sustained ventricular arrhythmias and myocardial infarction) (for definitions of these events see: supplemental table 3). Statistical analysis R Studio (version 4.0.3) was used for Statistical analysis. Data are presented as proportions or median and minimum/maximum ranges. Differences in the prevalence of cardiovascular risk factors between FD patients and the control group were tested by the 2x2 Fisher exact test. Generalized linear mixed- effect models (GLM) were used to evaluate the effect of age at the time of obtaining an ECG, type of study subject (FD patient or control subject) and sex on seven ECG parameters: P-wave duration, PR- interval, QRS-duration, QTc, Cornell Index (voltage sum of R in aVL and S in V3), spatial QRS-T angle, and frontal QRS-axis. A random intercept and slope were introduced into all mixed models, taking inter-patient differences into account. Model assumptions were checked and met [28]. Because of the assumption that the effect of age on ECG parameters would be different between men and women but also between FD patients and controls, we tested for three-way interactions (age * type of the study subject (FD patient or control subject) * sex) in all models. Subgroups were defined as: men with classical FD, women with classical FD, controls- men and controls- women. From the resulting model, regression lines per subgroup were obtained following the standard regression equation for a linear model: y= a + β*X, with the intercept (a) and slope (β) specified for each subgroup. Similarly, the differences between two given subgroups were calculated. The slopes of these regression equations (β per 10 years increase in age) were compared to study the difference in evolution of a given ECG parameter over time between subgroups. In a GLM subanalysis, the untreated FD patients were excluded to investigate if there was a difference in ECG parameters’ increment between the ERT treated patients only and the complete study cohort, that also contains a minority of untreated FD patients. The frontal T-axis showed too much nonlinear variation for a valid GLM approach. 3
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