COVID-19 infection often produces cardiovascular complications, which can range from mild to severe and influence the overall prognosis. Imaging is the cornerstone for diagnosing initial COVID-19 cardiovascular involvement as well as treatment guidance. In this review, we present the current state of the literature on this subject while also emphasizing possible algorithms for indicating and executing these investigations.

BACKGROUND: Stress perfusion cardiovascular magnetic resonance (CMR) is widely used to detect myocardial ischemia, mostly through visual assessment. Recent studies suggest that strain imaging at rest and during stress can also help in prognostic stratification. However, the additional prognostic value of combining both rest and stress strain imaging has not been fully established. This study examined the incremental benefit of combining these strain measures with traditional risk prognosticators and CMR findings to predict major adverse clinical events (MACE) in a cohort of consecutive patients referred for stress CMR. METHODS: This retrospective, single-center observational study included all consecutive patients with known or suspected coronary artery disease referred for stress CMR between 2016 and 2018. Fully automated machine learning was used to obtain global longitudinal strain at rest (rest-GLS) and global circumferential strain at stress (stress-GCS). The primary outcome was MACE, including cardiovascular death or hospitalization for heart failure. Cox models were used to assess the incremental prognostic value of combining these strain features with traditional prognosticators. RESULTS: Of 2778 patients (age 65±12 years, 68% men), 96% had feasible, fully automated rest-GLS and stress-GCS measurements. After a median follow-up of 5.2 (4.8–5.5) years, 316 (11.1%) patients experienced MACE. After adjustment for traditional prognosticators, both rest-GLS (hazard ratio, 1.09 [95% CI, 1.05–1.13]; P <0.001) and stress-GCS (hazard ratio, 1.08 [95% CI, 1.03–1.12]; P –10% for rest-GLS and stress-GCS, with a C-index improvement of 0.02, continuous net reclassification improvement of 15.6%, and integrative discrimination index of 2.2% (all P –10% provided an incremental prognostic value over and above traditional prognosticators, including CMR parameters, for predicting MACE in patients undergoing stress CMR.

Fabry disease (FD) is a rare genetic lysosomal disease with an estimated prevalence of 1:100000. Mutations on the GLA gene lead to alpha-galactosidase deficiency and multiorgan involvement due to sphingolipid accumulation. Our aim was to present and analyze the demographic and clinical characteristics of the Fabry patients in Romania. All known Fabry patients in Romania between 2015-2018 were prospectively included in the study. Data on personal history, family history and clinical parameters were collected and statistically analyzed. The study included 42 patients with a mean age of 47±15 years, of which 19 (45%) were men and 23 (55%) women. Women were significantly older (52±15 years vs. 40±13 years, p=0.006) and presented similar prevalence of cardiac, renal, neurologic, ophthalmologic and otologic burden. The majority of patients presented organ damage, most prevalent being cardiac (48%), cutaneous (45%) and neurologic (52%) involvements. There were 20 families in total, comprising on average of 2.1 members each. Of the 20 families, only two had the same pathogenic GLA mutation. FD patients in our country show a significant degree of multiorgan involvement with important psychological and social impact on the patients and their families. Women with Fabry disease show similar disease burden as men, but at a later age.

Background: Hypertrophic cardiomyopathy (HCM) is a genetic disorder marked by myocardial hypertrophy, leading to diastolic and systolic dysfunction and heart failure. Traditionally, the burn-out stage is defined by systolic dysfunction, but we propose expanding its definition to include advanced diastolic dysfunction. Methods: We retrospectively analyzed HCM patients (2004–2023) with either systolic dysfunction (left ventricular ejection fraction [LVEF] < 50%) or advanced diastolic dysfunction (preserved LVEF with left atrial enlargement and elevated filling pressures: E/A ≥ 2 or E/e′ ≥ 14). Both subgroups were included under the term “end-stage HCM” and compared to HCM controls with preserved LVEF and impaired relaxation. Results: Of 696 HCM patients, 94 had end-stage HCM (23 with systolic dysfunction, 71 with advanced diastolic dysfunction). Median age was 56.5 years, and 55.3% were male. End-stage HCM patients were more symptomatic at follow-up than controls (91.5% vs. 75.0%, p-value = 0.006), with higher rates of dyspnea and advanced heart failure (38.3% vs. 6.3%, p-value < 0.001). Advanced diastolic dysfunction was associated with a more symptomatic profile (p-value = 0.013) and a high annual mortality rate (2.34%, p = 0.014). Male sex, older age, lower LVEF, and higher E/A predicted systolic dysfunction. Conclusions: Advanced diastolic dysfunction represents an alternative progression pathway in burn-out HCM, requiring distinct management strategies alongside systolic dysfunction.