ERN GUARD-Heart

Hypertrophic cardiomyopathy (HCM) is an inherited heart disease characterized by unexplained left ventricular hypertrophy with or without outflow tract obstruction. Conventional therapies may relieve symptoms associated with left ventricular outflow tract (LVOT) obstruction; however, they do not act directly on the contractile cell, and refractory patients may require septal reduction therapy. Allosteric cardiac myosin inhibitors (CMIs) represent a novel therapeutic approach directly targeting sarcomeric hypercontractility. Mavacamten and aficamten have demonstrated significant clinical and haemodynamic benefits in obstructive HCM (oHCM). The MAPLE-HCM trial revealed that aficamten significantly improved peak oxygen uptake, NYHA functional class, quality of life, and reduced LVOT gradients compared with metoprolol, with a favourable safety profile. Encouraged by these findings, CMIs have been investigated in non-obstructive HCM (nHCM). The ODYSSEY-HCM trial evaluated mavacamten in patients with symptomatic nHCM. While the primary endpoints of exercise capacity and patient-reported health status were not met, secondary analyses showed favourable effects on NT-proBNP, high-sensitivity troponin I, left ventricular diastolic function, and hypertrophy parameters. In conclusion, CMIs offer substantial benefits in oHCM, improving symptoms and cardiac haemodynamics. In nHCM, despite limited impact on functional capacity, CMIs demonstrate biological activity and favourable cardiac remodelling, supporting further research into their potential role in modulating disease pathophysiology.

The aim of the study was to comprehensively characterize the population of hypertrophic cardiomyopathy (HCM) patients in Poland in 2016-2021, including the analysis of annual incidence, prevalence, comorbidities, and therapeutic paths. A population-based cross-sectional study was conducted using data from the Polish National Health Fund database. The analysis included a registered annual incidence and prevalence rates, mortality, prognosis, and data on patients pathways in the healthcare system. In 2016, the registered annual incidence of HCM diagnosis in Poland was 1,494 cases (3.89/100,000), decreasing to 808 cases (2.11/100,000) in 2021. Despite the decline in new diagnoses, the registered prevalence of HCM increased from 13,271 cases (34.53/100,000) in 2016 to 13,880 cases (36.23/100,000) in 2021, indicating improved patient survival. Annual mortality rose from 824 deaths (2.14/100,000) in 2016 to 1,022 deaths (2.67/100,000) in 2021, with the highest mortality observed in older adults (60+ years). The study highlights significant underdiagnosis of HCM in Poland. Mortality in HCM population remains high, underscoring the need for improvement in earlier detection and comprehensive care strategies in Polish healthcare system.

Double-seropositive anti-glomerular basement membrane (GBM) disease, characterized by the presence of both anti-GBM and anti-neutrophil cytoplasmic autoantibodies (ANCAs), is extremely rare in children. Double-seropositive patients represent a hybrid phenotype combining the severe acute kidney injury of isolated anti-GBM disease with the relapse risk and subsequent need for maintenance treatment of ANCA-associated vasculitis. Here we present the case of an 11-year-old girl presenting with rapidly progressive glomerulonephritis leading to kidney failure and warranting kidney replacement therapy. Anti-GBM antibodies and myeloperoxidase-ANCAs were both detected in serum. Kidney histopathology revealed over 90% crescents. Despite the aggressive presentation, treatment with high-dose corticosteroids, plasmapheresis, and rituximab led to recovery of kidney function and dialysis discontinuation. Our case suggests that rituximab, without cyclophosphamide, may represent a promising therapeutic approach in children with double-seropositive anti-GBM disease, even in severe presentations.

The European Federation of Internal Medicine (EFIM) was founded in 1996 by merging the Association Européenne de Médecine Interne and the Forum of Presidents of National Internal Medicine Societies in Europe, creating aunified platform for continental collaboration among national societies. Today, EFIM represents 48societies from 45countries-over 70,000 internists-making it one of Europe's largest medical federations. Its mission is to promote internal medicine scientifically, ethically, and professionally, centered on education, research, and advancement through research publication, congresses, internist communication, and health expertise. This article examines the present and future of internal medicine in light of EFIM's new policy, "Internal Medicine in the 21st Century: Back to the Future." It offers a critical appraisal of current challenges alongside strengths and opportunities. Internal medicine represents acornerstone of future hospitals and healthcare systems rather than aresidual specialty. Strengthening and standardizing training and granting internists formal leadership in care coordination and education will ensure sustainable, person-centered healthcare.

Spinal muscular atrophy (SMA) types III and IV are the most common late-onset forms, and they progress slowly, making the identification of sensitive biomarkers critical. The Motor Unit Number Index (MUNIX) estimates motor unit loss and may complement traditional electrophysiological measurements such as Compound Muscle Action Potential amplitudes (CMAP). However, their respective performances have never been directly compared in adult SMA. In a French multicenter study (NCT04690998), 71 adult patients with SMA and 24 healthy controls underwent clinical and electrophysiological evaluation. MUNIX, CMAP, and Motor Unit Size Index (MUSIX) were recorded in four muscles, and sum scores (SumMUNIX, SumCMAP, SumMUSIX) were calculated. Reliability was assessed using intraclass correlation coefficients (ICCs), and associations with functional outcomes were explored. MUNIX and CMAP effectively distinguished SMA patients from controls, showing strong test - retest reliability. MUNIX showed the highest discriminative performance (AUC = 0.92), while CMAP demonstrated the strongest and most consistent associations with clinical severity. In multivariate analyses, only CMAP remained independently associated with all functional and strength measures, whereas MUNIX and MUSIX lost significance. MUNIX demonstrated the highest discriminative performance among biomarkers for differentiating SMA from controls, indicating early motor unit loss even when CMAP values were within normal limits. However, disease burden and functional impairment were better reflected by CMAP, probably due to it integrating both motor unit loss and reinnervation. The complementary nature of these profiles supports their combined use (concurrent application), and longitudinal studies are warranted to assess their responsiveness in adult SMA as well as their appropriateness for clinical trial settings.

The present Reply addresses the commentary by Pagnoni et al. on our recent study exploring explainable artificial intelligence (AI) for mortality risk prediction in pulmonary arterial hypertension (PAH). We acknowledge the importance of several key issues raised by the authors, including endpoint selection, calibration, decision thresholds, and external validation, all of which are central to translating AI-based prognostic models into clinical practice. Our original endpoint, defined as death by the next follow-up visit, was driven by the structure of nationwide registry data and reflects real-world clinical workflows, although we recognize the advantages of predefined time horizons and time-to-event approaches for future analyses. We discuss the trade-off between sensitivity and precision, emphasizing our deliberate prioritization of minimizing false-negative classifications in high-risk patients, while acknowledging the need for structured clinical pathways to manage false-positive results. We further address calibration and threshold selection, underscoring the necessity of additional clinical studies to support intervention-oriented recommendations. The role of phenotypic determinants and modifiable risk factors in enhancing personalization is highlighted as a key direction for future model development. We reaffirm the value of SHAP-based explainability for improving model transparency, while recognizing the need for continued refinement and clinical validation. Finally, we emphasize the strengths and challenges inherent to registry-based analyses, the importance of external validation, and the need for methodologically sound comparisons with established risk calculators. Overall, this exchange underscores the critical role of interdisciplinary collaboration in advancing clinically actionable and interpretable AI solutions for PAH.

<h2>Abstract</h2> Steatotic liver disease (SLD) is a spectrum of highly prevalent liver disease that is encountered at many different healthcare levels. Awareness about metabolic dysfunction-associated SLD (MASLD), MetALD (MASLD and increased alcohol intake) and ALD (alcohol-related liver disease) is increasing beyond hepatology, as highlighted by the various SLD guidelines that have been issued by scientific societies from different disciplines, such as endocrinology. The guidance presented here aims to improve cross-disciplinary knowledge and know-how by providing guidance to healthcare professionals from a global, holistic, multi-society and -stakeholder perspective. The patient trajectory was used as an overarching anchor point to ensure uniform guidance at all points along the SLD spectrum, with the ultimate goal of improving patient identification and optimising their care. This consensus guidance covers patient identification and risk stratification, relevant cross-disciplinary primary and secondary care approaches, referral to and from tertiary care and strategies for disease management and monitoring. Strategies at each point of the patient trajectory are recommended and stratified as optimal (i.e., "nice-to-have") or minimal (i.e., "must-have"), per expert-opinion, making them adaptable to differences in healthcare settings, levels of resource availability and policies.