Shelby Kutty

Paediatric heart care is among the most complex, high-risk environments in medicine. Care is delivered by multidisciplinary teams across operating rooms, catheterisation laboratories, cardiac ICUs, and step-down settings, where small failures in communication or coordination may have serious consequences. Although advances in congenital and paediatric cardiac care have improved survival, dysfunctional team dynamics remain an underrecognised contributor to adverse events, inefficiency, clinician distress, and loss of family trust. This review synthesises evidence on how team dysfunction affects outcomes in paediatric heart care, identifies principal forms of dysfunction, and review system-based interventions that may improve team performance and safety. Drawing on literature from paediatric cardiac care, perioperative safety, critical care, interprofessional collaboration, organisational theory, and team science, the review is informed by the Input-Process-Output model, relational coordination, social exchange theory, psychological safety, and high-reliability organisation principles. Common forms of dysfunction include communication failures, hierarchical barriers, unclear role delineation, weak care transitions, and interpersonal conflict. These factors impair shared situational awareness, delay escalation, increase the risk of errors and complications, and affect family trust and clinician well-being. Evidence supports multifaceted strategies including simulation-based team training, structured communication tools, multidisciplinary case review, debriefing, cross-training, conflict-resolution approaches, leadership engagement, and measurement of teamwork processes. Emerging digital tools and artificial intelligence may support situational awareness and information reliability when carefully implemented. Team performance is a central determinant of safety and quality in paediatric heart care. Improving outcomes requires sustained investment in communication, psychological safety, role clarity, mutual respect, and organisational learning.

Innovation in paediatric and adult congenital cardiology increasingly depends on collaboration among academia, industry, and professional communities. From this perspective, the author argues that clinical prediction represents a natural convergence point for these stakeholders, aligning safe, personalised care with economic incentives. The author discusses emerging evidence highlighting the promise of artificial intelligence-driven prediction across various cardiovascular domains, while highlighting current limitations related to narrow scope, static design, and weak integration into clinical decision-making. Medicine-based evidence and a high-quality, inclusive data infrastructure may help address these gaps. Together, these approaches, along with stakeholders upholding their responsibilities, define a path towards predictive innovation.

Aims: The aim of the current study was to assess the utility of a state-of-the-art large language model (LLM) based on curated, defined clinical practice recommendations to support clinicians in obtaining point-of-care guidelines for individual patient treatment while maintaining transparency. Methods and results: We combined cloud-based and locally run LLMs with versatile open-source tools to form a multi-query, multimodal, retrieval-augmented generation chain that closely reflects European cardiology guidelines in its responses. We compared the performance of this generation chain to other LLMs including GPT-3.5 and GPT-4 on a 306-question multiple-choice exam with questions consisting of short patient vignettes from various cardiology subspecialties, originally written to prepare candidates for the European Exam in Core Cardiology. On the multiple-choice test, our system demonstrated overall accuracy of 73.53%, while GPT-3.5 and GPT-4 had overall accuracies of 44.03 and 62.26%, respectively. Our system outperformed GPT-3.5 and GPT-4 for the following categories of questions: coronary artery disease, arrhythmia, other, valvular heart disease, cardiomyopathies, endocarditis, adult congenital heart disease, pericardial disease, cardio-oncology, pulmonary hypertension, and non-cardiac surgery. For maximum transparency, the system also provided reference quotes for its recommendations. Conclusion: Our system demonstrated superior performance in question-answering tasks on a set of core cardiology questions as compared with contemporary publicly available chat models. The current study illustrates that LLMs can be tailored to provide documented and accountable guideline recommendations towards actual clinical needs while ensuring recommendations are derived from up-to-date, trustable, and traceable documents.

Background: Load dependence on left ventricular (LV) strain is under constant debate with its interference with prognostic implications remaining unclear. Consequently, we sought to investigate their interaction and prognostic value following acute myocardial infarction (AMI) using state-of-the-art cardiac magnetic resonance (CMR) imaging. Methods: In total, 1235 patients (n = 795 ST-elevation [STEMI] and 440 non-STEMI) underwent CMR in median 3 days following AMI. Infarct characteristics were described by CMR using tissue characterisation (infarct size, microvascular obstruction, area at risk) and deformation imaging including LV global longitudinal and circumferential strain (GLS/GCS). Non-invasive haemodynamic indices included effective arterial elastance Ea (end-systolic pressure (ESP)/stroke volume) and the non-geometric LV end-systolic afterload index NGI [(ESP × LV end-systolic volume (ESV))/LV mass] for estimation of LV afterload. LV contractility was assessed using end-systolic elastance Ees (ESP/LV ESV). Ventriculo–arterial coupling was described as Ea/Ees. Major adverse cardiac events (MACE) were recorded within the first year. Results: All haemodynamic indices were impaired in patients with MACE during follow-up compared to patients without (p < 0.001–0.005). Ventriculo–arterial coupling showed the highest correlation to infarct properties (infarct size r = 0.51, p < 0.001) and deformation imaging (GLS r = 0.54, GCS r = 0.72, p < 0.001). GLS and GCS were associated with MACE independently of all haemodynamic indices (p < 0.001 for all except of GCS-Ea/Ees p = 0.024). Conclusions: Non-invasive haemodynamic indices are associated with outcome following AMI with ventriculo–arterial coupling showing the most prominent association to infarct properties and outcome. GCS showed higher correlation to haemodynamic indices compared to GLS whilst both are independent predictors for MACE. Graphical

Background: There is significant interest in NO pathway modulators, specifically type 5 phosphodiesterase inhibitors (PDE5is), to treat patients with a Fontan circulation. Trials, however, have had mixed results. The relationship between the NO pathway and clinical status in patients with Fontan circulation is a significant knowledge gap. Methods and Results: We performed targeted metabolomic analysis using liquid chromatography coupled to mass spectrometry to quantify plasma NO pathway metabolite concentrations from 2 well‐characterized populations of patients with Fontan circulation: the Boston Adult Congenital Heart Disease Biobank and Fontan Udenafil Exercise Longitudinal studies. We investigated associations between NO metabolite concentrations and clinical outcomes, exercise capacity, and response to PDE5is. Increased plasma concentration of asymmetric dimethyl arginine (ADMA), an inhibitor of NO production, was associated with risk for hospitalization or death. Increased ADMA and symmetric dimethyl arginine (another inhibitor of NO production) concentrations were associated with decreased baseline exercise capacity among patients with Fontan circulation with <90% predicted peak oxygen uptake, and change in ADMA and symmetric dimethyl arginine concentrations were predictive of change in exercise capacity over time. Treatment with the PDE5i udenafil uncoupled this association. Finally, baseline ADMA and symmetric dimethyl arginine concentrations predicted response to PDE5is among patients with subnormal peak oxygen uptake. Conclusions: Plasma concentrations of metabolites that inhibit NO flux are associated with negative clinical outcomes and worse exercise capacity. Moreover, metabolite shifts over time associated with increased NO flux are associated with improved exercise capacity. In patients with a Fontan circulation, the NO pathway modulators ADMA and symmetric dimethyl arginine may be useful as biomarkers of clinical status and predictive of response to PDE5is.

Background/Objectives: While speckle-tracking echocardiography (STE) is increasingly gaining acceptance in the medical community, establishing normal pediatric values and interpreting data derived from software provided by various vendors can pose significant challenges. This review aims to present an updated compilation of nomograms pertinent to speckle-tracking echocardiography. Methods: A review of research using three medical engine searches (National Library of Medicine, Science Direct, and Cochrane Library) for Medical Subject Headings (MeSH) and the free text terms “echocardiography”, “STE”, “normal values”, and ”children” was performed and refined by adding the keywords “nomograms”, “z-scores”, and “healthy children”. Results: A total of twenty-five studies were selected for the final analysis. Our research indicated that current nomograms provide adequate coverage of most strain parameters; however, those pertaining to the right ventricle and the atria are less numerous than those for the left ventricle. A noted trend suggests a decrease in strain values with advancing age and increasing body surface area; nevertheless, the relationships observed were weak and nonlinear. The absence of robust correlations between strain values and age and body size parameters hindered the generation of a Z-score possessing sufficient statistical power. Consequently, normal values are primarily represented as mean values accompanied by standard deviation. A comparative analysis of vendors demonstrated good agreement between different versions of the same platform for Philips (except for QLAB 5) and, similarly, between General Electric (GE) and TomTec. The limited data available regarding the comparison between GE and Philips revealed significant findings that warrant further investigation of differences. Conclusions: A comprehensive review and an updated list of current pediatric nomograms for STE measurements have been presented. This may serve as a valuable guide for accurately interpreting STE in pediatric patients with congenital and acquired heart disease.