6 research outputs found
Mitral regurgitation in heart failure with preserved ejection fraction: The interplay of valve, ventricle, and atrium.
Full text linkMitral regurgitation (MR) is highly prevalent among patients with heart failure and preserved ejection fraction (HFpEF). Despite this combination being closely associated with unfavourable outcomes, it remains relatively understudied. This is partly due to the inherent heterogeneity of patients with HFpEF. To address this gap, dissecting HFpEF into mechanism-based phenotypes may offer a promising avenue for advancing our comprehension of these complex intertwined conditions. This review employs the validated CircAdapt model to explore the haemodynamic implications of moderate to severe MR across a well-defined spectrum of myocardial disease, characterized by impaired relaxation and reduced myocardial compliance. Both heart failure and mitral valve disease share overlapping symptomatology, primarily attributed to elevated pulmonary pressures. The intricate mechanisms contributing to these elevated pressures are multifaceted, potentially influenced by diastolic dysfunction, left atrial myopathy, and MR. Accurate evaluation of the haemodynamic and clinical impact of MR necessitates a comprehensive approach, taking into account the characteristics of both the left atrium and left ventricle, as well as their intricate interactions, which may currently be underemphasized in diagnostic practice. This holistic assessment is imperative for enhancing our understanding and refining therapeutic strategies within this patient cohort
The Impact of Left Ventricular Stiffness on Hemodynamic Responses to Mitral Regurgitation at Rest and During Exercise
No full textThe coexistence of mitral regurgitation (MR) and heart failure with preserved ejection fraction (HFpEF) poses a significant diagnostic challenge, as both increase left heart filling pressure and drive symptoms of congestion. Exercise testing has emerged as a valuable diagnostic tool in valvular heart disease, yet the comparative impact of myocardial abnormalities on exercise hemodynamics in MR patients remains unclear. Using computational modeling, we investigated how increased left ventricular (LV) stiffness – a characteristic feature of HFpEF – influences hemodynamic responses to MR both at rest and during exercise. Using the CircAdapt cardiovascular model, we simulated three myocardial phenotypes with comparable resting mean left atrial pressure (mLAP): isolated LV stiffening, isolated severe MR, and mild-to-moderate MR combined with increased LV stiffness. We analyzed conventional echocardiographic indices at rest and assessed cardiac exercise performance (CEP), defined as the maximum cardiac output achievable before reaching an exercise-limiting mLAP threshold of 35 mmHg, in addition to regurgitation fraction. Despite distinct underlying pathophysiology, all virtual patients demonstrated similar resting echocardiographic indices, including E/A ratio and maximum left atrial volume, while E-wave deceleration time showed variability across phenotypes. However, exercise simulation revealed marked differences in cardiac performance. Isolated LV stiffening resulted in the poorest exercise tolerance (CEP: 8.6 L/min) compared to isolated MR (CEP: 14.0 L/min) and combined mild-to-moderate MR with LV stiffening (CEP: 11.9 L/min). Our simulations imply that as exercise intensity increases, regurgitant fraction decreases, which reduces the hemodynamic impact of MR. This suggests that LV stiffening, rather than MR severity alone, appears to be the predominant limiting factor during exercise. Our computational study suggests that flow- and volumetric-derived resting echocardiographic indices may not differentiate between isolated MR and combined MR with LV stiffening, despite significant differences in exercise capacity. These findings emphasize the importance of exercise testing in evaluating cardiac function and highlight the need for comprehensive myocardial assessment in patients with MR and suspected HFpEF
Numerical accuracy of closed-loop steady state in a zero-dimensional cardiovascular model
No full textClosed-loop cardiovascular models are becoming vital tools in clinical settings, making their accuracy and reliability paramount. While these models rely heavily on steady-state simulations, accuracy because of steady-state convergence is often assumed negligible. Using a reduced-order cardiovascular model created with the CircAdapt framework as a case study, we investigated steady-state convergence behaviour across various integration methods and simulation protocols. To minimize the effect of numerical errors, we first quantified the numerical errors originating from integration methods and model assumptions. We subsequently investigate this steady-state convergence error under two distinct conditions: first without, and then with homeostatic pressure-flow control (PFC), providing a comprehensive assessment of the CircAdapt framework's numerical stability and accuracy. Our results demonstrated that achieving a clinically accurate steady state required 7-15 heartbeats in simulations without regulatory mechanisms. When homeostatic control mechanisms were included to regulate mean arterial pressure and blood volume, more than twice the number of heartbeats was needed. By simulating a variable number of heartbeats tailored to each simulation's characteristics, an efficient balance between computational cost and steady-state accuracy can be achieved. Understanding this balance is crucial as cardiovascular models progress towards clinical use. This article is part of the theme issue 'Uncertainty quantification for healthcare and biological systems (Part 2)'
The CircAdapt Framework:Create Fast Computational Models of Cardiovascular Function
No full textThe CircAdapt framework marks a milestone in cardiovascular system modeling, transforming the established CircAdapt model into a comprehensive platform that enables the development and implementation of multiple model variants. At its core, the framework maintains the one-fiber assumption to relate local sarcomere mechanics to global hemodynamics. The framework consists of three components: a high-performance C++ library, a Python-based interface (pyCircAdapt), and a graphical user interface (CircAdaptUI). The C++ library serves as the computational engine, featuring extensively verified modules that define ordinary differential equations for cardiovascular simulation. These modules undergo rigorous testing and are complemented by comprehensive documentation. PyCircAdapt provides a user-friendly wrapper that simplifies interaction with the core library, allowing researchers to focus on conceptual model development rather than numerical implementation. The framework supports both closed-loop and open-loop configurations. Additionally, the framework’s modular architecture enables external module development, providing flexibility for specialized research applications while maintaining high computational efficiency. A graphical user interface (CircAdaptUI) further enhances accessibility for research and educational purposes. This paper presents the framework’s architecture, components, and capabilities, demonstrating its versatility in creating fast, functional cardiovascular models tailored to specific research needs
Impact of left-heart myopathy on mitral valve stenosis assessment and interventional outcomes:an in-silico trial
No full textAims The shift in mitral stenosis (MS) aetiology from rheumatic to calcific valve disease complicates distinguishing valve-related from myocardial-driven haemodynamic abnormalities. This study examines how left-heart myopathy influences flow velocity-based echocardiographic MS severity assessment and evaluates haemodynamic changes following mitral valve (MV) intervention at rest and during exercise.Methods and results The CircAdapt biophysical model was used to create a virtual cohort with varying MS severity, left ventricular (LV) compliance, and left atrial (LA) function. Mean gradient (MG) was evaluated alongside left-heart pressures at rest and during exercise. To study acute haemodynamic effects of MV intervention, the mitral valve's effective orifice area was restored to 5.9 cm(2). MG showed variation of 1 mmHg attributable to left-heart myopathy. Following virtual MV intervention for clinically significant MS, mean left atrial pressure (mLAP) decreased by 50% in patients with preserved myocardial function but remained elevated in those with LV and LA dysfunction due to persistently elevated LV end-diastolic pressure, resulting in persistently impaired exercise capacity.Conclusion Virtual patient cohorts suggest that MV intervention reduces MG but may not normalize mLAP in patients with impaired LV and LA function. Persistent myocardial dysfunction may limit both symptomatic and exercise capacity improvement, despite successful intervention. As percutaneous treatment options expand, distinguishing myocardial from valve-driven abnormalities is essential for accurate assessment, patient selection, and optimizing outcomes
ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19
Full text linkThe International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use
