Syed Yusuf Ali

BACKGROUND: Chronic kidney disease (CKD) is common and ranks among the leading causes of mortality and morbidity. This analysis aimed to present global CKD estimates using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 to inform evidence-based policies for CKD identification and treatment. METHODS: This analysis focused on adults aged 20 years and older over the period 1990 to 2023, from 204 countries and territories. Data sources used were published literature, vital registration systems, kidney failure treatment registries, and household surveys. Estimates of CKD burden, including deaths, incidence, prevalence, and disability-adjusted life-years (DALYs), were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool. A comparative risk assessment approach estimated the proportion of cardiovascular deaths attributable to impaired kidney function and estimated risk factors for CKD. FINDINGS: Globally, in 2023, 788 million (95% uncertainty interval 743-843) people aged 20 years and older were estimated to have CKD, up from 378 million (354-407) in 1990. The global age-standardised prevalence of CKD in adults was 14·2% (13·4-15·2), a relative rise of 3·5% (2·7-4·1) from 1990. The region with the highest age-standardised prevalence was north Africa and the Middle East (18·0%; 16·9-19·4). Most people had stage 1-3 CKD, with a combined prevalence of 13·9% (13·1-15·0). In 2023, CKD was the ninth leading cause of death globally, accounting for 1·48 million (1·30-1·65) deaths, and the 12th leading cause of DALYs, with an age-standardised DALY rate of 769·2 (691·8-857·4) per 100 000. Impaired kidney function as a risk factor accounted for 11·5% (8·4-14·5) of cardiovascular deaths. High fasting plasma glucose, body-mass index, and systolic blood pressure were all leading risk factors for CKD DALYs. INTERPRETATION: CKD is a major global health issue, with rising prevalence and increasing importance as a cause of death and as a risk factor for cardiovascular death. A better understating of aetiology, appropriate screening, and implementation programmes are needed to translate advances in CKD treatment into improved patient outcomes. FUNDING: Gates Foundation, Wellcome, US National Kidney Foundation, and US National Institute of Diabetes and Digestive and Kidney Diseases.

Atrial fibrillation (AF), the most common heart rhythm disorder, may cause stroke and heart failure. For patients with persistent AF with fibrosis proliferation, the standard AF treatment-pulmonary vein isolation-has poor outcomes, necessitating redo procedures, owing to insufficient understanding of what constitutes good targets in fibrotic substrates. Here we present a prospective clinical and personalized digital twin study that characterizes the arrhythmogenic properties of persistent AF substrates and uncovers locations possessing rotor-attracting capabilities. Among these, a portion needs to be ablated to render the substrate not inducible for rotors, but the rest (37%) lose rotor-attracting capabilities when another location is ablated. Leveraging digital twin mechanistic insights, we suggest ablation targets that eliminate arrhythmia propensity with minimum lesions while also minimizing the risk of iatrogenic tachycardia and AF recurrence. Our findings provide further evidence regarding the appropriate substrate ablation targets in persistent AF, opening the door for effective strategies to mitigate patients' AF burden.

A key component in developing atrial digital twins (ADT) - virtual representations of patients' atria - is the accurate prescription of myocardial fibers which are essential for the tissue characterization. Due to the difficulty of reconstructing atrial fibers from medical imaging, a widely used strategy for fiber generation in ADT relies on mathematical models. Existing methodologies utilze semi-automatic approaches, are tailored to specific morphologies, and lack rigorous validation against imaging fiber data. In this study, we introduce a novel atrial Laplace-Dirichlet-Rule-Based Method (LDRBM) for prescribing highly detailed myofiber orientations and providing robust regional annotation in bi-atrial morphologies of any complexity. The robustness of our approach is verified in eight extremely detailed bi-atrial geometries, derived from a sub-millimiter Diffusion-Tensor-Magnetic-Resonance Imaging (DTMRI) human atrial fiber dataset. We validate the LDRBM by quantitatively recreating each of the DTMRI fiber architectures: a comprehensive comparison with DTMRI ground truth data is conducted, investigating differences between electrophysiology (EP) simulations provided by either LDRBM and DTMRI fibers. Finally, we demonstrate that the novel LDRBM outperforms current state-of-the-art fiber models, confirming the exceptional accuracy of our methodology and the critical importance of incorporating detailed fiber orientations in EP simulations. Ultimately, this work represents a fundamental step toward the development of physics-based digital twins of the human atria, establishing a new standard for prescribing fibers in ADT.

Abstract The objective of this research was to investigate the time‐dependent behaviors of yarns, which have significant bearings upon the properties of stretch fabrics made from them. In this study, 100% wool, wool–lycra (W‐L) (97 : 3), and polyester–wool–lycra (P‐W‐L) (52 : 45 : 3) blended yarns were considered. These yarns were subjected to the tensile fatigue failure, stress relaxation, and creep experiments. The findings showed that of these three yarns, P‐W‐L blend exhibited maximum fatigue lifetime, stress retention, and creep recovery, the pure wool yarn followed suit albeit to a lesser extent, whereas the W‐L blend made it least. The investigation suggests that wool alone with lycra as a core component is not sufficient to impart the expected properties upon stretch fabrics, rather a blend of polyester and wool with lycra as in the former would definitely make a worthwhile product. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011