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Resumen es: Introduccion La insuficiencia cardiaca (IC) es un problema de salud de creciente importancia, especialmente entre los pacientes anosos. Sobre la base ...
This study presents a methodological assessment of teleconnection-based modeling of monthly precipitation extremes in South America, quantified as the number of consecutive days above the month-specific 95th percentile and below the 5th percentile. The analysis covers 2002–2024 using the GPM IMERG Late Daily dataset. A multi-step framework is applied: hierarchical clustering and K-means identify regional patterns of extremes; Non-negative Matrix Factorization and Principal Component Analysis reduce dimensionality; and Variable Importance Analysis with 17 algorithms highlights the most relevant climate indices (CIs). Seasonally filtered time series are modeled using linear regression methods (ridge, lasso, and elastic net) to assess their ability to reproduce the general shape of the target series in a qualitative out-of-sample setting. Results show that wet extremes are more consistently reproduced than dry extremes and display stronger associations with Pacific-based ENSO indices, particularly in western South America, whereas dry extremes are reproduced less consistently, show greater dispersion, and appear less systematically linked to the large-scale indices considered here. By explicitly presenting coefficients and using publicly available indices, the study provides a transparent and interpretable framework for comparing teleconnection-based modeling strategies across regions. Main limitations include the weak reproducibility of dry events and the relatively short monthly record, which may affect the relative performance of the regression models and the VIA-based importance rankings. The contribution of the study therefore lies primarily in methodological comparison, stability assessment, and interpretability under limited sample conditions.
This work investigates the two-dimensional thermal behavior of a bilayer medium subject to both internal and external heat sources. The model incorporates diffusion, advection, and temperature-dependent volumetric heat generation or absorption in each layer, as well as general convective conditions on the external boundaries. The influence of interfacial thermal resistance between the two materials is also considered. An analytical solution is developed using Fourier-based techniques, and a stable and convergent finite difference method is proposed to analyze particular scenarios. The theoretical results are validated against known solutions and numerical simulations, demonstrating consistency with the expected physical behavior. The findings contribute to a deeper understanding of heat transfer phenomena in layered systems and offer potential insights for optimizing thermal performance in engineering applications involving composite materials.
Background & Aims Several clinical risk models have been proposed to stratify hepatocellular carcinoma (HCC) risk in patients with chronic hepatitis C virus (HCV) after sustained virologic response (SVR). However, validation efforts have focused on monocentric or country-specific cohorts, and it is unclear if clinical risk models can be broadly applied to global populations. We characterised regional variation in model performance for HCC risk stratification in post-SVR patients.Methods Four HCC clinical risk models (aMAP score, FIB-4 index, GES score, and Toronto HCC risk index [THRI]) were analysed in six real-world cohorts, which included 8796 post-SVR patients from different geographic regions globally. Model discrimination was assessed using Harrel's c-statistic index. HCC incidence rates were compared across low-, intermediate-, and high-risk groups for each model.Results Distributions of patient characteristics and HCC incidence rates varied across geographic regions. Predictive performances of models were comparable within each cohort despite the model with the highest c-statistics differing by regions. Performance was lower than those from original reports overall; c-statistics of models across most regions remained below 0.70.Conclusions There remains a continued need to improve discrimination and calibration of clinical models to stratify HCC risk in post-SVR patients. Accuracy of models may differ by geographic region, underscoring the importance of external validation to assess transportability of models and suggesting no single model can be universally applied.
La pregunta sobre "¿qué es un buen clínico?" y "¿qué es una buena medicina?" llevan a ponderar cuál es el rol de la persona humana médica en la medicina actual. Excelencia, acierto y prudencia sintetizan la bondad en los actos en medicina. El concepto de acertar, en medicina, resume los principales elementos de la bioética de la virtud en un formato más practicable y comprensible para la práctica clínica. Se reflexiona sobre algunos de ellos. Entre los principios de la bioética y la demanda de la práctica hay un camino del realismo clásico intermedio: el acierto en medicina. Este tiene amplias implicancias en profesionalismo, educación médica y servicios de salud.
