Proyecto Apertura de una Unidad de Fractura Ósea por Fragilidad (FLS) en el H. De la Plana.

Treball Final de Grau en Medicina. Codi: MD1158. Curs acadèmic: 2018/2019.Introduction: ostheoporosis (OP) is a chronic disease characterized by alterations of the bone tissue. These changes in the bone produce a decrease in the resistance and increase the risk of fragility fractures that entail a serious social, clinical and economical problem. Objective: project to open a fracture liaison service (FLS) at the Hospital de La Plana. Methods: we have made an analysis and synthesis of the most up-to-date scientific evidence (using the levels of evidence from the SIGN and critical reading CASPe) and the formulation of recommendations based on these evidence and consensus techniques. Elaboration process: development of the FLS protocol of the Hospital de La Plana with the identification and evaluation of fractured patients as well as the application of a treatment, education and favoring the link between the FLS and primary care to the follow-up of the patients. Conclusion: improve the quality of life of the patients in the La Plana area decreasing the number of fractures through the FLS.Introducción: la osteoporosis (OP) es una enfermedad crónica caracterizada por alteraciones del tejido óseo. Estos cambios en el hueso implican una disminución de la resistencia e incremento de fracturas por fragilidad ósea que conllevan un grave problema de interés clínico, social y económico. Objetivo: proyecto de apertura de una unidad de fractura ósea por fragilidad (FLS) en el Hospital de La Plana. Métodos: se ha realizado un análisis y síntesis de la evidencia científica más actualizada (utilizando los niveles de evidencia del SIGN y lectura crítica CASPe) y formulación de recomendaciones a partir de estas evidencia y técnicas de consenso. Resultados: desarrollo del protocolo de la FLS del Hospital de La Plana con la identificación, evaluación de los pacientes fracturados así como la aplicación de un tratamiento, educación y favorecer el enlace entre la FLS y atención primaria (AP) en el seguimiento de los pacientes. Conclusión: aumentar la calidad de vida de los pacientes del Área de La Plana disminuyendo el número de fracturas a través de la FLS. Palabras clave: fracturas por fragilidad, prevención secundaria, osteoporosis, unidad de fractura por fragilidad

Machine Learning Approaches to Predict Major Adverse Cardiovascular Events in Atrial Fibrillation

The increasing prevalence of atrial fibrillation (AF) and its association with Major Adverse Cardiovascular Events (MACE) presents challenges in early identification and treatment. Although existing risk factors, biomarkers, genetic variants, and imaging parameters predict MACE, emerging factors may be more decisive. Artificial intelligence and machine learning techniques (ML) offer a promising avenue for more effective AF evolution prediction. Five ML models were developed to obtain predictors of MACE in AF patients. Two-thirds of the data were used for training, employing diverse approaches and optimizing to minimize prediction errors, while the remaining third was reserved for testing and validation. AdaBoost emerged as the top-performing model (accuracy: 0.9999; recall: 1; F1 score: 0.9997). Noteworthy features influencing predictions included the Charlson Comorbidity Index (CCI), diabetes mellitus, cancer, the Wells scale, and CHA2DS2-VASc, with specific associations identified. Elevated MACE risk was observed, with a CCI score exceeding 2.67 ± 1.31 (p p < 0.001), and an intermediate-risk Wells scale classification. Overall, the AdaBoost ML offers an alternative predictive approach to facilitate the early identification of MACE risk in the assessment of patients with AF