XEN® 45 en el manejo quirúrgico del glaucoma en fases tempranas: estudio nacional de consenso según metodología Delphi / XEN-45 in the management of Early Glaucoma Surgery: A National Delphi Consensus Study

Antecedentes y objetivo: Las recomendaciones sobre el manejo general del glaucoma y el uso de cirugías mínimamente-invasivas y microincisionales en fases tempranas son limitadas. El objetivo de este estudio fue establecer un consenso sobre el manejo del glaucoma, centrándose en el implante XEN 45 (AbbVie Inc., North Chicago, IL, EE. UU.). Métodos: Se utilizó un método Delphi. El comité científico dirigió el estudio, identificó el panel de expertos y participó en la elaboración del cuestionario. Se invitó a 51 expertos a completar, en una escala Likert de 9 puntos, un cuestionario de 89 ítems que cubría 3 bloques temáticos. Se realizaron 2 rondas Delphi. Se logró consenso si≥66,6% de los expertos llegaron a un acuerdo o desacuerdo. Resultados: Los panelistas acordaron 84 ítems relacionados con la calidad de vida, el algoritmo terapéutico y el perfil del paciente, y el manejo quirúrgico pre y postoperatorio. Los panelistas consideraron el implante XEN idóneo para tratar el glaucoma en diferentes etapas y para diferentes perfiles de pacientes: pacientes jóvenes/ancianos/con comorbilidades-significativas, glaucoma-miópico, pacientes con fracaso quirúrgico previo y con postoperatorio complejo. El implante XEN se consideró un paso terapéutico previo a la cirugía filtrante clásica y una posible primera opción quirúrgica en pacientes ancianos con comorbilidades y presión intraocular descontrolada. El implante XEN permite al paciente retomar sus actividades diarias más rápidamente que las cirugías filtrantes convencionales y reducir y/o eliminar los tratamientos tópicos. Conclusiones: Este consenso según la metodología Delphi proporcionó una serie de recomendaciones generales para el tratamiento del glaucoma, incluidas aquellas relacionadas con la calidad de vida del paciente, el algoritmo terapéutico y el perfil del paciente, y específicas con respecto al uso del implante XEN.(AU)

Background and objective: Recommendations on general glaucoma management and the use of early minimally invasive and microincisional surgeries are limited. This study aimed to establish consensus regarding glaucoma management, focusing on the XEN-45 gel stent implant. Methods: A Delphi consensus-driven process was used. The scientific committee led the study, identified the expert panel, and participated in elaborating the questionnaire. Fifty-one panelists were invited to complete, on a nine-point Likert scale, an 89-item questionnaire covering three topic blocks. Two Delphi rounds were performed. Consensus was achieved if ≥66.6% of panelists reached agreement or disagreement. Results: Panelists agreed on 84 items related to the patients’ quality of life, the therapeutic algorithm and patient profile, and surgical and pre- and post-operative management. Panelists agreed on the suitability of XEN stent implants to treat glaucoma at different stages and for different patient profiles: young patients, elderly or with significant comorbidities, and with myopic glaucoma, patients who failed previous surgeries, and with previous poor post-operative experience. XEN surgery was considered a therapeutic step prior to classic filtering surgery and a possible first surgical option in elderly patients with comorbidities and uncontrolled intraocular pressure. XEN surgery allows the patient to return to routine daily activities faster than conventional filtering surgeries and to reduce and/or eliminate topical treatments. Conclusions: This Delphi-driven consensus resulted in a series of general recommendations for glaucoma management, including those related to patient quality of life, therapeutic algorithm, and patient profile, and specific ones regarding the use of XEN stent gel surgery.(AU)

Identification of ferroptosis-related diagnostic markers in primary Sjögren's syndrome based on machine learning / Identificación de marcadores diagnósticos relacionados con la ferroptosis en el síndrome de Sjögren primario basado en aprendizaje automático

Background: Primary Sjogren's syndrome (pSS) is a common autoimmune disorder that affects up to 0.3-3% of the global population. Ferroptosis has recently been identified to play a significant role in autoimmune diseases. However, the molecular mechanisms of ferroptosis in the initiation and progression of pSS remains unclear. Material and Methods: To investigate the molecular mechanisms underlying the occurrence and progression of pSS, we utilized a comprehensive approach by integrating data obtained from the Gene Expression Omnibus (GEO) database with data from the FerrDb database to identify the ferroptosis-related differentially expressed genes (DEGs). Furthermore, we implemented an innovative transcriptomic analysis method utilizing a computer-aided algorithm to establish a network between hub genes associated with ferroptosis and the immune microenvironment in pSS patients. Results: Our results revealed significant differences in the gene expression profiles of pSS samples compared to normal tissues, with 1,830 significantly up-regulated genes and 1,310 significantly down-regulated genes. In addition, our results showed a significant increase in the proportions of B cells and CD4+ T cells in pSS samples compared to normal tissues. AND then, our analysis revealed that a combination of six ferroptosis-related genes, including TBK1, SLC1A4, PIK3CA, ENO3, EGR1, and ATG5, could serve as optimal markers for the diagnosis of pSS. The combined analysis of these six genes accurately diagnosed the occurrence of pSS. Conclusions: This study offers valuable insights into the pathogenesis of pSS and highlights the importance of targeting ferroptosis-related DEGs, which suggests a novel treatment strategy for pSS.(AU)

Abordaje integral del vértigo: algoritmo diagnóstico, causas, tratamientos y criterios de derivación desde la perspectiva de atención primaria. Documento de consenso SEMERGEN / Comprehensive approach to vertigo: Diagnostic algorithm, causes, treatments, and referral criteria from the perspective of primary care. SEMERGEN consensus document

El vértigo es un síntoma común que puede tener diversas causas y requerir un enfoque integral para su diagnóstico y tratamiento desde atención primaria. Se propone un algoritmo de diagnóstico basado en la clasificación propuesta por la Comisión de Otoneurología de la SEORL-PCF, que facilita la clasificación de los diferentes tipos de vértigo y proporciona criterios de derivación de pacientes desde atención primaria hacia otras especialidades. Se realiza una revisión de los tratamientos disponibles basada en la causa subyacente para un manejo terapéutico adecuado. Se espera que este documento se convierta en una herramienta valiosa para los profesionales que atienden a pacientes con vértigo. El documento se basa en evidencia científica y en la experiencia de expertos en el campo de las diferentes especialidades médicas implicadas; y busca mejorar la comprensión y el abordaje clínico del vértigo agudo desde atención primaria.(AU)

Vertigo is a common symptom that can have various causes and may require a comprehensive approach for its diagnosis and treatment from primary care. A diagnostic algorithm based on the classification proposed by the Otoneurology Commission of the SEORL-PCF is suggested, which facilitates the classification of the different types of vertigo and provides referral criteria for patients from primary care to other specialties. A review of the available treatments based on the underlying cause is conducted for appropriate therapeutic management. This document is expected to become a valuable tool for professionals treating patients with vertigo. The document is based on scientific evidence and on the experience of experts in the field from various medical specialties; and seeks to improve the understanding and clinical approach to acute vertigo from primary care.(AU)

Lesiones cutáneas reticulares: algoritmo clínico práctico basado en el color de la lesión para el abordaje inicial / Reticulate Skin Lesions: Practical Color-Based Algorithm for Initial Clinical Assessment

Las enfermedades dermatológicas que cursan con un patrón reticular son múltiples y variadas. Aunque dicho patrón particular de presentación morfológica muchas veces es muy distintivo, usualmente es poco discutido y estudiado en el contexto clínico. A menudo, estos patrones no se abordan como una categoría diagnóstica propia. Asimismo, las etiologías de este grupo de enfermedades son diversas, desde causas vasculares, infecciosas, tumorales, inflamatorias, metabólicas o genéticas. Además, pueden variar desde condiciones relativamente benignas hasta enfermedades graves que amenazan la vida. Este artículo tiene como objetivo discutir la enfermedad de la piel que se manifiesta con lesiones reticulares y se propone un algoritmo de diagnóstico clínico, basado en el color predominante de las lesiones y los principales hallazgos clínicos, para un abordaje práctico inicial (AU)

Reticular patterns are observed in a great variety of skin diseases. While these morphologic patterns are often highly distinctive, they are seldom discussed or studied in clinical contexts or recognized as a diagnostic category in their own right. Diseases presenting with reticulate skin lesions have multiple etiologies (tumors, infections, vascular disorders, inflammatory conditions, and metabolic or genetic alterations) and can range from relatively benign conditions to life-threatening ones. We review a selection of these diseases and propose a clinical diagnostic algorithm based on predominant coloring and clinical features to aid in their initial assessment (AU)

[Translated article] Reticulate Skin Lesions: Practical Color-Based Algorithm for Initial Clinical Assessment / Lesiones cutáneas reticulares: algoritmo clínico práctico basado en el color de la lesión para el abordaje inicial

Reticular patterns are observed in a great variety of skin diseases. While these morphologic patterns are often highly distinctive, they are seldom discussed or studied in clinical contexts or recognized as a diagnostic category in their own right. Diseases presenting with reticulate skin lesions have multiple etiologies (tumors, infections, vascular disorders, inflammatory conditions, and metabolic or genetic alterations) and can range from relatively benign conditions to life-threatening ones. We review a selection of these diseases and propose a clinical diagnostic algorithm based on predominant coloring and clinical features to aid in their initial assessment (AU)

Las enfermedades dermatológicas que cursan con un patrón reticular son múltiples y variadas. Aunque dicho patrón particular de presentación morfológica muchas veces es muy distintivo, usualmente es poco discutido y estudiado en el contexto clínico. A menudo, estos patrones no se abordan como una categoría diagnóstica propia. Asimismo, las etiologías de este grupo de enfermedades son diversas, desde causas vasculares, infecciosas, tumorales, inflamatorias, metabólicas o genéticas. Además, pueden variar desde condiciones relativamente benignas hasta enfermedades graves que amenazan la vida. Este artículo tiene como objetivo discutir la enfermedad de la piel que se manifiesta con lesiones reticulares y se propone un algoritmo de diagnóstico clínico, basado en el color predominante de las lesiones y los principales hallazgos clínicos, para un abordaje práctico inicial (AU)

Precisión diagnóstica de la TC-RFF con un nuevo algoritmo de subpíxel grueso a fino en la detección de isquemia específica de lesión: un estudio multicéntrico prospectivo / Diagnostic accuracy of CT-FFR with a new coarse-to-fine subpixel algorithm in detecting lesion-specific ischemia: a prospective multicenter study

Introduction and objectives A new computed tomography-derived fractional flow reserve (CT-FFR) technique with a “coarse-to-fine subpixel” algorithm has been developed to generate precise lumen contours. The aim of this study was to assess the diagnostic performance of this new CT-FFR algorithm for discriminating lesion-specific ischemia using wire-based FFR ≤ 0.80 as the reference standard in patients with coronary artery disease. Methods This prospective, multicenter study screened 330 patients undergoing coronary CT angiography (CCTA) and invasive FFR (median interval 2 days) from 6 tertiary hospitals. CT-FFR was evaluated in a blinded fashion with a “coarse-to-fine subpixel” algorithm for lumen contour. Results Between March 2019 and May 2020, we included 316 patients with 324 vessels. There was a good correlation between CT-FFR and invasive FFR (r=0.76, P<.001). The diagnostic sensitivity, specificity, and accuracy on a per-vessel level were 95.3%, 89.8%, and 92.0% for CT-FFR, and 96.4%, 26.4%, and 53.1% for CCTA>50% stenosis, respectively. CT-FFR showed improved discrimination of ischemia compared with CCTA alone overall (AUC, 0.95 vs 0.74, P<.001) and in intermediate (AUC, 0.96 vs 0.62, P<.001) and “gray zone” lesions (AUC, 0.88 vs 0.61, P<.001). The diagnostic specificity, accuracy, and AUC for CT-FFR (71.9%, 82.8%, and 0.84) outperformed CCTA (9.4%, 48.3%, and 0.66) in patients or in vessels with severe calcification (all P<.05). Conclusions CT-FFR with a new “coarse-to-fine subpixel” algorithm showed high performance in identifying hemodynamically significant stenosis. The diagnostic performance of CT-FFR was superior to that of CCTA in intermediate lesions, “gray zone” lesions, and severely calcified lesions (AU)

Introducción y objetivos Se ha desarrollado una nueva técnica basada en tomografía computarizada para la evaluación de la reserva fraccional de flujo (TC-RFF) con un algoritmo de subpíxel «de grueso a fino» para generar contornos luminales precisos. El objetivo de este estudio es evaluar el rendimiento diagnóstico de este nuevo algoritmo de TC-RFF para discriminar la isquemia específica de lesión utilizando la evaluación invasiva de la RFF ≤ 0,80 como referencia en pacientes con enfermedad coronaria. Métodos Este estudio prospectivo y multicéntrico evaluó a 330 pacientes sometidos a angiografía coronaria no invasiva con TC (ACTC) y evaluación invasiva de la RFF (mediana del intervalo, 2 días) en 6 hospitales terciarios. La TC-RFF se evaluó a ciegas con un algoritmo de subpíxel «de grueso a fino» para la evaluación de la luz. Resultado Entre marzo de 2019 y mayo de 2020, se incluyó a un total de 316 pacientes con 324 vasos. Hubo una buena correlación entre la TC-RFF y la evaluación invasiva de la RFF (r=0,76; p<0,001). La sensibilidad, la especificidad y la exactitud diagnóstica por vaso fueron, respectivamente, del 95,3, el 89,8 y el 92,0% para la TC-RFF y del 96,4, el 26,4 y el 53,1% para la ACTC para las estenosis>50%. La TC-RFF mostró mejor discriminación de la isquemia que la ACTC sola en general (ABC=0,95 frente a ABC=0,74; p<0,001) y en lesiones intermedias (ABC=0,96 frente a ABC=0,62; p<0,001) y en «zona gris» (ABC=0,88 frente a ABC=0,61; p<0,001). La especificidad, la exactitud y el ABC diagnóstica de la TC-RFF (el 71,9%, el 82,8% y 0,84) superaron las de la ACTC (el 9,4%, el 48,3% y 0,66) en pacientes o vasos con calcificación grave (todos, p<0,05). Conclusiones La TC-RFF con un algoritmo de subpíxel «de grueso a fino» proporcionó un alto rendimiento en la identificación de estenosis hemodinámicamente significativas. El rendimiento diagnóstico de la TC-RFF fue superior al de la ACTC en lesiones intermedias, de «zona gris» y con calcificación grave (AU)

Mexican consensus on cow’s milk protein allergy

Background: The aim of this study is to present the current views of a diverse group of experts on the diagnosis and treatment of Cow’s Milk Protein Allergy (CMPA) in children under 2 years of age in Mexico. Material and methods: The study, led by a scientific committee of five experts in CMPA, was divided into six phases, including a modified Delphi process. A total of 20 panelists, all of whom were pediatric specialists, participated in administering a comprehensive 38-item questionnaire. The questionnaire was divided into two blocks: Diagnosis and Treatment (20 items each). Results: Consensus was reached on all the proposed items, with an agreement rate of over 70% for each of them. As a result, a diagnostic and treatment algorithm was developed that emphasized the reduction of unnecessary diagnostic studies and encouraged breastfeeding whenever possible. In cases where breast milk is not available, appropriate use of hypoallergenic formulas was recommended. In addition, recommendations on treatment duration and gradual reintroduction of cow’s milk protein were provided. Conclusions: The recommendations endorsed by 20 Mexican pediatricians through this study are applicable to everyday clinical practice, thereby enhancing the diagnosis and treatment of children under 2 years of age with CMPA. This, in turn, will foster improved health outcomes and optimize the utilization of healthcare resources (AU)

Evaluation of ideological and political teaching quality of physiology course for rehabilitation

The development of the information industry is a cross-era impact for any industry, especially under the influence of the database, and the systematic analysis of the data in the industry can improve the accuracy of the output vector and data analysis. With the increase of data volume, for the difficulty of data processing increased significantly, the number of college students growing rapidly in recent years, to the accurate analysis of teachers and students need to take information technology, improve the accuracy of the operation, in the analysis of students and teachers through the system processing education data, the results can be applied to the education management. Based on the above content, on the basis of the dragonfly algorithm, through the improvement of the algorithm, the quality of rehabilitation physiology ideological teaching evaluation, first constructed the course ideological teaching quality evaluation system, then on the basis of determining the evaluation index, the teaching quality evaluation score, in order to through the study of rehabilitation physiology ideological teaching quality to provide reference (AU)

Trends and challenges in implementing sports medicine practices in chilean athletic training

The aim of the research is to determine the trends and challenges related to sports medicine practices in Chilean athletic training. This research examines the state of sports medicine practices in the field of athletic training in Chile, taking a close expression at both international trends and regionally-specific issues. To determine the research, smart PLS software was used and generated informative results, including descriptive statistics and correlation coefficient analysis, which also explains the smart PLS Algorithm model between them. Global trends include the integration of cutting-edge technologies, customized training programs, and an all-encompassing, interdisciplinary approach; however, for successful implementation in Chile, issues including scarce resources, educational disparities, cultural influences, infrastructure needs, and legal considerations must be resolved. The overall research found that direct and significant implementation of sports medicine practices in Chilean athletic training. The study highlights how crucial it is to comprehend and overcome these obstacles to maximize athlete performance and well-being. Sports medicine practices in Chile can progress by practitioners and stakeholders recognizing and adjusting tothe distinct features of the nation's sports ecosystem (AU)

¿Podrían ayudarnos los algoritmos de machine learning en la predicción de hemorragia masiva a nivel prehospitalario? / Could machine learning algorithms help us in predicting massive hemorrhage at the prehospital level?

Objetivo: Comparación de la capacidad predictiva de diferentes algoritmos de machine learning (AML) respecto a escalas tradicionales de predicción de hemorragia masiva en pacientes con enfermedad traumática grave (ETG). Diseño: Sobre una base de datos de una cohorte retrospectiva con variables clínicas prehospitalarias y de resultado de hemorragia masiva se realizó un tratamiento de la base de datos para poder aplicar los AML, obteniéndose un conjunto total de 473 pacientes (80% entrenamiento, 20% validación). Para la modelización se realizó imputación proporcional y validación cruzada. El poder predictivo se evaluó con la métrica ROC y la importancia de las variables mediante los valores Shapley. Ámbito: Atención extrahospitalaria del paciente con ETG. Pacientes: Pacientes con ETG atendidos en el medio extrahospitalario por un servicio médico extrahospitalario desde enero de 2010 hasta diciembre de 2015 y trasladados a un centro de trauma en Madrid. Intervenciones: Ninguna. Variables de interés principales: Obtención y comparación de la métrica ROC de 4 AML: random forest, support vector machine, gradient boosting machine y neural network con los resultados obtenidos con escalas tradicionales de predicción. Resultados: Los diferentes AML alcanzaron valores ROC superiores al 0,85, teniendo medianas cercanas a 0,98. No encontramos diferencias significativas entre los AML. Cada AML ofrece un conjunto de variables diferentes, pero con predominancia de las variables hemodinámicas, de reanimación y de deterioro neurológico. Conclusiones: Los AML podrían superar a las escalas tradicionales de predicción en la predicción de hemorragia masiva. (AU)

Objective: Comparison of the predictive ability of various machine learning algorithms (MLA) versus traditional prediction scales for massive hemorrhage in patients with severe traumatic injury (ETG). Design: On a database of a retrospective cohort with prehospital clinical variables and massive hemorrhage outcome, a treatment of the database was performed to be able to apply the different MLA, obtaining a total set of 473 patients (80% training and 20% validation). For modeling, proportional imputation and cross validation were performed. The predictive power was evaluated with the ROC metric and the importance of the variables using the Shapley values. Setting: Out-of-hospital care of patients with ETG. Participants: Patients with ETG treated out-of-hospital by a prehospital medical service from January 2010 to December 2015 and transferred to a trauma center in Madrid. Interventions: None. Main variables of interest: Obtaining and comparing the ROC curve metric of 4 MLAs: random forest, support vector machine, gradient boosting machine and neural network with the results obtained with traditional prediction scales. Results: The different MLA reached ROC values higher than 0.85, having medians close to 0.98. We found no significant differences between MLAs. Each MLA offers a different set of more important variables with a predominance of hemodynamic, resuscitation variables and neurological impairment. Conclusions: MLA may be helpful in patients with massive hemorrhage by outperforming traditional prediction scales. (AU)

Variaciones en los parámetros cuantitativos y en la puntuación de la escala de Deauville aplicando diferentes algoritmos de reconstrucción en las imágenes PET/TC con [18F]FDG de pacientes con linfoma / The variation of quantitative parameters and Deauville scores with different reconstruction algorithms in FDG PET/CT imaging of lymphoma patients

Objetivos La escala de Deauville (DS) en la tomografía de emisión de positrones (PET) con [18F]fludeoxiglucosa ([18F]FDG) es un método semicuantitativo único para la evaluación del linfoma. Sin embargo, el tipo de algoritmo de reconstrucción empleado para el cálculo de los valores de captación estándar (max, medio y pico) podría afectar a la DS. Comparamos el algoritmo de reconstrucción de probabilidad penalizada bayesiano (BPL) con el de maximización de expectativas de subconjuntos ordenados (OSEM) respecto a los parámetros cuantitativos y en la DS en el linfoma. Investigamos el efecto del tamaño del ganglio linfático sobre la variación cuantitativa. Métodos Se reconstruyeron por separado los resultados de la PET sin procesar de 255 pacientes con linfoma utilizando la aplicación Q.Clear (General Electric Healthcare, Milwaukee, WI, EE. UU.), un algoritmo BPL, y la aplicación SharpIR (General Electric Healthcare, Milwaukee, WI, EE. UU.), un algoritmo OSEM. En ambas imágenes, para cada paciente, se valoró hígado, el pool sanguíneo mediastínico y los valores de captación estándar (SUV) (SUVmáx, SUVmedio y SUVpico) de un total de 487 lesiones seleccionadas. Se compararon DSmáx, DSmedio y DSpico. Resultados En nuestro estudio hubo un aumento significativo de la DS con el BPL (p<0,001) que pasó a una puntuación de 4 a 5 en 30 pacientes inicialmente catalogados como 1-2-3 mediante el algoritmo OSEM. Se observó que los valores cuantitativos de los ganglios linfáticos aumentaban de forma estadísticamente significativa con el BPL (p<0,001), mientras que la disminución de los valores de hígado fue notable respecto a las regiones de referencia (p<0,001). Además, la diferencia en los ganglios linfáticos se asoció de forma independiente con el tamaño de la lesión y fue considerablemente más pronunciada en las lesiones de pequeño tamaño (p<0,001) (AU)

Introduction and Objectives 18F-FDG PET with the Deauville score (DS) is a unique semiquantitative method for lymphoma. However, type of standard uptake values (max, mean, and peak) reconstruction algorithms could affect DS. We compared the Bayesian Penalized Likelihood reconstruction algorithm (BPL) with Ordered Subsets Expectation Maximization (OSEM) on quantitative parameters and DS in lymphoma. We investigated the effect of the size of the lymph node on quantitative variation. Patients and Methods Raw PET data of 255 lymphoma patients were reconstructed separately with Q.Clear (GE Healthcare), a BPL, and SharpIR (GE Healthcare), an OSEM algorithm. In both images, each patient's liver, mediastinal blood pool, and SUVs (SUVmax, SUVmean, and SUVpeak) of a total of 487 lesions selected from the patients were performed. DSmax, DSmean, and DSpeak were compared. Results In our study, DS increased significantly with BPL (p<0.001), and the DS increased to 4-5 in 30 patients evaluated as 1-2-3 with OSEM. It was found that the quantitative values of the lymph nodes increased statistically with BPL (p<0.001), and the liver from the reference regions were significantly decreased (p<0.001). In addition, difference in lymph node was independently associated with size of lesion and was significantly more pronounced in small lesions (p<0.001). The effects of BPL algorithm were more pronounced in SUVmax than in SUVmean and SUVpeak. DS-mean and DS-peak scores were less changed by BPL than DS-max. Conclusion Different reconstruction algorithms in FDG PET/CT affect the quantitative evaluation. That variation may affect the change in DS in lymphoma patients, thus affecting patient management (AU)

Validación externa del algoritmo InShape II para la exclusión de la enfermedad tromboembólica crónica en los pacientes con tromboembolismo pulmonar / External validation of the InShape II study algorithm for exclusion of chronic thromboembolic pulmonary hypertension in patients with pulmonary thromboembolism

Antecedentes y objetivo La complicación a largo plazo más grave del embolismo pulmonar (EP) es la hipertensión pulmonar tromboembólica crónica (HPTEC), cuyo diagnóstico precoz implica la realización de un gran número pruebas. El estudio InShape II propone un algoritmo de cribado precoz que pretende disminuir el número de estudios ecocardiográficos. El objetivo de nuestro estudio es validar este algoritmo en nuestra cohorte de pacientes. Material y métodos Se analizaron retrospectivamente los pacientes ingresados con diagnóstico de EP por angio-TC, en el Hospital Rey Juan Carlos entre noviembre del 2017 y febrero del 2020, seguidos durante al menos un año. Se recogieron datos clínicos, analíticos, y pruebas complementarias a los 3 meses y al año. Se aplicó a estos pacientes el algoritmo del estudio InShape II para validar sus resultados. Resultados En el periodo de estudio fueron diagnosticados de EP 236 pacientes, de los cuales 137 fueron excluidos. Se validó el algoritmo en 99 pacientes. Aplicando el score del InShape II hubiéramos realizado 19 ecocardiogramas (3 de ellos con probabilidad intermedia/alta de HPTEC) y no se hubieran hecho en 80 (2 de ellos con probabilidad intermedia/alta), por lo que se estableció una sensibilidad del score de un 60%, con una especificidad de un 83%, y un área bajo la curva (AUC) de 0,715 (IC 95%: 0,472-0,958). Conclusiones Nuestros resultados apoyan que el algoritmo del estudio InShape II podría ser una herramienta útil en el cribado inicial del estudio de HPTEC en entornos de baja incidencia, ya que evitaría la realización de ecocardiogramas que no aportan valor (AU)

Background and aim The most severe long-term complication of pulmonary embolism (PE) is chronic thromboembolic pulmonary hypertension (CTEPH), and its early diagnosis often requires numerous diagnostic tests. The InShape II study proposes an early screening algorithm that aims to reduce the number of echocardiographic studies. The objective of our study is to validate this algorithm in our patient cohort. Materials and methods We retrospectively analyzed patients admitted to Hospital Rey Juan Carlos between November 2017 and February 2020, who were diagnosed with PE based on computed tomography angiography (CTA). Patients were followed for at least one year, and clinical, laboratory, and complementary test data were collected at three months and one year. The InShape II algorithm was applied to these patients to validate its results. Results During the study period, 236 patients were diagnosed with PE, of which 137 were excluded. The algorithm was validated in 99 patients. Applying the InShape II score, 19 echocardiograms would have been performed (three of them with intermediate-high probability of CTEPH), while 80 echocardiograms would have been avoided (two of them with intermediate-high probability). This yielded a sensitivity of 60% and a specificity of 83% for the score, with an area under the curve (AUC) of 0.715 (95% CI: 0.472-0.958). Conclusions Our results support the notion that the InShape II algorithm could be a useful tool for initial screening of CTEPH in low-incidence settings, as it would avoid unnecessary echocardiograms that do not provide additional value (AU)

Construction of a hepatocytes-related and protein kinase–related gene signature in HCC based on ScRNA-Seq analysis and machine learning algorithm

With recent advancements in single-cell sequencing and machine learning methods, new insights into hepatocellular carcinoma (HCC) progression have been provided. Protein kinase–related genes (PKRGs) affect cell growth, differentiation, apoptosis, and signaling during HCC progression, making the predictive relevance of PKRGs in HCC highly necessary for personalized medicine. In this study, we analyzed single-cell data of HCC and used the machine learning method of LASSO regression to construct PKRG prediction models in six major cell types. CDK4 and AURKB were found to be the best PKRG prognostic signature for predicting the overall survival of HCC patients (including TCGA, ICGC, and GEO datasets) in hepatocytes. Independent clinical factors were further screened out using the COX regression method, and a nomogram combining PKRGs and cancer status was created. Treatment with Palbociclib (CDK4 Inhibitor) and Barasertib (AURKB Inhibitor) inhibited HCC cell migration. Patients classified as PKRG high- or low-risk groups showed different tumor mutation burdens, immune infiltrations, and gene enrichment. The PKRG high-risk group showed higher tumor mutation burdens and gene set enrichment analysis indicated that cell cycle, base excision repair, and RNA degradation pathways were more enriched in these patients. Additionally, the PKRG high-risk group demonstrated higher infiltration levels of Naïve CD8+ T cells, Endothelial cells, M2 macrophage, and Tregs than the low-risk group. In summary, this study established the hepatocytes-related PKRG signature for prognostic stratification at the single-cell level by using machine learning algorithms in HCC and identified potential HCC treatment targets based on the PKRG signature. (AU)

Beneficios del uso de un algoritmo de pruebas recomendadas para el diagnóstico y manejo dietético-nutricional del paciente con trastornos gastrointestinales crónicos / Benefits of using a recommended testing algorithm for the diagnosis and dietary-nutritional management of patients with chronic gastrointestinal disorders

Introducción y objetivo: los trastornos gastrointestinales crónicos como la enfermedad celiaca y la intolerancia a la lactosa o fructosa en la edad adulta son cada vez más frecuentes y se suelen acompañar de sintomatología que repercute en las actividades diarias y limita en gran medida la dieta. El espectro de síntomas que manifiestan los afectados es heterogéneo y poco específico y, además, no existe un protocolo estandarizado y consensuado para el manejo dietético, lo que dificulta un correcto diagnóstico y un adecuado tratamiento. Los trastornos relacionados con malabsorción/intolerancia alimentaria pueden originarse por causas primarias (genéticas) o secundarias (parásitos, alergias, enfermedad inflamatoria intestinal, fármacos, etc.). El empleo de análisis genéticos permite descartar o confirmar causas primarias y, cuando sea necesario, centrar la búsqueda en las secundarias. El objetivo del enfoque algorítmico que proponemos es guiar el manejo dietético-nutricional del paciente con trastornos gastrointestinales crónicos para optimizar el proceso diagnóstico y el tratamiento nutricional. Material y métodos: tras realizar una revisión bibliográfica sobre las patologías más frecuentemente asociadas a estos trastornos, se proponen un algoritmo de pruebas y los sucesivos pasos a seguir en función de los resultados obtenidos, para concretar el diagnóstico y el tratamiento. Resultados: el algoritmo propuesto pretende ser una herramienta para el personal sanitario (gastroenterólogos, endocrinólogos, nutricionistas,etc.) que atiende a este tipo de paciente. Se busca guiar el flujo de pruebas diagnósticas en función de la información aportada por el paciente y la clínica al inicio, así como recomendar el tratamiento (dietético-nutricional y/o farmacológico) más adecuado. Conclusiones: ... (AU)

Introduction and objective: chronic gastrointestinal disorders such as celiac disease and lactose or fructose intolerance in adulthood are becoming more frequent and are usually accompanied by symptoms that affect daily activities and greatly limit diet. The spectrum of symptoms manifested by those affected is heterogeneous and not very specific; in addition, there is no standardized and agreed protocol for dietary management, which makes a correct diagnosis and effective treatment difficult. Disorders related to malabsorption/food intolerance can originate from primary (genetic) or secondary causes (parasites, allergies, inflammatory bowel disease, drugs, etc.). Using genetic data makes it possible to rule out or confirm primary causes, and when necessary, focus the search on secondary ones. The objective of this algorithmic approach is to guide the dietary-nutritional management of the patient with chronic gastrointestinal disease to optimize the diagnostic process and nutritional treatment. Material and methods: after a review of the literature on the pathologies most frequently associated with these disorders, a testing algorithm is proposed and the successive steps to be followed depending on the results obtained, in order to determine the diagnosis and treatment.Results: the proposed algorithm aims to be a tool for health personnel (gastroenterologists, endocrinologists, nutritionists, etc.) who care for these patients. The aim is to guide the flow of diagnostic tests based on the information provided by the patient and the clinic at the beginning, as well as to recommend the most appropriate treatment (dietary-nutritional and/or pharmacological). Conclusions: ... (AU)

Mejora en el manejo de la sospecha del síndrome aórtico agudo en urgencias mediante un algoritmo clínico y el estudio de factores predictivos / Improvement in the management of suspected acute aortic syndrome in the emergency room through a clinical algorithm and study of predictive factors

Antecedentes y objetivo: El síndrome aórtico agudo (SAA) es poco frecuente y difícil de diagnosticar, con una gran variabilidad en su cuadro clínico inicial. Los objetivos son: 1) desarrollar un algoritmo informático, o un sistema de apoyo a las decisiones clínicas (SADC), para el manejo y la solicitud de estudios de diagnóstico por imagen en el servicio de Urgencias, en concreto de una tomografía computarizada (TC) de la aorta, ante la sospecha de SAA, 2) determinar el efecto de la implantación de este sistema, y 3) determinar los factores asociados a un diagnóstico radiológico positivo que mejoren la capacidad predictiva de los hallazgos de la TC de aorta. Material y métodos: Tras desarrollar e implementar un algoritmo basado en la evidencia, se estudiaron casos de sospecha de SAA. Se utilizó el test de la χ2 para analizar la asociación entre las variables incluidas en el algoritmo y el diagnóstico radiológico, con 3 categorías: sin hallazgos relevantes, positivo para SAA y diagnósticos alternativos. Resultados: Se identificaron 130 solicitudes; 19 (14,6%) tenían SAA y 34 (26,2%) tenían otra patología aguda. De las 19 con SAA, 15 habían sido estratificadas como de alto riesgo y 4 como de riesgo intermedio. La probabilidad de SAA era 3,4 veces mayor en los pacientes con aneurisma aórtico conocido (p=0,021, IC del 95%: 1,2-9,6) y 5,1 veces mayor en los pacientes con un soplo de insuficiencia vascular aórtica de novo(p=0,019, IC del 95 %: 1,3-20,1). La probabilidad de tener una enfermedad aguda grave alternativa fue 3,2 veces mayor en los pacientes con hipotensión o choque (p=0,02, IC del 95 %: 1,2-8,5). Conclusión: El uso de un SADC en el servicio de Urgencias puede ayudar a optimizar el diagnóstico del SAA. Se demostró que la presencia de un aneurisma aórtico conocido y de insuficiencia valvular aórtica de nueva aparición aumentan significativamente la probabilidad de SAA. Se necesitan más estudios para establecer una regla de predicción clínica.(AU)

Background and objective: Acute aortic syndrome (AAS) is uncommon and difficult to diagnose, with great variability in clinical presentation. To develop a computerized algorithm, or clinical decision support system (CDSS), for managing and requesting imaging in the emergency department, specifically computerized tomography of the aorta (CTA), when there is suspicion of AAS, and to determine the effect of implementing this system. To determine the factors associated with a positive radiological diagnosis that improve the predictive capacity of CTA findings. Materials and methods: After developing and implementing an evidence-based algorithm, we studied suspected cases of AAS. Chi-squared test was used to analyze the association between the variables included in the algorithm and radiological diagnosis, with 3 categories: no relevant findings, positive for AAS, and alternative diagnoses. Results: 130 requests were identified; 19 (14.6%) had AAS and 34 (26.2%) had a different acute pathology. Of the 19 with AAS, 15 had been stratified as high risk and 4 as intermediate risk. The probability of AAS was 3.4 times higher in patients with known aortic aneurysm (P=.021, 95% CI 1.2–9.6) and 5.1 times higher in patients with a new aortic regurgitation murmur (P=.019, 95% CI 1.3–20.1). The probability of having an alternative severe acute pathology was 3.2 times higher in patients with hypotension or shock (P=.02, 95% CI 1.2–8.5). Conclusion: The use of a CDSS in the emergency department can help optimize AAS diagnosis. The presence of a known aortic aneurysm and new-onset aortic regurgitation were shown to significantly increase the probability of AAS. Further studies are needed to establish a clinical prediction rule.(AU)

Optimización de los tratamientos de la insuficiencia cardiaca con fracción de eyección reducida en la práctica diaria: propuesta de un grupo de expertos / Optimisation of treatments for heart failure with reduced ejection fraction in routine practice: a position statement from a panel of experts

El tratamiento de los pacientes con insuficiencia cardiaca con fracción de eyección reducida (IC-FEr) con una combinación de 4 clases de fármacos se recomienda en las principales guías de práctica clínica internacionales. Sin embargo, no especifican cómo deben introducirse y ajustarse estos tratamientos. En consecuencia, muchos pacientes con IC-FEr no pasan a un régimen de tratamiento optimizado. El objetivo de esta revisión es proponer un algoritmo pragmático para optimizar el tratamiento, diseñado para que sea lo más fácil posible de aplicar en la práctica diaria. El primer objetivo es garantizar que las 4 clases de medicación recomendadas se inicien cuanto antes para establecer una terapia eficaz, incluso a dosis bajas. Esto se considera preferible a iniciar menos medicamentos a una dosis máxima. El segundo objetivo es garantizar que los intervalos entre la introducción de los medicamentos y entre los distintos pasos de titulación sean lo más breves posible, por la seguridad del paciente. Se hacen propuestas específicas para los pacientes de edad avanzada (> 75 años) frágiles, y para aquellos con trastornos del ritmo cardiaco. La aplicación de este algoritmo debería permitir alcanzar un protocolo de tratamiento óptimo en un plazo de 2 meses para la mayoría de los pacientes. Este debe ser nuestro objetivo en el tratamiento de la IC-FEr. (AU)

Major international practice guidelines recommend the use of a combination of 4 medication classes in the treatment of patients with heart failure with reduced ejection fraction (HFrEF) but do not specify how these treatments should be introduced and up-titrated. Consequently, many patients with HFrEF do not receive an optimized treatment regimen. This review proposes a pragmatic algorithm for treatment optimization designed to be easily applied in routine practice. The first goal is to ensure that all 4 recommended medication classes are initiated as early as possible to establish effective therapy, even at a low dose. This is considered preferable to starting fewer medications at a maximum dose. The second goal is to ensure that the intervals between the introduction of different medications and between different titration steps are as short as possible to ensure patient safety. Specific proposals are made for older patients (> 75 years) who are frail, and for those with cardiac rhythm disorders. Application of this algorithm should allow an optimal treatment protocol to be achieved within 2-months in most patients, which should the treatment goal in HFrEF. (AU)

Predicting Positive Repeat Prostate Biopsy Outcomes: Comparison of Machine Learning Approaches to Identify Key Parameters and Optimal Algorithms

Background: Innovative strategies are necessary to enhance prostate cancer diagnosis whilst reducing unnecessary and invasive repeat biopsies. This study aimed to determine the significant parameters affecting repeat prostate biopsy outcomes and develop an optimal machine learning algorithm for predicting positive repeat prostate biopsy results. Methods: We analysed data from 174 men who underwent repeated prostate biopsies between January 2008 and December 2022. Systematic multiple-core, ultrasound-targeted prostate biopsies were performed, each two samples from prostatic transitional zone and peripheral zone were obtained bilaterally. Clinical characteristics were collected, including patients’ age, initial prostate volume, prostate-specific antigen (PSA) level, free PSA (fPSA)/PSA ratio, biopsy core numbers, pathological result; The time interval between first and latest prostate biopsy; Latest PSA level, fPSA/PSA ratio, biopsy core numbers; And final pathological diagnosis. Six feature selection methods, namely, variable ranking, correlation matrix, random forest regression, recursive feature elimination, cross-validation and forward selection, were employed to identify key influencing factors for repeat biopsy outcomes. Subsequently, the performance of seven machine learning algorithms, namely, multivariable logistic regression (LR), K-nearest neighbour search (KNN), support vector classification (SVC), decision tree (DT), random forest classifier (RF), naïve Bayes classifier (NBC) and gradient booster tree (GB), was assessed based on accuracy, misclassification, recall, specificity, precision and receiver operating characteristic (ROC) area under the curve (AUC). About 70% of patients were used as the training dataset, meanwhile remaining 30% as validation dataset. Results: 52 were ultimately diagnosed with prostate cancer following the final pathological examination. The remaining 122 patients were negative (AU)