Revista clinica espanola最新文献

英文中文

Comorbilidades autoinmunes en pacientes con esclerosis múltiple. Un estudio basado en la población utilizando inteligencia artificial 多发性硬化症患者的自身免疫并发症。使用人工智能的以人口为基础的研究

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502414

N. García-Alvarado , M.I. Morales-Casado , P. Beneyto-Martín

Introduction

The prevalence of autoimmune comorbidities in patients with multiple sclerosis (MS) has been the subject of numerous epidemiological studies. Due to the presence of biases and the heterogeneity of the publications, this association has not been firmly demonstrated. The aim of our study is to establish the prevalence of autoimmune diseases in MS patients from our region (Castilla-La Mancha, Spain) and to compare it with the prevalence of autoimmune diseases in a non-MS population, in order to strengthen the evidence for an association between MS and other autoimmune conditions.

Patients and methods

We conducted a retrospective, non-interventional, multicenter study analyzing the electronic medical records of 3,309,298 patients in the Castilla-La Mancha area (Spain) using an artificial intelligence system.

Results

The 22.5% of MS patients had at least one other autoimmune disease. Hypothyroidism, followed by type 1 diabetes mellitus and psoriasis, were the three most frequent autoimmune diseases in the MS cohort.

Conclusions

In the present study, we observed an association between most of the autoimmune diseases studied and MS when comparing their prevalence in the MS population versus the non-MS population. Confirmation of these findings could lead to changes in preventive strategies, diagnostic protocols, and therapeutic approaches for MS patients. Large-scale data analysis using artificial intelligence may help resolve epidemiological questions that remain unanswered to date.

多发性硬化症（MS）患者自身免疫性合并症的患病率一直是众多流行病学研究的主题。由于存在偏倚和出版物的异质性，这种关联尚未得到证实。我们研究的目的是建立自身免疫性疾病在我们地区（西班牙Castilla-La Mancha） MS患者中的患病率，并将其与非MS人群中自身免疫性疾病的患病率进行比较，以加强MS与其他自身免疫性疾病之间关联的证据。患者和方法我们进行了一项回顾性、非干预性、多中心研究，使用人工智能系统分析了西班牙Castilla-La Mancha地区3,309,298名患者的电子病历。结果22.5%的MS患者至少有一种其他自身免疫性疾病。甲状腺功能减退，其次是1型糖尿病和牛皮癣，是MS队列中最常见的三种自身免疫性疾病。结论在本研究中，我们通过比较自身免疫性疾病在多发性硬化症人群和非多发性硬化症人群中的患病率，观察到大多数自身免疫性疾病与多发性硬化症之间的关联。这些发现的证实可能导致MS患者预防策略、诊断方案和治疗方法的改变。使用人工智能的大规模数据分析可能有助于解决迄今为止尚未解决的流行病学问题。

{"title":"Comorbilidades autoinmunes en pacientes con esclerosis múltiple. Un estudio basado en la población utilizando inteligencia artificial","authors":"N. García-Alvarado , M.I. Morales-Casado , P. Beneyto-Martín","doi":"10.1016/j.rce.2025.502414","DOIUrl":"10.1016/j.rce.2025.502414","url":null,"abstract":"<div><h3>Introduction</h3><div>The prevalence of autoimmune comorbidities in patients with multiple sclerosis (MS) has been the subject of numerous epidemiological studies. Due to the presence of biases and the heterogeneity of the publications, this association has not been firmly demonstrated. The aim of our study is to establish the prevalence of autoimmune diseases in MS patients from our region (Castilla-La Mancha, Spain) and to compare it with the prevalence of autoimmune diseases in a non-MS population, in order to strengthen the evidence for an association between MS and other autoimmune conditions.</div></div><div><h3>Patients and methods</h3><div>We conducted a retrospective, non-interventional, multicenter study analyzing the electronic medical records of 3,309,298 patients in the Castilla-La Mancha area (Spain) using an artificial intelligence system.</div></div><div><h3>Results</h3><div>The 22.5% of MS patients had at least one other autoimmune disease. Hypothyroidism, followed by type 1 diabetes mellitus and psoriasis, were the three most frequent autoimmune diseases in the MS cohort.</div></div><div><h3>Conclusions</h3><div>In the present study, we observed an association between most of the autoimmune diseases studied and MS when comparing their prevalence in the MS population versus the non-MS population. Confirmation of these findings could lead to changes in preventive strategies, diagnostic protocols, and therapeutic approaches for MS patients. Large-scale data analysis using artificial intelligence may help resolve epidemiological questions that remain unanswered to date.</div></div>","PeriodicalId":21223,"journal":{"name":"Revista clinica espanola","volume":"226 1","pages":"Article 502414"},"PeriodicalIF":1.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145908843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Un ojo más cerrado… y un diagnóstico inesperado 闭上眼睛——一个意想不到的诊断

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502417

M. Moro Muñiz, A. Janicka-Caulineau, D. Salom Alonso

引用次数: 0

Inteligencia artificial generativa: los modelos fundacionales. Procesamiento del lenguaje natural y modelos de lenguaje grandes 生成式人工智能：基础模型。自然语言处理和大型语言模型

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502413

J. Mora-Delgado , L. Ramos-Ruperto , M.J. Pardilla , M.Á. Sicilia , A. Rodríguez-González , J.M. Sempere , R. Puchades

This work aims to provide internists with a practical, focused overview of how generative artificial intelligence (AI) based on large language models can be effectively integrated into daily clinical practice. It describes the primary adaptation mechanisms like fine-tuning and retrieval-augmented generation (RAG) for tasks such as report generation, synthesis of clinical findings, and support in differential diagnoses, highlighting real-world examples in Internal Medicine. Technical and organizational requirements for adoption are analyzed, including computing infrastructure, integration with electronic health records, and security/privacy protocols under GDPR and the EU AI Act. Opportunities for enhancing clinical decision-making, optimizing workflows, and reducing administrative burden are emphasized, alongside current limitations like bias, hallucinations, and the need for human oversight. Finally, recommendations are offered for prospective validation in real-world settings and for ensuring explainable transparency, with the goal of empowering internists to incorporate these innovative tools responsibly and efficiently.

这项工作旨在为内科医生提供一个实用的、有重点的概述，即如何将基于大型语言模型的生成式人工智能（AI）有效地集成到日常临床实践中。它描述了主要的适应机制，如微调和检索增强生成（RAG），用于报告生成、临床发现综合和鉴别诊断支持等任务，突出了内科医学中的实际例子。分析了采用的技术和组织要求，包括计算基础设施、与电子健康记录的集成以及GDPR和欧盟人工智能法案下的安全/隐私协议。强调了加强临床决策、优化工作流程和减轻行政负担的机会，以及当前的局限性，如偏见、幻觉和对人类监督的需求。最后，为在现实环境中进行前瞻性验证和确保可解释的透明度提供了建议，其目标是使内科医生能够负责任和有效地采用这些创新工具。

{"title":"Inteligencia artificial generativa: los modelos fundacionales. Procesamiento del lenguaje natural y modelos de lenguaje grandes","authors":"J. Mora-Delgado , L. Ramos-Ruperto , M.J. Pardilla , M.Á. Sicilia , A. Rodríguez-González , J.M. Sempere , R. Puchades","doi":"10.1016/j.rce.2025.502413","DOIUrl":"10.1016/j.rce.2025.502413","url":null,"abstract":"<div><div>This work aims to provide internists with a practical, focused overview of how generative artificial intelligence (AI) based on large language models can be effectively integrated into daily clinical practice. It describes the primary adaptation mechanisms like fine-tuning and retrieval-augmented generation (RAG) for tasks such as report generation, synthesis of clinical findings, and support in differential diagnoses, highlighting real-world examples in Internal Medicine. Technical and organizational requirements for adoption are analyzed, including computing infrastructure, integration with electronic health records, and security/privacy protocols under GDPR and the EU AI Act. Opportunities for enhancing clinical decision-making, optimizing workflows, and reducing administrative burden are emphasized, alongside current limitations like bias, hallucinations, and the need for human oversight. Finally, recommendations are offered for prospective validation in real-world settings and for ensuring explainable transparency, with the goal of empowering internists to incorporate these innovative tools responsibly and efficiently.</div></div>","PeriodicalId":21223,"journal":{"name":"Revista clinica espanola","volume":"226 1","pages":"Article 502413"},"PeriodicalIF":1.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145908844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning y deep learning en medicina interna: desmitificando conceptos 内科中的机器学习和深度学习：揭秘概念

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502412

L. Ramos-Ruperto , J. Mora-Delgado , A. Rodríguez-González , M.A. Sicilia , M.J. Pardilla , J.M. Sempere , R. Puchades

Machine learning (ML) is a branch of artificial intelligence that is transforming clinical practice by providing tools capable of analyzing large volumes of data, identifying complex patterns, and generating predictions useful for medical decision-making. This article offers a practical and accessible introduction to key ML concepts for internists, addressing its application in tasks such as diagnosis, prognosis, and clinical management. The main types of learning (supervised, unsupervised, and reinforcement learning), the importance of data quality, and the systematic process for developing ML projects in medicine are described. Advanced approaches, such as neural networks and model explainability, are also explored. By integrating these tools, clinicians can improve diagnostic accuracy, personalize treatments, and optimize resources, always with a critical approach that respects medical ethics.

机器学习（ML）是人工智能的一个分支，通过提供能够分析大量数据、识别复杂模式和生成对医疗决策有用的预测的工具，正在改变临床实践。本文为内科医生提供了一个实用的、可访问的ML关键概念的介绍，解决了它在诊断、预后和临床管理等任务中的应用。介绍了学习的主要类型（监督学习、无监督学习和强化学习）、数据质量的重要性以及在医学中开发ML项目的系统过程。先进的方法，如神经网络和模型的可解释性，也进行了探讨。通过整合这些工具，临床医生可以提高诊断准确性、个性化治疗并优化资源，同时始终采用尊重医学伦理的关键方法。

引用次数: 0

De la alfabetización digital a la medicina aumentada: comprender para confiar 从数字素养到增强医学：从理解到信任

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502415

R. Quirós-López , J. Trujillo-Santos

引用次数: 0

Evolución del profesorado acreditado por la ANECA para el Grado de Medicina (2019-2024). Expectativas ante el nuevo modelo de acreditación 由ANECA认证的医学学位教师的演变（2019-2024）。对新认证模式的期望

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502416

J.P. Lara Muñoz , J.A. Vargas Núñez , J.J. García Seoane , A.F. Compañ Rosique

The training required for a Medical Degree requires a sufficient faculty structure to guarantee the acquisition of general practitioner skills. The National Conference of Deans of Spanish Medical Schools (CNDFME) has highlighted the significant faculty shortage, maintaining collaboration with university and healthcare institutions, promoting an increase in accredited faculty, modifications to the accreditation model, and the implementation of new teaching positions.

The evolution of accredited faculty for the Health Sciences Branch (2019-2024) is described: the number of accredited permanent teachers has increased significantly. The modifications to the accreditation processes incorporated in the Organic Law of the University System (LOSU) and the new accreditation model (RD 678/2023) are considered positive in encouraging the best professionals to join the faculty of the Schools of Medicine.

医学学位所需的培训要求有足够的师资结构，以保证获得全科医生的技能。西班牙医学院院长全国会议（CNDFME）强调了教员严重短缺的问题，与大学和保健机构保持合作，促进增加经认证的教员，修改认证模式，并设立新的教学职位。描述了健康科学分部认可教师（2019-2024）的演变：认可的长期教师数量显着增加。大学系统组织法（LOSU）对认证程序的修改和新的认证模式（RD 678/2023）被认为是积极的，鼓励最优秀的专业人员加入医学院的教师队伍。

引用次数: 0

Inteligencia artificial en medicina interna: conocimiento, uso clínico y necesidades formativas 内科中的人工智能：知识、临床应用和培训需求

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502421

J. García Alegría , C. García Tortosa , M.D. Martín Escalante , F. Miralles Linares , R. Puchades-Rincón de Arellano , M.M. Chimeno-Viñas

Background/objective

Artificial intelligence (AI) has been revolutionising medical practice in recent years. The aim of this study was to analyse the perception of self-knowledge, personal experience, degree of use and training needs in AI among Spanish internists who are members of the Spanish Society of Internal Medicine (SEMI) in order to guide their educational activities.

Materials and methods

Cross-sectional study using an anonymous survey with demographic variables, categorical questions, multiple-choice questions, and open-ended qualitative questions. Descriptive analysis with differences between age groups. The minimum estimated sample size of representative members was 368.

Results

Five hundred fourvalid responses were analysed (82% specialists, 16% residents). Self-perceived knowledge of AI was mainly intermediate or basic, with higher levels among those under 30 and lower levels among those over 60. Three out of four respondents had used AI, mainly in clinical practice, followed by research and teaching. The main perceived barriers were lack of specific training, doubts about reliability and ethical-legal issues, as well as technological limitations and resistance to change. The vast majority considered AI training to be important or very important, with particular interest in practical clinical applications, basic fundamentals and tool evaluation. The willingness to incorporate AI into practice was high across all age groups.

Conclusions

Spanish internists have varying levels of knowledge about artificial intelligence, with younger doctors having greater knowledge, and its main current use is in clinical practice. Lack of training is the main barrier to its incorporation, despite high demand for training and a general willingness to adopt it, highlighting the need for training programmes and strategies for integrating AI into internal medicine.

近年来，人工智能（AI）已经彻底改变了医疗实践。本研究的目的是分析西班牙内科医学会（SEMI）成员的西班牙内科医生对人工智能的自我认知、个人经验、使用程度和培训需求，以指导他们的教育活动。材料和方法采用匿名调查的横断面研究，包括人口统计变量、分类问题、多项选择问题和开放式定性问题。年龄组间差异的描述性分析。代表成员的最小估计样本量为368人。结果共收集有效问卷5400份，其中专家82%，居民16%。人工智能自我认知知识以中级或基础知识为主，30岁以下人群认知水平较高，60岁以上人群认知水平较低。四分之三的受访者使用过人工智能，主要用于临床实践，其次是研究和教学。人们认为的主要障碍是缺乏具体的培训、对可靠性的怀疑和道德-法律问题、以及技术限制和对变革的抵制。绝大多数人认为人工智能培训很重要或非常重要，对实际临床应用、基础知识和工具评估特别感兴趣。在所有年龄组中，将人工智能应用于实践的意愿都很高。结论西班牙内科医生对人工智能的了解程度参差不齐，年轻医生对人工智能的了解程度更高，目前人工智能主要应用于临床。缺乏培训是纳入人工智能的主要障碍，尽管对培训的需求很高，而且人们普遍愿意采用它，这突出了将人工智能纳入内科的培训计划和战略的必要性。

{"title":"Inteligencia artificial en medicina interna: conocimiento, uso clínico y necesidades formativas","authors":"J. García Alegría , C. García Tortosa , M.D. Martín Escalante , F. Miralles Linares , R. Puchades-Rincón de Arellano , M.M. Chimeno-Viñas","doi":"10.1016/j.rce.2025.502421","DOIUrl":"10.1016/j.rce.2025.502421","url":null,"abstract":"<div><h3>Background/objective</h3><div>Artificial intelligence (AI) has been revolutionising medical practice in recent years. The aim of this study was to analyse the perception of self-knowledge, personal experience, degree of use and training needs in AI among Spanish internists who are members of the Spanish Society of Internal Medicine (SEMI) in order to guide their educational activities.</div></div><div><h3>Materials and methods</h3><div>Cross-sectional study using an anonymous survey with demographic variables, categorical questions, multiple-choice questions, and open-ended qualitative questions. Descriptive analysis with differences between age groups. The minimum estimated sample size of representative members was 368.</div></div><div><h3>Results</h3><div>Five hundred fourvalid responses were analysed (82% specialists, 16% residents). Self-perceived knowledge of AI was mainly intermediate or basic, with higher levels among those under 30 and lower levels among those over 60. Three out of four respondents had used AI, mainly in clinical practice, followed by research and teaching. The main perceived barriers were lack of specific training, doubts about reliability and ethical-legal issues, as well as technological limitations and resistance to change. The vast majority considered AI training to be important or very important, with particular interest in practical clinical applications, basic fundamentals and tool evaluation. The willingness to incorporate AI into practice was high across all age groups.</div></div><div><h3>Conclusions</h3><div>Spanish internists have varying levels of knowledge about artificial intelligence, with younger doctors having greater knowledge, and its main current use is in clinical practice. Lack of training is the main barrier to its incorporation, despite high demand for training and a general willingness to adopt it, highlighting the need for training programmes and strategies for integrating AI into internal medicine.</div></div>","PeriodicalId":21223,"journal":{"name":"Revista clinica espanola","volume":"226 1","pages":"Article 502421"},"PeriodicalIF":1.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145908834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integración de modelos de lenguaje natural en el diagnóstico de enfermedades autoinmunes sistémicas: validación de GPT-4 en un centro de tercer nivel 将自然语言模型整合到系统性自身免疫性疾病的诊断中：在三级中心进行GPT-4验证

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502418

A. Carrasco Laraña , J. Álvarez Troncoso , J.J. Ríos Blanco

Introduction

Systemic autoimmune diseases (SADs) pose a diagnostic challenge due to the heterogeneity of their manifestations and the frequent overlap of symptoms. The integration of large language models (LLMs), such as GPT-4, could complement clinical judgment through the systematic analysis of standardized clinical data.

Objective

To evaluate the diagnostic capability of GPT-4 in patients with SADs at a tertiary care center, comparing its results with the final consensus diagnosis issued by specialists.

Methods

A retrospective study was conducted on a cohort of 101 consecutively treated patients between January 1 and March 31, 2024, at the SAD Unit of La Paz University Hospital. Data collection was carried out using the unit's standardized anamnesis protocol. The “my GPT” model, based on GPT-4 and trained according to international diagnostic criteria, was evaluated following TRIPOD-AI guidelines.

Results

The overall diagnostic accuracy rate was 97.03%. Analysis based solely on anamnesis data achieved an accuracy of 82.18%, which increased by 14.85% when immunological results were included. A 100% accuracy was achieved in diagnosing systemic lupus erythematosus, Sjögren's syndrome, inflammatory myopathies, Behçet's disease, and scleroderma. In contrast, for sarcoidosis and vasculitis —conditions that often require histological confirmation— accuracy was 91.67% and 80%, respectively.

Conclusion

The use of GPT-4, grounded in systematic clinical data collection and evaluated in accordance with TRIPOD-AI guidelines, demonstrates strong potential as an auxiliary tool in the diagnosis of SADs. Integrating this approach into clinical practice could help reduce interobserver variability and optimize decision-making.

系统性自身免疫性疾病（SADs）由于其表现的异质性和症状的频繁重叠，给诊断带来了挑战。整合大型语言模型（llm），如GPT-4，可以通过对标准化临床数据的系统分析来补充临床判断。目的评价GPT-4对某三级医疗中心SADs患者的诊断能力，并将其结果与专家最终共识诊断结果进行比较。方法对2024年1月1日至3月31日在La Paz大学医院SAD单元连续治疗的101例患者进行回顾性研究。数据收集采用该单位的标准化记忆方案进行。“我的GPT”模型基于GPT-4，并根据国际诊断标准进行训练，根据TRIPOD-AI指南进行评估。结果总诊断率为97.03%。仅基于记忆数据的分析准确率为82.18%，当纳入免疫学结果时，准确率提高了14.85%。诊断系统性红斑狼疮、Sjögren综合征、炎性肌病、behaperet病和硬皮病的准确率达到100%。相比之下，结节病和血管炎（通常需要组织学证实）的准确率分别为91.67%和80%。结论基于系统的临床数据收集，并根据TRIPOD-AI指南进行评估，GPT-4的使用显示出作为SADs诊断辅助工具的强大潜力。将这种方法整合到临床实践中可以帮助减少观察者之间的差异并优化决策。

{"title":"Integración de modelos de lenguaje natural en el diagnóstico de enfermedades autoinmunes sistémicas: validación de GPT-4 en un centro de tercer nivel","authors":"A. Carrasco Laraña , J. Álvarez Troncoso , J.J. Ríos Blanco","doi":"10.1016/j.rce.2025.502418","DOIUrl":"10.1016/j.rce.2025.502418","url":null,"abstract":"<div><h3>Introduction</h3><div>Systemic autoimmune diseases (SADs) pose a diagnostic challenge due to the heterogeneity of their manifestations and the frequent overlap of symptoms. The integration of large language models (LLMs), such as GPT-4, could complement clinical judgment through the systematic analysis of standardized clinical data.</div></div><div><h3>Objective</h3><div>To evaluate the diagnostic capability of GPT-4 in patients with SADs at a tertiary care center, comparing its results with the final consensus diagnosis issued by specialists.</div></div><div><h3>Methods</h3><div>A retrospective study was conducted on a cohort of 101 consecutively treated patients between January 1 and March 31, 2024, at the SAD Unit of La Paz University Hospital. Data collection was carried out using the unit's standardized anamnesis protocol. The “my GPT” model, based on GPT-4 and trained according to international diagnostic criteria, was evaluated following TRIPOD-AI guidelines.</div></div><div><h3>Results</h3><div>The overall diagnostic accuracy rate was 97.03%. Analysis based solely on anamnesis data achieved an accuracy of 82.18%, which increased by 14.85% when immunological results were included. A 100% accuracy was achieved in diagnosing systemic lupus erythematosus, Sjögren's syndrome, inflammatory myopathies, Behçet's disease, and scleroderma. In contrast, for sarcoidosis and vasculitis —conditions that often require histological confirmation— accuracy was 91.67% and 80%, respectively.</div></div><div><h3>Conclusion</h3><div>The use of GPT-4, grounded in systematic clinical data collection and evaluated in accordance with TRIPOD-AI guidelines, demonstrates strong potential as an auxiliary tool in the diagnosis of SADs. Integrating this approach into clinical practice could help reduce interobserver variability and optimize decision-making.</div></div>","PeriodicalId":21223,"journal":{"name":"Revista clinica espanola","volume":"226 1","pages":"Article 502418"},"PeriodicalIF":1.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145908840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impacto de la optimización terapéutica en ancianos pluripatológicos con insuficiencia cardíaca y fracción de eyección reducida 治疗优化对患有心力衰竭和射精率降低的多病症老年人的影响

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2026-01-01 DOI: 10.1016/j.rce.2025.502419

G. Martínez de las Cuevas , C. Baldeón Conde , S. Merino Millán , J.M. Olmos Martínez , J.L. Hernández Hernández , D. Nan

Background

We evaluated the impact of a specialized unit on reducing heart failure (HF) readmissions in elderly patients with multiple comorbidities and HFrEF (LVEF < 40%) or mildly reduced EF (LVEF 40-50%), considering different levels of pharmacological optimization.

Methods

Retrospective analysis of a cohort of 135 patients. Readmission rates and their association with optimized treatment were analyzed.

Results

HF admissions decreased by 51% compared to the previous year (P = .013). Sixty percent received quadruple therapy, and 62-71% at least three drugs. NT-proBNP levels dropped by 70% (P < .001). Quadruple therapy was associated with fewer readmissions at 12 months (P = .036), as were ARNI + BB + MRA (P = .016) and MRA monotherapy (P = .012). The median time to achieve therapeutic optimization was 52 days (27-82 days).

Conclusions

A specialized unit markedly improves therapeutic optimization and reduces readmissions in these patients.

背景：考虑不同水平的药理学优化，我们评估了一个专门的单位对降低老年患者心力衰竭（HF）再入院的影响，这些患者有多种合并症和HFrEF （LVEF < 40%）或轻度降低的EF （LVEF 40-50%）。方法对135例患者进行回顾性分析。分析再入院率及其与优化治疗的关系。结果我院住院人数较上年下降51% （P = 0.013）。60%的患者接受了四种药物治疗，62-71%的患者至少接受了三种药物治疗。NT-proBNP水平下降了70% （P < .001）。四联疗法与12个月时再入院率较低相关（P = 0.036）， ARNI + BB + MRA （P = 0.016）和MRA单药治疗（P = 0.012）也是如此。实现治疗优化的中位时间为52天（27-82天）。结论专科治疗可显著改善该类患者的治疗效果，降低再入院率。

{"title":"Impacto de la optimización terapéutica en ancianos pluripatológicos con insuficiencia cardíaca y fracción de eyección reducida","authors":"G. Martínez de las Cuevas , C. Baldeón Conde , S. Merino Millán , J.M. Olmos Martínez , J.L. Hernández Hernández , D. Nan","doi":"10.1016/j.rce.2025.502419","DOIUrl":"10.1016/j.rce.2025.502419","url":null,"abstract":"<div><h3>Background</h3><div>We evaluated the impact of a specialized unit on reducing heart failure (HF) readmissions in elderly patients with multiple comorbidities and HFrEF (LVEF<40%) or mildly reduced EF (LVEF 40-50%), considering different levels of pharmacological optimization.</div></div><div><h3>Methods</h3><div>Retrospective analysis of a cohort of 135 patients. Readmission rates and their association with optimized treatment were analyzed.</div></div><div><h3>Results</h3><div>HF admissions decreased by 51% compared to the previous year (<em>P</em>  <.001). Quadruple therapy was associated with fewer readmissions at 12months (<em>P</em>    =.016) and MRA monotherapy (<em>P</em>   <!-->days (27-82 days).</div></div><div><h3>Conclusions</h3><div>A specialized unit markedly improves therapeutic optimization and reduces readmissions in these patients.</div></div>","PeriodicalId":21223,"journal":{"name":"Revista clinica espanola","volume":"226 1","pages":"Article 502419"},"PeriodicalIF":1.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145908841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ecografía clínica para la caracterización de la obesidad: más allá del índice de masa corporal 用于肥胖症特征的临床超声：超越身体质量指数

IF 1.7 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Revista clinica espanola

Pub Date : 2025-12-01 DOI: 10.1016/j.rce.2025.502392

J.A. Peregrina Rivas , I.F. Aomar Millán , L.M. Beltrán Romero , L. Castilla Guerra

Obesity is a complex and heterogeneus disease, with metabolic risk that is not solely determined by body mass index. The distribution and functionality of adipose tissue-particularly that of white adipocytes- play a critical role in the development of insulin resistance, chronic inflammation and ectopic lipid deposition. Clinical ultrasound enables direct and reproducible characterization of the major fat compartments (epicardial, hepatic, perirenal, subcutaneous and intramuscular), of preperitoneal fat as an indirect marker of visceral adiposity and muscle mass, thereby overcoming the limitations of traditional anthropometric markers. These measurements have been associated with cardiovascular risk, renal dysfunction, hepatic steatosis, frailty and hospital-related complications, even among individuals with normal weight. Furthermore, ultrasound can be employed to monitor changes in these compartments following therapeutic interventions. Given its accessibility, low cost, and prognostic value, this technique serves as a valuable tool in the comprehensive evaluation of patients with obesity in Internal Medicine settings, contributing to a more precise, individualized and efficient approach to care.

肥胖是一种复杂且异质性的疾病，其代谢风险并不完全由体重指数决定。脂肪组织的分布和功能——尤其是白色脂肪细胞的分布和功能——在胰岛素抵抗、慢性炎症和异位脂质沉积的发展中起着关键作用。临床超声能够直接和可重复地表征腹膜前脂肪的主要脂肪区（心外膜、肝、肾周、皮下和肌肉内），作为内脏脂肪和肌肉质量的间接标记，从而克服了传统人体测量标记的局限性。这些测量结果与心血管风险、肾功能障碍、肝脂肪变性、虚弱和医院相关并发症有关，即使在体重正常的人群中也是如此。此外，超声可用于监测治疗干预后这些隔室的变化。鉴于其可及性、低成本和预后价值，该技术可作为内科环境中肥胖患者综合评估的宝贵工具，有助于更精确、个性化和有效的护理方法。

{"title":"Ecografía clínica para la caracterización de la obesidad: más allá del índice de masa corporal","authors":"J.A. Peregrina Rivas , I.F. Aomar Millán , L.M. Beltrán Romero , L. Castilla Guerra","doi":"10.1016/j.rce.2025.502392","DOIUrl":"10.1016/j.rce.2025.502392","url":null,"abstract":"<div><div>Obesity is a complex and heterogeneus disease, with metabolic risk that is not solely determined by body mass index. The distribution and functionality of adipose tissue-particularly that of white adipocytes- play a critical role in the development of insulin resistance, chronic inflammation and ectopic lipid deposition. Clinical ultrasound enables direct and reproducible characterization of the major fat compartments (epicardial, hepatic, perirenal, subcutaneous and intramuscular), of preperitoneal fat as an indirect marker of visceral adiposity and muscle mass, thereby overcoming the limitations of traditional anthropometric markers. These measurements have been associated with cardiovascular risk, renal dysfunction, hepatic steatosis, frailty and hospital-related complications, even among individuals with normal weight. Furthermore, ultrasound can be employed to monitor changes in these compartments following therapeutic interventions. Given its accessibility, low cost, and prognostic value, this technique serves as a valuable tool in the comprehensive evaluation of patients with obesity in Internal Medicine settings, contributing to a more precise, individualized and efficient approach to care.</div></div>","PeriodicalId":21223,"journal":{"name":"Revista clinica espanola","volume":"225 10","pages":"Article 502392"},"PeriodicalIF":1.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

首页上一页

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

Revista clinica espanola

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀