Revista espanola de cardiologia最新文献

英文中文

Muerte súbita en un niño con hipercolesterolemia familiar homocigota y cardiomiopatía no compactada. ¿Es solo una coincidencia? 患有家族性同型高胆固醇血症和非致密性心肌病的儿童突然死亡。这只是一个巧合吗？

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-04-02 DOI: 10.1016/j.recesp.2025.01.020

Daiana Ibarretxe-Guerediaga , Cristina Marimón , Albert Feliu , Cèlia Rodríguez-Borjabad , Núria Plana , Lluís Masana

引用次数: 0

Ecocardiografía avanzada y análisis de conglomerados para identificar fenogrupos de insuficiencia tricuspídea secundaria con diferente riesgo 高级超声心动图和聚类分析，以识别具有不同风险的继发性三足功能不全的表型群

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-28 DOI: 10.1016/j.recesp.2025.02.005

Luigi P. Badano , Marco Penso , Michele Tomaselli , Kyu Kim , Alexandra Clement , Noela Radu , Geu-Ru Hong , Diana R. Hădăreanu , Alexandra Buta , Caterina Delcea , Samantha Fisicaro , Gianfranco Parati , Chi Young Shim , Denisa Muraru

Introduction and objectives

Significant secondary tricuspid regurgitation (STR) is associated with poor prognosis, but its heterogeneity makes predicting patient outcomes challenging. Our objective was to identify STR prognostic phenogroups.

Methods

We analyzed 758 patients with moderate-to-severe STR: 558 (74 ± 14 years, 55% women) in the derivation cohort and 200 (73 ± 12 years, 60% women) in the external validation cohort. The primary endpoint was a composite of heart failure hospitalization and all-cause mortality.

Results

We identified 3 phenogroups. The low-risk phenogroup (2-year event-free survival 80%, 95%CI, 74%-87%) had moderate STR, preserved right ventricular (RV) size and function, and a moderately dilated but normally functioning right atrium. The intermediate-risk phenogroup (HR, 2.20; 95%CI, 1.44-3.37; P < .001) included older patients with severe STR, and a mildly dilated but uncoupled RV. The high-risk phenogroup (HR, 4.67; 95%CI, 3.20-6.82; P < .001) included younger patients with massive-to-torrential tricuspid regurgitation, as well as severely dilated and dysfunctional RV and right atrium. Multivariable analysis confirmed the clustering as independently associated with the composite endpoint (HR, 1.40; 95%CI, 1.13-1.70; P = .002). A supervised machine learning model, developed to assist clinicians in assigning patients to the 3 phenogroups, demonstrated excellent performance both in the derivation cohort (accuracy = 0.91, precision = 0.91, recall = 0.91, and F1 score = 0.91) and in the validation cohort (accuracy = 0.80, precision = 0.78, recall = 0.78, and F1 score = 0.77).

Conclusions

The unsupervised cluster analysis identified 3 risk phenogroups, which could assist clinicians in developing more personalized treatment and follow-up strategies for STR patients.

重要的继发性三尖瓣反流（STR）与不良预后相关，但其异质性使得预测患者预后具有挑战性。我们的目的是确定STR预后表型。方法对758例中重度STR患者进行分析：衍生队列558例（74±14岁，55%为女性），外部验证队列200例（73±12岁，60%为女性）。主要终点是心力衰竭住院和全因死亡率的综合。结果共鉴定出3个表型组。低风险表型组（2年无事件生存率80%，95%CI, 74%-87%）有中度STR，保留右心室（RV）大小和功能，中度扩张但功能正常的右心房。中危表型组（HR, 2.20; 95%CI, 1.44-3.37; P < .001）包括严重STR的老年患者和轻度扩张但未耦合的RV。高危表型组（HR, 4.67; 95%CI, 3.20-6.82; P < .001）包括年轻的三尖瓣大量到剧烈反流的患者，以及严重扩张和功能不全的右心室和右心房。多变量分析证实聚类与复合终点独立相关（HR, 1.40; 95%CI, 1.13-1.70; P = 0.002）。为了帮助临床医生将患者分配到3个表型组，开发了一个监督机器学习模型，该模型在衍生队列（准确性= 0.91，精度= 0.91，召回率= 0.91，F1评分= 0.91）和验证队列（准确性= 0.80，精度= 0.78，召回率= 0.78，F1评分= 0.77）中都表现出色。结论无监督聚类分析确定了3个风险表型，有助于临床医生为STR患者制定更个性化的治疗和随访策略。

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引用次数: 0

Diferencias de sexo en pacientes sometidos a recambio valvular aórtico: una historia de dos corazones 主动脉瓣置换术患者的性别差异：两颗心脏的故事

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-28 DOI: 10.1016/j.recesp.2025.01.014

Giovanni Occhipinti , Andrea Alberto Ruberti , Jorge Alcocer , Marc Giménez-Mila , Bárbara Vidal , Ander Regueiro

引用次数: 0

La continuidad asistencial en atención primaria se asocia a un mejor pronóstico de los pacientes remitidos a un servicio de cardiología 初级保健的连续性与转诊到心脏病科的患者的预后改善有关

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-28 DOI: 10.1016/j.recesp.2025.03.009

Sergio Cinza-Sanjurjo , Pilar Mazón-Ramos , Daniel Rey-Aldana , Alfonso Varela-Román , Manuel Portela-Romero , José R. González-Juanatey

Introduction and objectives

To analyze the relationship between continuity of care in primary care and hospitalizations and mortality among patients referred from primary care to a cardiology service.

Methods

Continuity of care was assessed using 3 measures: a) whether the referral was made by the patient's regular family medicine physician (FMP) or a different FMP, b) FMP turnover within a patient panel, and c) turnover of the referring FMP among different patient panels. The association between continuity of care and hospitalizations and mortality was assessed using a multivariate analysis, with adjustment for potential confounding variables. The results are expressed as odds ratios (OR) with 95% confidence intervals (95%CI).

Results

A total of 67 889 patients, referred from 2010 to 2023, were included, of whom 80.5% were referred by their FMP. Patients referred by an FMP other than their own had a higher annual referral rate (2.3 [2.9]) vs 1.5 [0.6]); P < .001) and were assigned to panels with a higher referral rate (10.5 [12.7] vs 1.6 (1.1]; P < .001). Patients referred by their FMP had a lower risk of overall hospitalizations (OR, 0.90; 95%CI, 0.86-0.94), hospitalizations for cardiovascular causes (OR, 0.88; 95%IC, 0.82-0.95), all-cause mortality (OR, 0.84; 95%CI, 0.80-0.89), cardiovascular-related mortality (OR, 0.86; 95%CI, 0.78-0.96), and heart failure-related mortality (OR, 0.77; 95%CI, 0.66-0.89).

Conclusions

Continuity of care, measured by the persistence of the FMP within the same patient panel, improves health outcomes by reducing hospitalizations and mortality, as well as the number of cardiology service referrals.

前言和目的分析初级保健护理连续性与从初级保健转到心脏病科服务的患者住院和死亡率之间的关系。方法采用3个指标评估护理的连续性：a)是否由患者的常规家庭医学医生（FMP）或不同的FMP进行转诊，b) FMP在患者小组内的更替，c)转诊FMP在不同患者小组之间的更替。使用多变量分析评估护理连续性与住院和死亡率之间的关系，并对潜在的混杂变量进行调整。结果以95%置信区间（95% ci）的优势比（OR）表示。结果2010 - 2023年共纳入67 889例患者，其中80.5%是通过FMP转诊的。由非自己的FMP转诊的患者有更高的年转诊率（2.3 [2.9]vs 1.5 [0.6]）；P < .001)，并被分配到转诊率较高的小组(10.5 [12.7]vs 1.6 （1.1]; P < .001）。通过FMP转诊的患者总体住院（OR, 0.90; 95%CI, 0.86-0.94）、心血管原因住院（OR, 0.88; 95%CI, 0.82-0.95）、全因死亡率（OR, 0.84; 95%CI, 0.80-0.89）、心血管相关死亡率（OR, 0.86; 95%CI, 0.78-0.96）和心力衰竭相关死亡率（OR, 0.77; 95%CI, 0.66-0.89）的风险较低。结论：通过FMP在同一组患者中的持续性来衡量的护理连续性，通过减少住院和死亡率以及心脏病服务转诊的数量来改善健康结果。

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引用次数: 0

Prevención cardiovascular primaria y secundaria en los ciclos vitales de la mujer. Documento de consenso de la SEC-GT ECV en la Mujer, ACP-SEC, SEGO, AEEM, SEEN, semFYC, SEMERGEN, AEP y AEM 妇女生命周期的一级和二级心血管预防。SEC-GT - ECV关于妇女、ACP-SEC、SEGO、EEM、SEEN、SEMERGEN、AEP和AEM的共识文件

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-21 DOI: 10.1016/j.recesp.2025.01.015

Antonia Sambola , Raquel Campuzano , Almudena Castro , María Goya , Pluvio Coronado , Rosa Fernández-Olmo , Miguel Ángel María-Tablado , Carolina Ortiz-Cortés , Xènia Ortolà , Vicente Pallarés-Carratalá , Antonia Pijuan-Domenech , Rosa M. Plata , Rosa María Sánchez-Hernández , José Manuel Siurana , Càtia Timoteo , Begoña Viejo-Hernández

This consensus document on cardiovascular disease in women summarizes the views of a panel of experts organized by the Working Group on Women and Cardiovascular Disease of the Spanish Society of Cardiology (SEC-GT CVD in Women), and the Association of Preventive Cardiology of the SEC (ACP-SEC). The document was developed in collaboration with experts from various Spanish societies and associations: the Spanish Society of Gynecology and Obstetrics (SEGO), the Spanish Society of Endocrinology and Nutrition (SEEN), the Spanish Association for the Study of Menopause (AEEM), the Spanish Association of Pediatrics (AEP), the Spanish Society of Primary Care Physicians (SEMERGEN), the Spanish Society of Family and Community Medicine (semFYC), and the Spanish Association of Midwives (AEM). The document received formal approval from the SEC. This consensus serves as a guide for the clinical community on the diagnostic approach and management of cardiovascular health during the stages or life cycles of women: adolescence, the menopausal transition, postpartum disorders, and other gynecologic conditions. It is based on current evidence and best available practices.

这份关于妇女心血管疾病的共识文件总结了由西班牙心脏病学会妇女和心血管疾病工作组（SEC- gt CVD in women）和美国预防心脏病学会（ACP-SEC）组织的一个专家小组的观点。该文件是与来自西班牙各学会和协会的专家合作制定的：西班牙妇产科学会（SEGO）、西班牙内分泌与营养学会（SEEN）、西班牙更年期研究协会（AEEM）、西班牙儿科协会（AEP）、西班牙初级保健医师协会（SEMERGEN）、西班牙家庭和社区医学学会（semFYC）和西班牙助产士协会（AEM）。该文件已获得美国证券交易委员会的正式批准。该共识可作为临床社区在女性各阶段或生命周期（青春期、绝经期过渡、产后疾病和其他妇科疾病）心血管健康诊断方法和管理的指南。它以现有证据和最佳可得做法为基础。

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引用次数: 0

Juan José Rufilanchas Sánchez 胡安·何塞·鲁菲兰查斯·桑切斯

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-21 DOI: 10.1016/j.recesp.2025.03.007

José Luis Pomar

引用次数: 0

Fibrilación auricular e infarto de miocardio: una relación bidireccional con más preguntas que respuestas 心房颤动与心肌梗死：双向关系，问题多于答案

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-21 DOI: 10.1016/j.recesp.2025.02.025

Alfredo Bardají, Gabriel Martín, Sandra Cabrera

引用次数: 0

Arteriolovenular anastomosis Arteriolovenular融合

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-21 DOI: 10.1016/j.recesp.2025.03.005

引用次数: 0

Preservación apical en el ecocardiograma de esfuerzo por sospecha de amiloidosis cardiaca 怀疑有心脏淀粉样变的力量超声心动图的顶端保存

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-21 DOI: 10.1016/j.recesp.2025.01.017

Jesús Peteiro , Marina Combarro , Gonzalo Barge-Caballero , Alberto Bouzas-Mosquera , José Larrañaga-Moreira , José M. Vázquez-Rodríguez

引用次数: 0

Predicción de la mortalidad intrahospitalaria mediante aprendizaje automático y validación externa en pacientes con shock cardiogénico: la escala RESCUE 通过自动学习和外部验证预测心源性休克患者的医院内死亡率：RESCUE量表

IF 5.9 2区医学 Q2 Medicine

Revista espanola de cardiologia

Pub Date : 2025-03-21 DOI: 10.1016/j.recesp.2025.01.003

Ji Hyun Cha , Ki Hong Choi , Chul-Min Ahn , Cheol Woong Yu , Ik Hyun Park , Woo Jin Jang , Hyun-Joong Kim , Jang-Whan Bae , Sung Uk Kwon , Hyun-Jong Lee , Wang Soo Lee , Jin-Ok Jeong , Sang-Don Park , Taek Kyu Park , Joo Myung Lee , Young Bin Song , Joo-Yong Hahn , Seung-Hyuk Choi , Hyeon-Cheol Gwon , Jeong Hoon Yang

Introduction and objectives

Despite advances in mechanical circulatory support, mortality rates in cardiogenic shock (CS) remain high. A reliable risk stratification system could serve as a valuable guide in the clinical management of patients with CS. This study aimed to develop and externally validate a risk prediction model for in-hospital mortality in CS patients using machine learning (ML) algorithms.

Methods

Data from 1247 patients with all-cause CS in the RESCUE registry (January 2014-December 2018) were analyzed. Key predictive variables were identified using 4 ML algorithms. A risk prediction model, the RESCUE score, was developed using logistic regression based on the selected variables. Internal validation was conducted within the RESCUE registry, and external validation was performed using an independent CS registry of 750 patients.

Results

The 4 ML models identified 7 predictors: age, vasoactive inotropic score, left ventricular ejection fraction, lactic acid level, in-hospital cardiac arrest at presentation, need for continuous renal replacement therapy, and mechanical ventilation. The RESCUE score demonstrated strong predictive performance, with an AUC of 0.86 (95%CI, 0.83-0.88) for in-hospital mortality. Ten-fold internal cross-validation yielded an AUC of 0.86 (95%CI, 0.77-0.95). External validation showed an AUC of 0.80 (95%CI, 0.76-0.84).

Conclusions

Our ML-based risk-scoring system, the RESCUE score, demonstrated excellent predictive performance for in-hospital mortality in all patients with CS, regardless of cause. The system could be a useful and reliable tool to estimate risk stratification of CS in everyday clinical practice. Clinical trial registration: NCT02985008.

尽管机械循环支持技术有所进步，但心源性休克（CS）的死亡率仍然很高。一个可靠的风险分层系统可以为CS患者的临床管理提供有价值的指导。本研究旨在利用机器学习（ML）算法开发并外部验证CS患者住院死亡率的风险预测模型。方法分析2014年1月至2018年12月RESCUE登记的1247例全因CS患者的数据。使用4ml算法确定关键预测变量。基于所选变量，采用logistic回归建立了风险预测模型，即RESCUE评分。内部验证在RESCUE注册中心进行，外部验证使用750名患者的独立CS注册中心进行。结果4 ML模型确定了7个预测因素：年龄、血管活性肌力评分、左心室射血分数、乳酸水平、住院时心脏骤停、是否需要持续肾脏替代治疗和机械通气。RESCUE评分显示出很强的预测性能，对院内死亡率的AUC为0.86 （95%CI, 0.83-0.88）。10倍内部交叉验证的AUC为0.86 （95%CI, 0.77-0.95）。外部验证显示AUC为0.80 （95%CI, 0.76-0.84）。结论基于ml的风险评分系统RESCUE评分对所有CS患者的院内死亡率均具有出色的预测效果，无论其原因如何。该系统可作为日常临床实践中评估CS风险分层的有效、可靠的工具。临床试验注册：NCT02985008。

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