Association of Cardiovascular-Kidney-Metabolic Overlap with Physical Function and Prognosis in Older Patients with Heart Failure: A Post-hoc Analysis of the FRAGILE-HF and SONIC-HF.

IF 8.4 2区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Taisuke Nakade, Yuya Matsue, Yoshiaki Ikeda, Daichi Maeda, Nobuyuki Kagiyama, Yudai Fujimoto, Hanako Inoue, Tsutomu Sunayama, Taishi Dotare, Kentaro Jujo, Kazuya Saito, Kentaro Kamiya, Hiroshi Saito, Yuki Ogasahara, Emi Maekawa, Masaaki Konishi, Takeshi Kitai, Kentaro Iwata, Hiroshi Wada, Takatoshi Kasai, Hirofumi Nagamatsu, Misako Toki, Kenji Yoshioka, Shin-Ichi Momomura, Tohru Minamino
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Abstract

Aims: The prevalence and impact of cardiovascular, kidney, and metabolic (CKM) overlap on physical function and prognosis in older patients with heart failure (HF) remain unclear. This study aimed to assess the impact of overlapping CKM conditions on physical function and prognosis in older patients with HF.

Methods: This post-hoc analysis of the FRAGILE-HF (main cohort) and SONIC-HF (validation cohort), both prospective multicentre studies, included patients aged ≥65 years who were hospitalised for HF. CKM overlap was defined as the presence of one or more of the following comorbidities: atherosclerotic cardiovascular disease, chronic kidney disease, or type 2 diabetes mellitus. The primary outcome was a composite of all-cause death and HF readmission within 2 years. Physical function was assessed using gait speed, five-time chair stand test (5CST), short physical performance battery (SPPB), and 6-min walk test (6MWT). To validate the prognostic association of CKM overlap, we conducted an external validation using the SONIC-HF cohort, an independent prospective study with identical inclusion criteria.

Results: Of 1,113 patients (mean age: 80±8 years, 58.1% male), 193 (17.3%) had no CKM conditions, 370 (33.2%) had one, and 550 (49.5%) had two or three. A multivariable logistic regression model, adjusted for age, sex, comorbidities, and New York Heart Association functional class, showed that two or three CKM conditions were independently associated with lower physical function (5CST: odds ratio [OR]=1.91, P<0.001; SPPB: OR=1.87, P=0.001; 6MWT: OR=1.84, P=0.003). Kaplan-Meier analysis demonstrated a significant stepwise association between CKM overlap and the primary outcome in both the FRAGILE-HF and SONIC-HF cohorts (Log-rank: P < 0.001). Adjusted Cox analysis demonstrated that the overlapping CKM conditions were associated with the primary outcome, with two or more CKM conditions showing a statistically significant association in the FRAGILE-HF cohort (HR = 1.64, P = 0.003). Similarly, although statistical significance was not reached in the SONIC-HF cohort, a stepwise increase in HR was observed (2-3 CKM conditions: HR = 1.90, 95% CI: 0.97-3.73, P = 0.063).

Conclusion: Older patients with HF who have greater CKM overlap exhibited significantly poorer physical function and prognosis.

老年心力衰竭患者心血管-肾-代谢重叠与身体功能和预后的关系:对脆性心力衰竭和超声心力衰竭的事后分析
目的:老年心力衰竭(HF)患者心血管、肾脏和代谢(CKM)重叠的患病率及其对身体功能和预后的影响尚不清楚。本研究旨在评估重叠CKM条件对老年心衰患者身体功能和预后的影响。方法:这项对FRAGILE-HF(主要队列)和SONIC-HF(验证队列)的事后分析,均为前瞻性多中心研究,纳入了年龄≥65岁因心衰住院的患者。CKM重叠被定义为存在以下一种或多种合并症:动脉粥样硬化性心血管疾病、慢性肾病或2型糖尿病。主要结局是2年内全因死亡和心衰再入院的综合结果。采用步态速度、5次椅站立测试(5CST)、短时间物理性能电池(SPPB)和6分钟步行测试(6MWT)评估身体功能。为了验证CKM重叠与预后的关联,我们使用SONIC-HF队列进行了外部验证,这是一项具有相同纳入标准的独立前瞻性研究。结果:1113例患者(平均年龄80±8岁,男性58.1%)中,无CKM 193例(17.3%),有一种CKM 370例(33.2%),两种或三种CKM 550例(49.5%)。一个校正了年龄、性别、合共病和纽约心脏协会功能分类的多变量logistic回归模型显示,两种或三种CKM状况与较低的身体功能独立相关(5CST:比值比[or]=1.91, p)。结论:CKM重叠较多的老年HF患者身体功能和预后明显较差。
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来源期刊
European journal of preventive cardiology
European journal of preventive cardiology CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
12.50
自引率
12.00%
发文量
601
审稿时长
3-8 weeks
期刊介绍: European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.
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