Razjouyan Javad, Tofighi Saeed, Orkaby Ariela R, Bozkurt Biykem, Sharafkhaneh Amir, Horstman Molly J, Goyal Parag, Amos Christopher I, Intrator Orna, Naik Aanand D
VA HSR&D, Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas, USA; Department of Medicine, Baylor College of Medicine, Houston, Texas, USA; Big Data Scientist Training Enhancement Program, VA Office of Research and Development, Washington, District of Columbia, USA.
Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran.
JACC Adv. 2025 May;4(5):101751. doi: 10.1016/j.jacadv.2025.101751.
Frailty is a syndrome associated with increased vulnerability and diminished physiological reserves. Three-quarters (78%) of heart failure (HF) patients are frail. Traditional frailty indices (FIs) assess cross-sectional deficits, while frailty trajectories (FTs) measure changes over time.
This study aims to examine the interaction between FI and FT to enhance risk stratification in hospitalized adults with HF.
This retrospective cohort study utilized data from the Veterans Health Administration, including 143,687 veterans aged >50 admitted for HF from 2005 to 2019. FT measurements were derived from FI calculations for each of the 3 years before index hospitalization. Unsupervised clustering identified 4 clusters based on FI and FT interactions: low-low, low-high, high-low, and high-high. Associations between these clusters and clinical outcomes (ie, 1-year mortality, prolonged hospital stays, emergency department visits, and readmissions) were analyzed.
The study cohort was mostly older (mean age 74 ± 10 years), male (98%), and diverse (55% non-Hispanic White). Survival analysis showed distinct mortality risks across clusters; while the 2 clusters with low FI had the longest survival, the high-high group had the lowest survival probability. Adjusted logistic regression indicated that the high-high cluster had over twice the odds of 1-year mortality compared to the low-low cluster (OR: 2.29; 95% CI: 2.15-2.44). The high-high cluster also had significantly higher rates of prolonged hospital stays, emergency department visits, and readmissions at 30 and 90 days postdischarge.
Integrating cross-sectional FI and longitudinal FT offers a comprehensive assessment of frailty in HF patients, improving risk stratification and disease management.
衰弱是一种与易损性增加和生理储备减少相关的综合征。四分之三(78%)的心力衰竭(HF)患者存在衰弱。传统的衰弱指数(FI)评估横断面缺陷,而衰弱轨迹(FT)则衡量随时间的变化。
本研究旨在探讨FI与FT之间的相互作用,以加强对住院成年HF患者的风险分层。
这项回顾性队列研究利用了退伍军人健康管理局的数据,包括2005年至2019年因HF入院的143687名年龄大于50岁的退伍军人。FT测量值来自于指数住院前3年中每年的FI计算。无监督聚类根据FI和FT的相互作用确定了4个聚类:低-低、低-高、高-低和高-高。分析了这些聚类与临床结局(即1年死亡率、住院时间延长、急诊科就诊和再入院)之间的关联。
研究队列大多为老年人(平均年龄74±10岁),男性(98%),且种族多样(55%为非西班牙裔白人)。生存分析显示各聚类的死亡风险不同;FI较低的两个聚类生存时间最长,而高-高聚类的生存概率最低。校正后的逻辑回归表明,与低-低聚类相比,高-高聚类1年死亡率的比值比高出两倍多(OR:2.29;95%CI:2.15-2.44)。高-高聚类在出院后30天和90天的住院时间延长、急诊科就诊和再入院率也显著更高。
整合横断面FI和纵向FT可对HF患者的衰弱情况进行全面评估,改善风险分层和疾病管理。