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Background <p>Frailty is common in older adults and significantly increases the risk of multiple medical conditions, yet the temporal progression and interaction of these diseases remain poorly understood. Analyzing disease trajectories alongside comorbidity networks provides a strategy for exploring the temporal patterns and system evolutionary features of diseases. In the current study, we evaluated baseline frailty and systematically identified main disease clusters and death trajectories in a frail population.</p> Method <p>Data from the UK Biobank, including 18,999 individuals classified as frail and 94,995 matched controls selected after propensity score matching, were evaluated. Diagnoses were reclassified into 385 medical conditions and 14 categories of death causes using PhecodeX. Disease trajectory and comorbidity network analyses were conducted to describe the patterns of disease development in the frail population.</p> Results <p>Over a median follow-up of 14.9 years, a phenome-wide association study using Cox regression analysis revealed that individuals with frailty had significantly higher risks for 147 medical conditions and 6 causes of death. Modeling disease pairs and trajectories in combination with comorbidity networks revealed three main disease clusters: musculoskeletal/psychiatric disorders, respiratory/multi-system diseases, and cardiovascular/metabolic diseases, with cardiovascular diseases central in mortality outcomes.</p> Conclusions <p>Individuals with frailty have a greater risk of experiencing various medical conditions and death. These risks often involve multiple interconnected trajectories, highlighting potential targets to prevent further deterioration in health.</p>

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Disease clusters and death trajectories in individuals with frailty: a prospective cohort study from the UK Biobank

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月17日

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  • He Ye,
  • Sisi Liu,
  • Ruyang Zhang,
  • Kunyi Wang,
  • Hangjie Zhu,
  • Mengyuan Liang,
  • Yi Qian,
  • Yang Zhao,
  • Liya Liu

摘要

Background

Frailty is common in older adults and significantly increases the risk of multiple medical conditions, yet the temporal progression and interaction of these diseases remain poorly understood. Analyzing disease trajectories alongside comorbidity networks provides a strategy for exploring the temporal patterns and system evolutionary features of diseases. In the current study, we evaluated baseline frailty and systematically identified main disease clusters and death trajectories in a frail population.

Method

Data from the UK Biobank, including 18,999 individuals classified as frail and 94,995 matched controls selected after propensity score matching, were evaluated. Diagnoses were reclassified into 385 medical conditions and 14 categories of death causes using PhecodeX. Disease trajectory and comorbidity network analyses were conducted to describe the patterns of disease development in the frail population.

Results

Over a median follow-up of 14.9 years, a phenome-wide association study using Cox regression analysis revealed that individuals with frailty had significantly higher risks for 147 medical conditions and 6 causes of death. Modeling disease pairs and trajectories in combination with comorbidity networks revealed three main disease clusters: musculoskeletal/psychiatric disorders, respiratory/multi-system diseases, and cardiovascular/metabolic diseases, with cardiovascular diseases central in mortality outcomes.

Conclusions

Individuals with frailty have a greater risk of experiencing various medical conditions and death. These risks often involve multiple interconnected trajectories, highlighting potential targets to prevent further deterioration in health.