Unravelling the trajectory of frailty and its influencing factors in elderly patients with coronary heart disease after percutaneous coronary intervention: protocol for a cohort study in China
Introduction Frailty is an important factor affecting the short-term and long-term outcomes of elderly patients with coronary heart disease (CHD) after surgery. Most previous studies only assessed frailty before surgery or at discharge, and there was limited tracking of the occurrence and progressio...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2025-03-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/15/3/e089528.full |
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| Summary: | Introduction Frailty is an important factor affecting the short-term and long-term outcomes of elderly patients with coronary heart disease (CHD) after surgery. Most previous studies only assessed frailty before surgery or at discharge, and there was limited tracking of the occurrence and progression of frailty during hospitalisation and after surgery. This paper describes the trends and influencing factors of frailty in elderly patients with CHD before and 6 months after percutaneous coronary intervention (PCI).Method and analysis The frailty study is an observational, prospective cohort study aiming to recruit patients with CHD over 60 years of age who intend to undergo PCI. This study aims to investigate the evolving trends in frailty among elderly patients who have undergone PCI in the 6 months following hospital discharge. Additionally, the influence of cognitive, behavioural, psychosocial, physiological and biological factors on the trajectory of frailty changes in this population was explored based on the International Classification of Functioning, Disability and Health. There will be 11 data collection points, within 48 hours after admission, at hospital discharge and then monthly for the first 6 months, followed by assessments at 12, 24 and 36 months postdischarge. A general estimation equation will be used to analyse the overall trend of frailty. Growth mixture modelling and latent class growth modelling will both be used to identify distinct frailty trajectories. Univariate and logistic regression analyses will be used to identify predictors of trajectories. The Cox proportional hazard regression model will be employed to explore the relationship between the changing trend of different types of frailty within 6 months after discharge and survival status at 36 months.Ethics and dissemination Ethical approval has been obtained from the Ethics Committee of Guangzhou First People’s Hospital (K-2023-136-01). All findings will be disseminated through publication in peer-reviewed scientific journals and presentation at conferences and stakeholder organisation events. |
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| ISSN: | 2044-6055 |