Abstract: Objective: To clarify latent classes and their influencing factors of frailty trajectories in geriatric patients with Acute Myocardial Infarction (AMI) after discharge, and to provide references for precise prevention and scientific management of frailty in the geriatric. Methods: A convenience sampling method was used to select geriatric patients with first-diagnosis AMI in the chest pain center ward of a tertiary grade A hospital in Shandong from May 2023 to May 2024 as the survey subjects. The FRAIL scale was used to assess frailty at discharge, 1 month, 3 months, and 6 months after discharge. The Latent Class Growth Model was used to identify trajectories, and Logistic regression was used to analyze the influencing factors of trajectories. Results: A total of 226 patients with AMI completed all follow-up surveys, and three different frailty trajectories were identified: the low-level stable group (36.7%), the medium-level slow-declining group (50.0%), and the high-level declining group (13.3%). Logistic regression analysis results showed that age, educational level, anxiety, social support level, white blood cells level, N-terminal natriuretic peptide precursor level, and hemoglobin level were influencing factors for patients' frailty trajectories (P<0.05). Conclusion: Geriatric patients with AMI show different frailty trajectories after discharge. Nurses should develop intervention plans based on different trajectories, stages, and influencing factors to achieve precise and continuous care.

Key words: Acute Myocardial Infarction; trajectory of frailty; longitudinal study; Latent Class Growth Model; influencing factor