BMC cardiovascular disorders · 2025
Analysis of potential categories of quality of life of transcatheter aortic valve replacement patients and discussion of their influencing factors.
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Tang Mingming, Wang Dongmei, Xue Fang, Chen Yongxia, Zhang Nana, Wang Jun, Zhao Peng, Zhou Tong
Аннотация
BACKGROUND: The prevalence of aortic valve stenosis is on the rise, primarily due to an aging population. Transcatheter Aortic Valve Replacement (TAVR) has emerged as an effective treatment option, especially for patients at high surgical risk. However, the variation in post-TAVR quality of life across patient groups warrants further examination to understand the contributing factors.
OBJECTIVE: This study aims to evaluate the quality of life in patients post-TAVR, characterize distinct patient group profiles, and identify key factors that influence their quality of life.
METHODS: From July 2023 to September 2024, 215 TAVR patients were recruited via convenience sampling. Data on sociodemographics and quality of life were gathered using the TAVR-specific quality of life scale. Latent variable growth modeling helped identify quality of life categories and predict influencing factors.
RESULTS: Three categories of TAVR patients were identified based on quality of life: the "High quality of life-high health status" group, the "Medium quality of life-intermediate health" group, and the "Low quality of life-low health status" group. Logistic regression analysis revealed that sleep quality, self-efficacy, and performance on the 30-s chair sit-to-stand test were significant predictors of quality of life.
CONCLUSION: There is considerable variability in the quality of life among TAVR patients. Tailored health management strategies based on specific patient profiles can potentially improve outcomes in these populations.
OBJECTIVE: This study aims to evaluate the quality of life in patients post-TAVR, characterize distinct patient group profiles, and identify key factors that influence their quality of life.
METHODS: From July 2023 to September 2024, 215 TAVR patients were recruited via convenience sampling. Data on sociodemographics and quality of life were gathered using the TAVR-specific quality of life scale. Latent variable growth modeling helped identify quality of life categories and predict influencing factors.
RESULTS: Three categories of TAVR patients were identified based on quality of life: the "High quality of life-high health status" group, the "Medium quality of life-intermediate health" group, and the "Low quality of life-low health status" group. Logistic regression analysis revealed that sleep quality, self-efficacy, and performance on the 30-s chair sit-to-stand test were significant predictors of quality of life.
CONCLUSION: There is considerable variability in the quality of life among TAVR patients. Tailored health management strategies based on specific patient profiles can potentially improve outcomes in these populations.