Predicting recovery is TOTALLY FUCKING USELESS! Survivors' want you to deliver recovery! When will you do that?
The heterogeneous life space trajectories and predictors in stroke patients: a cohort study
Bei Yang
Rui Xie2†
Ruixue Tang
Yin Wang- 1Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- 2School of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, China
Objective: This study aimed to identify heterogeneous trajectories of life space among stroke patients and explore the predictors for different classes of life space.
Methods: This prospective cohort study assessed 210 stroke patients’ life space at baseline and 1, 3, 6 months post-discharge. We elucidated heterogeneous trajectories of life space by latent class growth model and explored the predictors of trajectories by multinomial logistic regression analysis.
Results: Among 173 participants completing the 6-month follow-up, three distinct life space trajectories were identified: the “high-level recovery flat class” (8%), the “medium-level recovery good class” (72%), and the “low-level recovery poor class” (20%). Multinomial logistic regression, using the low-level recovery poor class as the reference, indicated that age <60, absence of limb sensory deficit, and positive environmental experiences were predictors of the medium-level recovery good class, whereas employment status and positive environmental experiences were predictors of the high-level recovery flat class.
Conclusion: The three trajectories of life space indicated that the 1 month post-discharge is the most vulnerable phase for stroke patients. Age and employment status significantly influence life space trajectories. Patients in the low-level recovery poor class should receive special attention. Strategies to improve sensory deficits and environmental experiences should be developed to expand life space, promoting stroke patients’ rehabilitation.
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