Objectives: To establish an ADL prediction model for Parkinson’s inpatients as an auxiliary evaluation scheme. Methods: The data of Parkinson’s patients hospitalized in the Department of Neurology of Affiliated Brain Hospital of Guangzhou Medical University from 2019 to 2022, which suited the criteria were collected, and a multiple linear regression model was established with serum total protein, serum albumin, age, BMI and education level as independent variables and BI scores as dependent variables. Results: A total of 95 PD patients were included (mean 70.05 ± 10.87 years): 53 males and 42 females. The correlation analysis showed that the serum total protein (r = 0.398, P < 0.001), serum albumin (r = 0.217, P = 0.035), age (r = -0.434, P < 0.001), BMI (r = 0.269, P = 0.008) were respectively linearly correlated with BI total score, and education level is negatively correlated with BI scores (Kendall’s tau-b = -0.2, P = 0.011). A multiple linear regression model which established with serum total protein, serum albumin, age, BMI and education level as independent variables and BI scores as dependent variables, is statistically significant (F = 9.041, P < 0.001, adjust R2 = 0.3). Conclusion: The ADL multiple linear regression model can be used as an important means to evaluate the ADL ability of PD patients in hospital.
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