Study On The Application Value Of Geriatric Comprehensive Assessment In Poststroke Depression

Aims: To explore the application value of Comprehensive Geriatric Assessment(CGA)in post-stroke depression(PSD).To investigate the correlation between PSD and geriatric assessment,risk analysis and model prediction of poststroke depression.Methods: From August 2021 to August 2022,141 elderly patients aged 60 or above with acute ischemic stroke admitted to the Department of Neurology,Suzhou Hospital Affiliated to Anhui Medical University were selected.They were diagnosed with PSD 1week and 3 months after stroke according to the Diagnostic and Statistical Manual of Mental Disorders.And the severity of depression was assessed by PHQ-9.Chi-square test was used to analyze the differences in morbidity at 1 week and 3 months after stroke,and paired sample t test was used to analyze the differences in PHQ-9 scores at two time points.T test was used to compare the differences of frailty,sleep,nutrition and other related geriatric assessment data in whether PSD occurred at different time periods.Pearson correlation was used to test the correlation between PHQ-9 scores and various indexes of geriatric assessment.The risk factors of depression were screened by stepwise regression.The independent risk factors of depression 1 week and 3 months after stroke were analyzed based on Logistic regression system,and the prediction model of PSD 1week and 3 months after stroke was established.The performance of the model was evaluated by receiver operating characteristic(ROC).Results:(1)141 elderly acute ischemic stroke patients were included,67(47.5%)in the PSD group at 1 week of stroke onset and 61(43.3%)in the PSD group at 3 months.Chisquare test showed no significant difference in the prevalence of PSD between 1 week and 3 months after stroke,χ~2=0.515(P=0.473).According to the paired sample t test,the PHQ-9 score of patients 1 week after stroke was significantly correlated with that of patients 3 months after stroke,and the correlation coefficient was 0.549(P < 0.001),t=5.933(P < 0.001).There was a significant difference in PHQ-9 before and after,t=5.933(P < 0.001).(2)Comparing the differences between the PSD group and the non-PSD group in the comprehensive assessment of aging.There were significant differences in the score of National Institutes of Health Stroke Scale(NIHSS)score,asthenic state,Micronutrition Rating Scale(MNA),Tinetti Scale score,Pittsburgh Sleep Quality Index(PSQI),Social Support Rating Scale(SSRS)score,1 week and 3 months after stroke were significantly different between the PSD group and the non-PSD group Difference(P < 0.05);There were no statistically significant differences in age,BMI,Braden scale,MMSE scale,NRS pain assessment score,home environment score,gender,education level,alcohol consumption,smoking,comorbidity assessment and multidrug assessment(P > 0.05).(3)Pearson correlation analysis: 1 week after stroke,PHQ-9 score was moderately positive correlated with fissility score and PSQI score,and moderately negative correlated with gait score and MNA score;PHQ-9 score was moderately positive correlated with frailty score,and weakly correlated with NIHSS score,PSQI score,gait score,MNA score,NRS pain score,SSRS score,and home environment score at 3 months after stroke.(4)Logistic regression showed that non-minor stroke(OR=2.973,P=0.021),debilitating state(OR=3.363,P=0.019),malnutrition(OR=3.990,P=0.004),balance dysfunction OR risk of falling(OR=5.369,P=0.001),good cognition was an independent risk factor for PSD in the first week after stroke.Good social support(OR=0.318,P=0.011)was associated with improved depression.Non-minor stroke(OR=2.378,P=0.024),fthenic state(OR=3.869,P=0.001),and poor sleep quality(OR=3.311,P=0.003)were independent risk factors for PSD 3 months after stroke.(5)A predictive model of PSD 3 months after stroke was established in hospital:Finally,PSD after 1 week,fasthenic state,sleep state,NIHSS score,nutritional state,gait evaluation and social support were included in the regression forecasting model.The fitting effect was better under the model,and the area under the subject working curve was 0.873(95%CI,0.815-0.931).The optimal threshold sensitivity and specificity were 0.820 and 0.812,respectively.Conclusion: In this study,an effective PSD risk prediction model was established on the basis of CGA assessment,and it was pointed out that frailty,malnutrition,unsteady gait,poor sleep and neurological impairment are important risk factors for PSD,which can help elderly stroke patients identify depression early.