ABSTRACT
Objective:To analyze the efficacy of the Post-stroke Depression Prediction Scale (DePreS) combined with the Early Symptom Measurement of Post-Stroke Depression-Short Form (ESMPSD-SF) in predicting post stroke depression (PSD).Methods:This study was a cross-sectional survey, using convenience sampling method to select 185 stroke patients admitted to Henan Provincial People′s Hospital from June 2019 to May 2021 as the research subjects. The DePreS, ESMPSD-SF, and general information questionnaire were used to investigate them.Results:The incidence of PSD was 36.76% (68/185). The DePreS and ESMPSD-SF scores in the PSD patients were (6.29 ± 8.77), (33.83 ± 6.78) points, respectively, significantly higher than those in the non-PSD patients (-2.05 ± 5.70), (26.51 ± 5.56) points, with statistically significant differences ( t=7.06, 7.97, both P<0.05). Logistic regression analysis showed that DePreS and ESMPSD-SF scores, marital status, and the number of comorbidities were predictive factors for PSD occurrence ( P<0.05). The AUC of DePreS for diagnosing PSD was 0.777, with an optimal diagnostic point of 2 points, a sensitivity of 59.42%, and a specificity of 80.71%; the AUC of the ESMPSD-SF for diagnosing PSD was 0.792, with an optimal diagnostic point of 28 points, a sensitivity of 78.26%, and a specificity of 74.14%. The sensitivity, specificity, and AUC of DePreS combined with ESMPSD-SF in the diagnosis of PSD were 82.61%, 83.62%, and 0.886, respectively. The differences were statistically significant compared to the AUC evaluated separately by DePreS or ESMPSD-SF ( Z=3.21, 3.49, both P<0.05). Conclusions:The combination of DePreS and ESMPSD-SF had a higher detection efficiency for PSD, and the combination of the two is more suitable for assessing PSD risk in stroke patients.