Influencing factors and construction of a nomogram for post-stroke depression in patients with chronic stroke.
Zheng Han, Dong-Dong Zhang, Ni-Ni Li
Abstract
Open AccessBACKGROUND: Post-stroke depression (PSD), a condition commonly developed in patients with chronic stroke, impairs both functional rehabilitation and daily living. AIM: To comprehensively analyze PSD contributors in chronic phase stroke and construct a precise nomogram. METHODS: Two hundred patients with chronic stroke admitted in over 7 years (January 2017 to January 2024), were enrolled and categorized into the PSD group (n = 96) and the non-PSD (NPSD) group (n = 104). Demographic characteristics, clinicopathological data, and biochemical indicators were collected and analyzed by univariate analysis. Significant predictors identified in the univariate analysis were subsequently incorporated into a binary logistic regression model to assess their independent effects on PSD risk. The discriminative ability/calibration of the developed PSD prediction nomogram was assessed. RESULTS: Compared with the NPSD group, the PSD group included a higher proportion of patients aged ≥ 60 years, divorced/widowed, with an education level below senior high school, presenting with ≥ 2 comorbidities, exhibiting severe neurological impairment, and having multiple lesions. Additionally, the PSD group showed significantly higher neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) than the NPSD group. After assigning values to significant predictors, multivariate analysis indicated that educational level (P = 0.046), NLR (P < 0.001), and PLR (P < 0.001) were independently associated with PSD in patients with chronic stroke. The developed nomogram exhibited favorable discrimination performance. The nomogram's calibration remained accurate for high-risk stratification but displayed modest inconsistencies in low- and middle-risk categories. CONCLUSION: Education level, NLR, and PLR independently contribute to PSD in patients with chronic stroke. The constructed nomogram effectively predicts PSD risk within the range of 0.10-0.90, presenting a valuable tool for clinical monitoring and risk assessment of PSD in patients with chronic stroke.