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Published on: May 22, 2019
Influencing factors and construction of a nomogram for post-stroke depression in patients with chronic stroke
Zheng Han1, Dong-Dong Zhang2, Ni-Ni Li3
1Department of Neurology, Shaanxi Provincial People's Hospital, Xi'an 710068, Shaanxi Province, China.
Background:
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.
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