©The Author(s) 2025.
World J Psychiatry. Nov 19, 2025; 15(11): 108688
Published online Nov 19, 2025. doi: 10.5498/wjp.v15.i11.108688
Published online Nov 19, 2025. doi: 10.5498/wjp.v15.i11.108688
Table 5 Binary logistic regression analysis of risk factors for post-stroke depression
| Factors | β | SE | Wald | P value | Exp (β) | 95%CI |
| Age (years) | -1.023 | 0.686 | 2.223 | 0.136 | 0.359 | 0.094-1.380 |
| Marital status | 0.796 | 0.500 | 2.531 | 0.112 | 2.216 | 0.831-5.906 |
| Education level | 1.718 | 0.862 | 3.969 | 0.046 | 5.574 | 1.028-30.214 |
| Number of comorbid conditions | 0.105 | 0.276 | 0.145 | 0.703 | 1.111 | 0.647-1.907 |
| Severity of neurological impairment | 0.460 | 0.284 | 2.617 | 0.106 | 1.584 | 0.907-2.766 |
| Number of lesions | 0.169 | 0.694 | 0.059 | 0.808 | 1.184 | 0.304-4.615 |
| NLR | 0.780 | 0.207 | 14.175 | < 0.001 | 2.181 | 1.453-3.274 |
| PLR | 0.027 | 0.006 | 19.528 | < 0.001 | 1.028 | 1.015-1.040 |
- Citation: Han Z, Zhang DD, Li NN. Influencing factors and construction of a nomogram for post-stroke depression in patients with chronic stroke. World J Psychiatry 2025; 15(11): 108688
- URL: https://www.wjgnet.com/2220-3206/full/v15/i11/108688.htm
- DOI: https://dx.doi.org/10.5498/wjp.v15.i11.108688