Abstract
BackgroundPost-stroke depression (PSD) is a frequent complication that worsens rehabilitation outcomes and patient quality of life. This study developed a risk prediction model for PSD based on patient clinical and socio-psychology features for the early detection of high risk PSD patients.ResultsRisk predictors included a history of brain cerebral infarction (odds ratio [OR], 3.84; 95% confidence interval [CI], 2.22-6.70; P < 0.0001) and four socio-psychological factors including Eysenck Personality Questionnaire with Neuroticism/Stability (OR, 1.18; 95% CI, 1.12-1.20; P < 0.0001), life event scale (OR, 0.99; 95% CI, 0.98-0.99; P = 0.0007), 20 items Toronto Alexithymia Scale (OR, 1.06; 95% CI, 1.02-1.10; P = 0.002) and Social Support Rating Scale (OR, 0.91; 95% CI, 0.87-0.90; P < 0.001) in the logistic model. In addition, 11 rules were generated in the tree model. The areas under the curve of the ROC and the accuracy for the tree model were 0.85 and 0.86, respectively.MethodsThis study recruited 562 stroke patients in China who were assessed for demographic data, medical history, vascular risk factors, functional status post-stroke, and socio-psychological factors. Multivariate backward logistic regression was used to extract risk factors for depression in 1-month after stroke. We converted the logistic model to a visible tree model using the decision tree method. Receiver operating characteristic (ROC) was used to evaluate the performance of the model.ConclusionThis study provided an effective risk model for PSD and indicated that the socio-psychological factors were important risk factors of PSD.
Highlights
Post-stroke depression (PSD) is considered to be one of the most frequent and important post stroke sequela, with a prevalence ranging from 20% to 65% [1, 2]
Previous studies demonstrated that personality traits are associated with PSD, they found the patients with higher levels of neuroticism have higher risk of PSD, suggested that the impact of personality traits on depressive symptoms is mediated through illness cognitions and coping styles [5, 6, 10]
Stroke survivors have a high prevalence of alexithymia and anhedonia, PSD symptoms that cause a high burden to family caregivers
Summary
Post-stroke depression (PSD) is considered to be one of the most frequent and important post stroke sequela, with a prevalence ranging from 20% to 65% [1, 2]. The longitudinal study reported that a prevalence of PSD was increased to 25% between 0 to 3 months after stroke, decreased to 16% between 3 and 12 months after stroke, and would be increased again 1 year after stroke [4].it is important to identify patients at high risk of PSD, which will facilitate early prevention and adequate treatment. Previous studies demonstrated that personality traits are associated with PSD, they found the patients with higher levels of neuroticism have higher risk of PSD, suggested that the impact of personality traits on depressive symptoms is mediated through illness cognitions and coping styles [5, 6, 10]. This study developed a risk prediction model for PSD based on patient clinical and socio-psychology features for the early detection of high risk PSD patients
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