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Aim: To evaluate the psychometric properties of the Post-Stroke Depression Scale in the Sequelae Stage (PSDS-SS). Background: The incidence of the sequelae stage Post-Stroke Depression (PSD) is high, and the best screening tools are still lacking. Under this circumstances, our research team developed the PSDS-SS by Delphi method, but its psychometric properties need to be further verified. Method: This was a cross-sectional study. Seven hundred and sixteen stroke patients in the sequelae stage were enrolled by purpose sampling from May 2022 to September 2022. The exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to verify the factor structure of the scale. The reliability of the scale was tested by Cronbach's α coefficient, test-retest reliability and composite reliability. The validity of the scale was tested by criterion-related validity, convergent and discriminant validity. Result: Eight items were deleted through item analysis. The EFA ended up with a 5-factor scale including 24 items after removing one item with low factor loading. Finally, a 21-item model was established by confirmatory factor analysis, and all the fit indexes were acceptable. The reliability and validity of the total scale and each factor are acceptable. Conclusion: The PSDS-SS has a stable factor structure, and demonstrated good reliability and validity. And it would be an effective tool to assess PSD in the sequelae stage.
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Background and Purpose: White blood cell count to mean platelet volume ratio (WMR) is increasingly recognized as a promising biomarker. However, its predictive capability for acute ischemic stroke (AIS) patients is relatively less researched. The primary aim of this study is to explore its prognostic value in AIS patients after reperfusion regarding 3-month poor functional outcome. Methods: A total of 549 AIS patients who had undergone vascular reperfusion procedure with complete 3-month follow-up were retrospectively recruited in this study. White blood cell count, mean platelet volume at 24 h of admission were recorded. Stroke severity had been estimated using the National Institutes of Health Stroke Scale (NIHSS) and poor outcome was defined as modified Rankin Scale (mRS) 3-6 at 3 months. Results: AIS patients with poor functional outcome at 3 months displayed higher WMR. A positive correlation between WMR and NIHSS score was found (r = 0.334, p < 0.001). After adjusting potential confounders, WMR was still an independent risk factor for poor prognosis at 3 months (OR = 2.257, 95% CI [1.117-4.564], p = 0.023) in multivariate logistic regression model. Subgroup analyses further suggested a significant association between WMR and poor outcome in high baseline NIHSS (per 0.1-point increase: OR = 1.153, 95% CI [1.014-1.312], p = 0.030) group. Receiver operating characteristic (ROC) curves analysis was utilized to assess the predictive ability of WMR, indicating a cut-off value of 0.86. A nomogram that includes age, sex, NIHSS on admission, high WMR for predicting 1-year all-cause survival was also developed (C-index = 0.628). Conclusions: WMR is significantly correlated with stroke severity on admission and is proved to be an important prognostic indicator for AIS outcomes, especially in high NIHSS on admission group. Additionally, the developed nomogram that includes high WMR for predicting 1-year survival provides us with an effective visualization tool.
