The aim of this study was to evaluate the diagnostic value of the serum biochemical markers high-sensitivity C-reactive protein (hs-CRP), D-dimer (DD) and fibrinogen (Fg) in differentiating etiological subtypes of ischemic stroke. This study was a retrospective case-only study, consecutively including patients with acute ischemic stroke. All patients were classified into subtypes using the TOAST classification system. A total of 317 patients were evaluated. Hs-CRP and DD levels were significantly different among the subtypes and were the highest in CE, followed by LAA and SAA; no significant difference between the subtypes was found for Fg. Hs-CRP > 6.96 mg/L was classified as the CE subtype, with a sensitivity of 41% and a specificity of 74%; DD > 791.30 ng/mL was classified as CE, with a sensitivity of 58% and a specificity of 78%. The combination of hs-CRP and DD classification as CE yielded a sensitivity of 65% and a specificity of 91%. DD > 791.30 ng/mL was considered an independent predictive factor of CE. Hs-CRP and DD could be useful for identifying the etiological subtypes of acute ischemic stroke, especially for predicting CE. The diagnostic value of DD was higher than that of hs-CRP.

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Objective. The aim of this study was to investigate the cognitive function characteristics of Parkinson's disease (PD) with sleep disorders. Methods. Consecutive patients with PD (n = 96), patients with primary sleep disorders (n = 76), and healthy control subjects (n = 66) were assessed. The patients with PD were classified into sleep disorder (PD-SD) and non-sleep disorder (PD-NSD) groups. Results. Among 96 patients with PD, 69 were diagnosed with a sleep disorder. There were 38 sleep disorder cases, 31 RBD cases, and 27 NSD cases. On the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and MoCA subtests, patients in the PD-SD, primary sleep disorder, and PD-NSD groups exhibited lower scores than those in the control group. Moreover, the PD-SD patients exhibited more significant cognitive impairment than was observed in the primary sleep disorder patients. In the PD-SD subgroup, the attention scores on the MoCA and on MoCA subtests were lower in the PD with RBD group than in the PD with insomnia group. Conclusion. PD with sleep disorders may exacerbate cognitive dysfunction in patients. PD associated with different types of sleep disorders differentially affects cognitive functions, and patients with PD with RBD exhibited poorer cognitive function than was seen in patients with PD with insomnia.

Background This study aimed to investigate integrating radiomics with clinical factors in cranial computed tomography (CT) to predict ischemic strokes in patients with silent lacunar infarction (SLI). Methods Radiomic features were extracted from baseline cranial CT images of patients with SLI. A least absolute shrinkage and selection operator (LASSO)–Cox regression analysis was used to select significant prognostic factors based on Model C with clinical factors, Model R with radiomic features, and Model CR with both factors. The Kaplan–Meier method was used to compare stroke-free survival probabilities. A nomogram and a calibration curve were used for further evaluation. Results Radiomic signature ( p < 0.01), age ( p = 0.09), dyslipidemia ( p = 0.03), and multiple infarctions ( p = 0.02) were independently associated with future ischemic strokes. Model CR had the best accuracy with 6-, 12-, and 18-month areas under the curve of 0.84, 0.81, and 0.79 for the training cohort and 0.79, 0.88, and 0.75 for the validation cohort, respectively. Patients with a Model CR score < 0.17 had higher probabilities of stroke-free survival. The prognostic nomogram and calibration curves of the training and validation cohorts showed acceptable discrimination and calibration capabilities (concordance index [95% confidence interval]: 0.7864 [0.70–0.86]; 0.7140 [0.59–0.83], respectively). Conclusions Radiomic analysis based on baseline CT images may provide a novel approach for predicting future ischemic strokes in patients with SLI. Older patients and those with dyslipidemia or multiple infarctions are at higher risk for ischemic stroke and require close monitoring and intensive intervention.