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Objective:To assess the predictive factors and prognosis of post-stroke seizures.Methods:A total of 315 inpatients with acute anterior circulation cerebral infarction from January 2018 to December 2018 were retrospectively collected, including 95 patients with PSS as observation group and 220 patients without PSS as control group.Clinical characteristics of the patients were recorded, including gender, age, lesion specificity, imaging features, past history, and the time and type of seizures.The Alberta stroke program early CT score (ASPECTS) was used to assess the extent of infarction, the national institutes of health stroke scale (NIHSS) and the modified rankin scale (MRS) were used to assess the severity and prognosis of cerebral infarction.The hemorrhage transformation of cerebral infarction was graded according to the European cooperative acute stroke study Ⅲ(ECASS Ⅲ) classification system.SPSS 21.0 software was used for data analysis.Chi-square test was used for categorical variables and t-test or non-parametric test was used for continuous variables. Results:The observation group had lower ASPECTS scores compared with the control group (5(4, 7), 7 (5, 8)), the presence of atrial fibrillation, hemorrhage transformation, laminar necrosis(LN) and hemosiderin deposition (31.6%, 45.3%, 24.2%, 26.3%) were higher than those of control group (20.9%, 28.2%, 9.1%, 16.4%), and the differences were statistically significant (all P<0.05). In multivariate analysis, ASPECTS score ( OR=0.658, 95% CI=0.556-0.778, P<0.001), hemorrhage transformation ( OR=2.307, 95% CI=1.311-4.059, P=0.004), LN ( OR=2.530, 95% CI=1.250-5.123, P=0.010) and hemosiderin deposition ( OR=2.308, 95% CI=1.201-4.436, P=0.012) were the influencing factors of PSS.Partial secondary generalized seizures was the most common type of seizures, and in this group it accounted for 42.1% (40/95), simple partial seizures and complex partial seizures accounted for 12.6% (12/95)respectively, and generalized seizures accounted for 32.6% (31/95). The mean follow-up time of the two groups was 24.1 months and 24.6 months, respectively.The scores of MRS at the last follow-up and discharge (3(2, 4), 2(1, 4)) of the observation group were better than those of the control group (2(1, 3), 1(1, 3)), and the differences were statistically significant(both P<0.05). Conclusions:PSS after cerebral infarction can affect the prognosis of patients, and the large infarction scope, hemorrhage transformation, LN and hemosiderin deposition are the high risk factors of PSS.
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Objective:To investigate the effect of hemorrhagic transformation (HT) and its different subtypes on the clinical outcome of patients with acute ischemic stroke (AIS).Methods:Patients with AIS within 24 h of onset treated in Henan Provincial People's Hospital from January 2018 to January 2021 were retrospectively enrolled. HT was defined as intracranial hemorrhage found by CT reexamination within 7 d after the onset of AIS, and further divided into hemorrhagic infarction (HI) and parenchymal hematoma (PH) according to the classification standard of European Cooperative Acute Stroke Study (ECASS)-Ⅱ. The modified Rankin Scale was used to evaluate the outcome at 90 d after onset. 0-2 was defined as good outcome and 3-5 were defined as poor outcome. Multivariate logistic regression analysis was used to determine the independent influencing factors of the outcomes. Results:A total of 822 patients were enrolled, including 478 males (58.2%), aged 60.6±10.6 years. The median score of the baseline National Institutes of Health Stroke Scale (NIHSS) was 8 (interquartile range: 6-12). Two hundred and eighty-two patients (34.4%) developed HT and 447 (54.4%) had poor outcomes. Multivariate logistic regression analysis showed that PH-1 (odds ratio [ OR] 2.461, 95% confidence interval [ CI] 1.285-4.712; P=0.007), PH-2 ( OR 5.291, 95% CI 1.178-23.758; P=0.030), blood glucose at admission ( OR 1.063, 95% CI 1.018-1.109; P=0.005) and baseline NIHSS score ( OR 1.124, 95% CI 1.076-1.175; P<0.001) were the independent influencing factors of the poor outcomes. Conclusion:Different HT subtypes have different effects on the outcomes of patients with AIS, among which PH-1 and PH-2 are the independent risk factors for poor outcomes.
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Objective:To investigate the monocyte to high-density lipoprotein cholesterol (HDL-C) ratio (MHR) for the predictive value of early neurological deterioration (END) and poor outcome in patients with acute anterior circulation ischemic stroke (AACIS).Methods:Patients with AACIS admitted to Henan Provincial People's Hospital from January 2021 to January 2022 were included retrospectively. END was defined as the National Institutes of Health Stroke Scale (NIHSS) score within 7 d of onset increase ≥2 compred with baseline or the increase of motor function score ≥1. The patients were divided into END group and non-END group according to the presence or absence of END. The patients were also divided into good outcome group (0-2 points) and poor outcome group (3-6 points) according to the modified Rankin Scale score 3 months after onset. Multivariate logistic regression analysis was used to determine the independent risk factors for END and poor outcome, and the predictive value of MHR for END and poor outcome was evaluated by receiver operating characteristic (ROC) curve. Results:A total of 522 patients were enrolled, including 338 male (64.8%), aged 61.99±11.39 years old. One hundred and five patients (20.1%) had END, 123 (23.6%) had poor outcome. Multivariate logistic regression analysis showed that baseline NIHSS score (odds ratio [ OR] 1.075, 95% confidence interval [ CI] 1.017-1.137; P=0.010) and MHR (with the lowest quartile as the reference, the third quartile: OR 2.778, 95% CI 1.255-6.151, P=0.012; the fourth quartile: OR 12.645, 95% CI 5.942-26.912; P<0.001) were the independent risk factors for END; the baseline NIHSS score ( OR 1.075, 95% CI 1.021-1.132; P=0.006), END ( OR 2.306, 95% CI 1.010-6.261; P=0.047) and MHR (with the first quartile as reference, the fourth quartile: OR 2.769, 95% CI 1.167-6.569; P=0.021) were the independent risk factors for poor outcomes. ROC curve analysis showed that area under the curve of MHR for predicting END and poor outcome in patients with AACIS were 0.805 (95% CI 0.750-0.860; P<0.001) and 0.747 (95% CI 0.690-0.803; P<0.001) respectively. The best cutoff value was 0.435, the sensitivity was 73.3% and 64.2%, and the specificity was 79.6% and 78.7% respectively. The area under the curve of MHR for predicting END and poor outcome was higher than that of monocyte and HDL-C alone. Conclusion:MHR can be used as a predictor of END and poor outcome in patients with AACIS, and its predictive value is higher than that of monocytes or HDL-C.
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Objective:To observe the clinical and imaging features of cortical laminar necrosis (CLN) after acute cerebral infarction, and to explore its possible mechanism.Methods:Five hundred and three patients were recruited into study with acute anterior circulation cerebral infarction confirmed by magnetic resonance imaging in People′s Hospital of Zhengzhou University from June 2019 to June 2020. They were divided into 24 patients with CLN (CLN group) and 479 patients without CLN (NCLN group). The general information and clinical manifestations of the patients were recorded. National Institutes of Health Stroke Scale (NIHSS) and Montreal Cognitive Assessment Scale (MoCA) scores and cranial magnetic resonance imaging characteristics were compared between the two groups, and the possible mechanism was discussed.Results:After acute cerebral infarction, the incidence of CLN was 4.77% (24/503). CLN group had more cognitive impairment (MoCA total score 15.17±2.67; NCLN group 18.12±2.49) and less neurological impairment (NIHSS total score 6.93±3.63; NCLN group 8.86±3.26),and there were significant differences between the two group ( t=-5.58, t=-2.75; P<0.05). In the CLN group, the proportion of perfusion-weighted imaging showing hyper-perfusion in the laminar necrosis area (increased relative cerebral blood volume) was 87.5% (21/24), while in the NCLN group, the proportion of hyper-perfusion was lower [1.25% (6/479)]. There was statistically significant difference in the perfusion between the two groups (χ2=143.06, P<0.01). In the CLN group, CT angiography or magnetic resonance angiography showed common atherosclerotic stenosis or occlusion of the large intracranial arteries. Conclusion:CLN after cerebral infarction is relatively rare in clinical practice, and its occurrence may be related to local cortical hyper-perfusion.