1.Short-term prognostic model of spontaneous cerebral hemorrhage based on XGboost
Hong YUE ; Aimei WU ; Zhi GENG ; Zhaoping YU ; Ye YANG ; Chi ZHANG ; Xuechun LIU ; Juncang WU
Chinese Journal of Neuromedicine 2023;22(7):706-710
Objective:To develop a short-term prognostic model of spontaneous cerebral hemorrhage based on eXtreme Gradient Boosting (XGBoost) machine learning, and to compare its predictive performance with a Logistic regression model.Methods:Patients with sICH admitted to Department of Neurology, Second People's Hospital of Hefei from January 2018 to March 2022 were chosen; their general demographic characteristics, medical history, laboratory indices and cranial imaging data were retrospectively collected. The prognoses of patients 90 d after discharge were evaluated according to modified Rankin Scale (mRS) scores (good prognosis: mRS scores<3; poor prognosis: mRS scores≥3). XGboost and multiple Logistic regression models were used to screen out the factors for prognoses of patients 90 d after discharge, and area under receiver operating characteristic (ROC) curves, sensitivity, specificity and prediction accuracy of the 2 models were analyzed and compared.Results:A total of 413 patients with sICH were included; 180 patients(43.6 %) had poor prognosis and 233 (56.4%) had good prognosis 90 d after discharge. Multivariate Logistic regression results showed that age≥65 years, hemorrhage into the ventricle, hematoma volume of 20-40 mL, hematoma volume>40 mL and National Institutes of Health Stroke Scale (NIHSS) scores were independent influencing factors for short-term prognoses of sICH ( P<0.05). The variables in the XGBoost model were ranked in order of importance: NIHSS scores, systolic blood pressure at admission, Glasgow coma scale (GCS) scores, age≥65 years, hemorrhage into the ventricle, hematoma volume of 20-40 mL, and hematoma volume>40 mL. AUC of XGBoost model in predicting the prognosis was 0.895 (95% CI: 0.820-0.947), enjoying sensitivity of 68.89%, specificity of 94.83%, and prediction accuracy of 83.5%. AUC of Logistic regression model in predicting the prognosis was 0.894 (95% CI: 0.818-0.946), enjoying sensitivity of 93.33%, specificity of 70.69%, and prediction accuracy of 80.58%. Conclusion:The short-term prognostic model based on XGboost for sICH patients has high predictive efficacy, whose predictive accuracy is better than traditional Logistic regression.
2.Monocyte-to-high-density lipoprotein cholesterol ratio predicts early neurological deterioration and hemorrhagic transformation after intravenous thrombolytic therapy in patients with acute ischemic stroke
Ruorui YANG ; Liuzhenxiong YU ; Kangrui ZHANG ; Juncang WU
International Journal of Cerebrovascular Diseases 2023;31(2):87-93
Objective:To investigate the predictive value of monocyte-to-high-density lipoprotein cholesterol ratio (MHR) for early neurological deterioration (END) and hemorrhagic transformation (HT) after intravenous thrombolysis in patients with acute ischemic stroke (AIS).Methods:Patients with AIS received IVT in Hefei Second People's Hospital from May 2020 to January 2022 were retrospectively enrolled. Blood collection was completed and MHR was calculated before intravenous thrombolysis. END was defined as an increase of ≥2 from the baseline in the National Institutes of Health Stroke Scale (NIHSS) score or ≥1 from the baseline in motor function score at any time within 7 d after admission. HT was defined as intracranial hemorrhage newly found by CT/MRI within 24 h after intravenous thrombolysis. Multivariate logistic regression analysis was used to determine the independent predictors of END and HT, and the receiver operating characteristic (ROC) curve was used to analyze the predictive value of MHR for END and HT. Results:A total of 186 patients with AIS treated with IVT were included, of which 50 (26.9%) had END and 31 (16.7%) had HT. The median MHR was 0.43. The MHR in the END group was significantly higher than that in the non-END group (0.49 vs. 0.40; P=0.008), and the MHR in the HT group was significantly higher than that in the non-HT group (0.52 vs. 0.40; P=0.013). All patients were divided into 4 groups (MHR1, MHR2, MHR3 and MHR4) according to the MHR quartile from low to high. Multivariate logistic regression analysis showed that after adjusting for confounding factors, taking MHR1 as a reference, MHR3 (odds ratio [ OR] 6.317, 95% confidence interval [ CI] 1.465-27.237; P=0.013) and MHR4 ( OR 8.064, 95% CI 1.910-34.051; P=0.005) were the significant independent predictors of END; Taking MHR1 as a reference, MHR4 ( OR 5.147, 95% CI 1.194-22.182; P=0.028) was the significant independent predictor of HT. The ROC curve analysis showed that the area under the curve of MHR for predicting END was 0.628 (95% CI 0.554-0.698; P=0.008). When the optimal MHR cutoff value was 0.41, its sensitivity and specificity for predicting END was 74.0% and 53.7% respectively. The area under the curve of MHR for predicting HT was 0.642 (95% CI 0.569-0.711; P=0.013). When the best cutoff value was 0.44, the sensitivity and specificity of MHR for predicting HT were 77.4% and 58.1% respectively. Conclusion:Higher MHR is a risk factor for END and HT after intravenous thrombolysis in patients with AIS, but the predictive value of MHR for END and HT is limited.
3.Obstructive sleep apnea in patients with ischemic stroke: mechanism, diagnosis, and treatment
Qianyun ZHANG ; Xuechun LIU ; Wenpei WU ; Zheng TAN ; Xiaoying MENG ; Juncang WU
International Journal of Cerebrovascular Diseases 2023;31(7):535-541
Ischemic stroke is the main cause of death and disability in adults, and its incidence is increasing year by year. Obstructive sleep apnea (OSA) is the most common type of sleep-disordered breathing, which can increase the risk of ischemic stroke and affect the outcomes of patients. There is an increasing amount of research on the relationship between OSA and ischemic stroke. This article reviews the bidirectional relationship between OSA and ischemic stroke, the mechanism of OSA causing ischemic stroke, and the diagnosis and treatment of OSA in patients with ischemic stroke.
4.Carotid plaque and ischemic stroke
Xiaoying MENG ; Zheng TAN ; Wenpei WU ; Qianyun ZHANG ; Juncang WU
International Journal of Cerebrovascular Diseases 2023;31(9):672-676
Carotid atherosclerosis is closely associated with ischemic stroke. Research shows that the rupture of vulnerable carotid plaque is an important reason for carotid atherosclerosis leading to thromboembolic events. Therefore, early identification of vulnerable carotid plaques is of great significance for the diagnosis, treatment, and prevention of ischemic stroke. This article reviews the pathophysiological features, imaging evaluation of carotid plaque and its relationship with ischemic stroke.
5.Impact of obstructive sleep apnea on outcome in patients with acute ischemic stroke
Qianyun ZHANG ; Xuechun LIU ; Juncang WU
International Journal of Cerebrovascular Diseases 2023;31(12):895-900
Objective:To investigate the impact of obstructive sleep apnea (OSA) on neurological function outcome in patients with acute ischemic stroke (AIS) at 90 days after onset.Methods:Patients with AIS admitted to Hefei Second People's Hospital from September 2022 to June 2023 were prospectively included. According to the modified Rankin Scale score at 90 days after onset, they were divided into a good outcome group (0-2) and a poor outcome group (>2). The demographic data, vascular risk factors, baseline laboratory tests, National Institutes of Health Stroke Scale (NIHSS) scores at admission, severity of obstructive sleep apnea (OSA), and apnea hypopnea index (AHI) were compared between the two groups. Multivariate logistic regression analysis was used to determine the independent risk factors for poor outcomes. Results:A total of 104 patients with AIS were enrolled, including 62 males (59.6%), with a median age of 65.5 years (interquartile range, 57.0-72.0 years). The median baseline NIHSS score was 3.00 (interquartile range, 2.00-4.00). The median AHI was 18.14/h (interquartile range, 11.34-27.88/h), 43 patients (41.35%) with no/mild OSA and 61 patients (58.65%) with moderate to severe OSA. Seventy-four patients (71.2%) had good outcome, and 30 patients (28.8%) had poor outcome. When introducing AHI as a categorical variable into the logistic regression model, the higher baseline NIHSS score (odds ratio [ OR] 3.041, 95% confidence interval [ CI] 1.797-5.145; P<0.001) and moderate to severe OSA ( OR 4.413, 95% CI 1.032-18.877; P=0.045) were independent risk factors for poor outcome; When introducing AHI as a continuous variable into the logistic regression model, higher baseline NIHSS score ( OR 3.176, 95% CI 1.844-5.472; P<0.001), age ( OR 1.093, 95% CI 1.014-1.177; P=0.020), and AHI ( OR 1.044, 95% CI 1.002-1.089; P=0.042) were independent risk factors for poor outcome. Conclusion:Moderate to severe OSA is an independent risk factor for poor functional outcome in patients with AIS at 90 days after onset, and a higher AHI indicates poor outcome in patients.
6.Vitamin D and ischemic stroke
Liuzhenxiong YU ; Kangrui ZHANG ; Ruorui YANG ; Juncang WU
International Journal of Cerebrovascular Diseases 2022;30(8):621-625
Ischemic stroke is the second leading cause of disability and death worldwide, which brings heavy burden to society and families. Epidemiological studies have shown that vitamin D level are associated with the prevalence of hypertension, diabetes, atherosclerosis, and cerebrovascular events. This article reviews the relationship between vitamin D level and ischemic stroke risk, infarct volume in acute phase, severity of neurological deficit and functional outcome, and discusses the impact of vitamin D supplementation on ischemic stroke, and expects to provide new ideas for the prevention and treatment of ischemic stroke.
7.Platelet-to-neutrophil ratio predicts the outcomes after intravenous thrombolysis in patients with acute ischemic stroke
Yurong TIAN ; Qiuwan LIU ; Fang HUANG ; Liuzhenxiong YU ; Kangrui ZHANG ; Ruorui YANG ; Juncang WU
International Journal of Cerebrovascular Diseases 2022;30(3):167-173
Objective:To investigate the predictive value of platelet-to-neutrophil ratio (PNR) on hemorrhagic transformation (HT) and poor outcomes at 90 d after intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS).Methods:Patients with AIS received IVT in Hefei Second People's Hospital from July 2019 to June 2021 were retrospectively enrolled. HT was defined as intracerebral hemorrhage found by CT reexamination within 24 h after IVT, and the poor outcome was defined as the modified Rankin Scale score ≥3 at 90 d after onset. Multivariate logistic regression analysis was used to determine the independent predictors of HT and poor outcomes at 90 d, and the predictive value of PNR on HT and poor outcomes at 90 d was analyzed by receiver operating characteristic (ROC) curve. Results:A total of 202 patients with AIS treated with IVT were included, of which 32 had HT and 50 had poor outcomes at 90 d after onset. Multivariate logistic regression analysis showed that PNR at 24 h after IVT was significantly and independently negatively correlated with the poor outcomes (odds ratio [ OR] 0.959, 95% confidence interval [ CI] 0.928-0.991; P=0.012); PNR at admission ( OR 0.886, 95% CI 0.827-0.948; P<0.001) and PNR at 24 h after IVT ( OR 0.923, 95% CI 0.879-0.969; P=0.001) were significantly independently and negatively correlated with HT. ROC curve analysis showed that the area under the curve of PNR at 24 h after IVT for predicting poor outcomes was 0.733 (95% CI 0.659-0.807; P=0.012), the best cutoff value was 35.03, and the predictive sensitivity and specificity were 70.4% and 74%, respectively. The area under the curve of PNR at admission for predicting HT was 0.830 (95% CI 0.774-0.886; P<0.001), the best cutoff value was 34.81, and the predictive sensitivity and specificity were 70% and 93.7%, respectively. The area under the curve of PNR at 24 h after IVT for predicting HT was 0.770 (95% CI 0.702-0.839; P=0.001), the best cutoff value was 41.73, and the predictive sensitivity and specificity were 53.5% and 96.9%, respectively. Conclusion:For patients with AIS treated with IVT, lower PNR at 24 h after IVT is an independent predictor of the poor outcomes at 90 d, while PNR at admission and 24 h after IVT are the independent predictors of HT.
8.Von Willebrand factor-glycoprotein Ⅰb axis and ischemic stroke
Jing CHEN ; Juncang WU ; Chi ZHANG ; Lei HUANG
International Journal of Cerebrovascular Diseases 2021;29(5):378-381
Due to the narrow time window of traditional reperfusion therapy and the presence of the risk of reperfusion injury, it is of great significance to study the pathogenesis of ischemic stroke and explore methods to reduce reperfusion injury from the perspective of pathophysiology. This article expounds the functions of von Willebrand factor (vWF) and platelet glycoprotein (GP) Ⅰb and their roles in hemostasis, thrombosis, and inflammation. It is believed that pharmacological blockade of the interaction of vWF-GP Ⅰb may contribute to the treatment of ischemic stroke. In addition, its clinical significance in ischemic stroke and ischemic brain injury was further discussed.
9.Relationship between ascorbic acid and depression
Fang HUANG ; Hong YUE ; Aimei WU ; Yurong TIAN ; Kangrui ZHANG ; Zhenxiong YULIU ; Ruorui YANG ; Juncang WU
Chinese Journal of Neuromedicine 2021;20(11):1182-1187
Depression is a common emotional disorder, which has high incidence rate and mortality worldwide. Ascorbic acid (AA) is also known as vitamin C. As a kind of reducing vitamin, AA participates in anti-oxidation, enzyme assistance and neuro-modulation in the central nervous system. Clinical evidence and animal studies show that AA has anti-depressant effect. This article reviews the function of AA in the nervous system, the current researches on relation between AA and depression, and possible mechanism, and analyzes its therapeutic significance in this disease, hoping to provide new ideas for the clinical treatment of depression.
10.Mean platelet volume predicts the outcomes in patients with acute ischemic stroke treated with intravenous thrombolysis
Chi ZHANG ; Xiaolu HE ; Yurong TIAN ; Zhenxiong YULIU ; Kangrui ZHANG ; Ruorui YANG ; Juncang WU
International Journal of Cerebrovascular Diseases 2021;29(3):169-173
Objective:To investigate the correlation between mean platelet volume (MPV) and clinical outcome in patients with acute ischemic stroke (AIS) after intravenous thrombolysis.Methods:Consecutive patients with AIS treated with standard dose alteplase intravenous thrombolysis in the Department of Neurology, the Second People's Hospital of Hefei from July 1, 2019 to August 30, 2020 were enrolled retrospectively. The clinical, laboratory, and imaging data of the patients were collected. The modified Rankin Scale was used to evaluate the clinical outcome at 90 d after onset, and a score of >2 was defined as a poor outcome. Multivariate logistic regression model was used to analyze the independent correlation between MPV and clinical outcome. The receiver operating characteristic (ROC) curve was used to analyze the predictive value of MPV for clinical outcome. Results:A total of 104 patients with AIS who received intravenous thrombolytic therapy were included, including 40 males (38.5%), 64 females (61.5%), and their age was 68.7±12.5 years. The baseline median National Institutes of Health Stroke Scale (NIHSS) score was 6 (interquartile range, 4-11), and the time from onset to intravenous thrombolysis was (128.5±55.9) min. Seventy-five patients (72.1%) had a good outcome, 29 (27.9%) had a poor outcome, and there was no death. The baseline NIHSS score, C-reactive protein, MPV, MPV/platelet count ratio and the proportion of patients with anterior circulation infarction in the poor outcome group were significantly higher than those in the good outcome group (all P<0.05). Multivariate logistic regression analysis showed that MPV (odds ratio [ OR] 1.868, 95% confidence interval [ CI] 1.277-2.732; P=0.001) and baseline NIHSS score ( OR 1.199, 95% CI 1.083-1.328; P<0.001) were the independent risk factors for poor outcome. ROC curve analysis showed that the area under the curve for predicting poor outcome was 0.714 (95% CI 0.606-0.821; P=0.001). The optimal cut-off value was 11.25 fl, the predictive sensitivity and specificity were 65.5% and 70.5%, respectively. Conclusions:There was a significant independent correlation between MPV and the clinical outcome in patients with AIS after intravenous thrombolysis. A higher baseline MPV had a certain predictive value for poor outcome.

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