脑白质疏松症相关危险因素分析

目的探讨LA发病的危险因素,为临床干预提供更多证据支持。方法根据磁共振检查结果,将128例患者分为无LA组和LA组,收集相关危险因素,通过单因素分析及多因素Logistic回归比较2组危险因素分布差异。结果单因素分析提示,2组年龄、吸烟史、饮酒史、高血压史、低密度脂蛋白(LDL)、血纤维蛋白原(FIB)、同型半胱氨酸(HCY)比较差异有统计学意义(P<0.05),FIB、HCY越高,LA分级程度越高(P值分别为0.006、0.000)。多因素Logistic回归表明,年龄、吸烟史、高血压、FIB与LA发病相关。结论年龄、吸烟史、高血压、高FIB血症为LA发病的危险因素。     

伴智能障碍的脑白质疏松症患者相关危险因素分析

目的分析伴智能障碍的脑白质疏松症(LA)患者的相关危险因素。方法 207例LA患者分为伴有智能障碍组和无智能障碍组,对患者的性别、年龄、高血压病史、糖尿病史、冠心病史及既往脑梗死病史等进行相关因素分析和Logistic回归分析。结果两组年龄、高血压病史、糖尿病史、既往脑梗死病史和LA的严重程度均有显著差异。多因素回归分析最终入选模型的变量是年龄、高血压病史、既往脑梗死病史和重度LA。结论高龄、高血压病史、既往脑梗死病史和重度LA,对LA是否伴智能障碍有独立的提示作用。     

脑白质疏松症危险因素相关性分析

目的分析脑白质疏松症与危险因素的相关性。方法根据头颅MRI或CT结果选取脑白质疏松症患者132例,非脑白质疏松症患者100例,对年龄、缺血性脑卒中史、高血压史、吸烟、慢性酒精中毒、一氧化碳中毒等脑白质疏松症的危险因素用Logistic回归方法进行相关性分析。结果高血压、缺血性脑卒中、吸烟、慢性酒精中毒均可作为脑白质疏松症的独立危险因素。结论脑白质疏松症有明确的危险因素,需改变生活方式,戒烟戒酒,积极控制血压,预防和延缓脑白质疏松症的发生、发展。     

脑白质疏松症的临床危险因素分析

目的探讨脑白质疏松症的临床危险因素。方法回顾性分析2015-01-01—2016-06-01连续收治的116例脑白质疏松症患者的临床资料,利用脑白质疏松症Fazekasz量表评分将LA患者分为中度组(n=70)和重度组(n=46),并对其临床资料进行统计学处理。结果脑白质疏松症合并高血压史85例(73.2%),糖尿病15例(12.9%),脂代谢异常76例(65.5%),大动脉粥样硬化63例(54.3%),平均同型半胱氨酸水平为21.98mg/L。与中度组相比,重度组年龄较大,胆固醇、低密度脂蛋白、载脂蛋白A及载脂蛋白B的水平更低(P0.05);而同型半胱氨酸水平更高(P0.05)。结论年龄、高血压、脂代谢异常、同型半胱氨酸水平等因素均与LA的发生有关;其中高龄和高同型半胱氨酸与LA的发生有关,而血胆固醇、低密度脂蛋白及载脂蛋白A、B为LA的保护因素,其降低与更高的Fazekasz量表评分有关。     

脑白质疏松症患者的相关危险因素分析

目的探讨血浆同型半胱氨酸(Hcy)、年龄、高血压及糖尿病与脑白质疏松严重程度的相关性。方法对比分析123例LA患者和60例正常对照组之间血浆同型半胱氨酸、年龄、高血压、糖尿病及糖化血红蛋白(HbA1c)。结果 LA组较对照组Hcy、HbA1c、高血压及糖尿病发生率显著增高(P0.05)。回归分析显示,Hcy、年龄、高血压病程及HbA1c与LA严重程度呈正相关。结论 Hcy升高、年龄、高血压病程及HbA1c与LA严重程度密切相关。     

脑白质疏松症的危险因素研究新进展

随着CT和MRI的广泛应用，近年无临床症状的脑白质病变在中老年人群中检出率大大增加。新概念的脑白质疏松症(LA)是由多种原因引起的脑白质异常改变的一组疾病，与皮质下动脉硬化性脑病(BD)有不同的影像学表现。近年有学者提出其危险因素完全有别于BD，故临床诊断也应与BD有完全不同的标准。为此，现就LA的危险因素研究进展作一综述。     

脑白质疏松症1例

脑白质疏松症（1eukoaraiosis,LA）是一种非特异性脑白质改变,见于多种神经系统疾病,影像学表现为脑室周围、皮质下、半卵圆中心区CT上低密度或MRI的T2WI上高信号。临床主要表现为双下肢功能异常,认知功能障碍及记忆力损害、情感反应等。本文报道1例脑白质疏松症患者诊疗过程如下。     

脑白质疏松症患者的诱发电位研究

对２４例经颅脑ＣＴ证实的脑白质疏松症患者进行脑干听觉诱发电位和短潜伏期体感觉诱发电位检查，结果ＢＥＡＰ异常率７９％，ＳＥＰ总异常率８３％，两种诱发电位均以时间参数的异常率明显比波幅参数的异常率高。     

脑白质疏松症1例

脑白质疏松症(leukoaraiosis,LA)是一种非特异性脑白质改变,见于多种神经系统疾病,影像学表现为脑室周围、皮质下、半卵圆中心区CT上低密度或MRI的T2WI上高信号。临床主要表现为双下肢功能异常,认知功能障碍及记忆力损害、情感反应等。本文报道1例脑白质疏松症患者诊疗过程如下     

脑白质疏松症与脑血管病的关系

目的 :研究脑白质疏松症 (LA)与脑血管病的关系。方法 :对 10 2例LA伴发脑血管病患者与同期随机抽样的 10 2例无LA的脑血管病患者作对照组进行对比分析。结果 :脑血管伴发LA组年龄、高血压史≥ 10年 ,冠心病和脑卒中与对照组比较均有显著性差异 (P <0 0 5～ 0 0 1)。伴有LA的患者脑血管病类型以腔隙梗死最多见 ,与对照组比较有非常显著性差异 (P <0 0 1)。结论 :高血压引起的动脉硬化是腔隙梗死、脑出血及LA的共同病因 ,长期高血压更易导致腔隙梗死及LA。     

数据挖掘技术在卒中相关研究中的应用

卒中是一种高发病率、高死亡率、高致残率的疾病,严重威胁人类健康,降低生存质量。国内外卒中数据库及医院信息系统提供大量卒中患者临床及随访资料。数据挖掘作为智能时代的新技术,能够更高效地分析大量临床资料,进行卒中病因、诊断、疗效及预后等方面的研究。本文将分两部分介绍数据挖掘技术在卒中相关研究中的应用：①数据挖掘技术分析临床资料的基本步骤,此部分重点探讨数据分析过程一般步骤以及常用数据挖掘预测模型;②数据挖掘技术在卒中相关研究中的应用举例,此部分总结目前国内外基于数据挖掘技术的卒中相关研究,列出6种可应用数据挖掘进行的研究主题。     

老年人脑白质变性及相关危险因素分析

目的研究脑白质变性患者的血浆同型半胱氨酸(tHcy)及脑血管病危险因素与无白质变性患者差异。方法本文研究了200例老年住院患者,经头部MRI证实97例存在白质变性,103例无明显白质变性。分析白质变性的严重程度及病变分布特点,比较两组tHcy和卒中危险因素的区别。结果白质变性以中等程度占大多数(ARWMC评分2级),分布特点以皮层下深部白质较多见,其次为脑室周围白质,基底节区最少。白质变性患者,患高血压、既往卒中发生率和tHcy水平均较无白质变性的患者高(P<0.05)。结论白质变性常与高血压、有卒中史及tHcy等多种卒中危险因素共存。     

脑白质疏松的危险因素及发病机制研究进展

【摘要】 既往研究认为脑白质疏松（leukoaraiosis,LA）可能与高龄、高血压、糖尿病、高同型半胱氨酸血症等危险因素有关,但其具体相关性尚无明确结论。关于LA发病机制的研究多集中在低灌注、血脑屏障破坏上,基因的研究也是热点之一,但都尚缺乏公认的肯定研究结果。本文对LA危险因素和发病机制的研究进展和争议进行了综述。     

Leukoaraiosis on Magnetic Resonance Imaging Is Related to Long-Term Poor Functional Outcome after Thrombolysis in Acute Ischemic Stroke

Objective

Leukoaraiosis (LA) has been suggested to be related to the poor outcome or the occurrence of symptomatic intracerebral hemorrhage (sICH) after acute ischemic stroke. We retrospectively investigated the influences of LA on long-term outcome and the occurrence of sICH after thrombolysis in acute ischemic stroke (AIS).

Methods

In this study, we recruited 164 patients with AIS and magnetic resonance image (MRI)-detected thrombolysis. The presence and extent of LA were assessed using the Fazekas grading system. The National Institutes of Health Stroke Scale score was used to assess the baseline measure of neurologic severity, and the modified Rankin Scale score assessment was used up to 1 year after thrombolysis.

Results

Of 164 subjects, 56 (34.2%) showed LA on MRI. Compared to the 108 patients without LA, the patients with LA were of much older age (p<0.01), had a higher prevalence of hypertension (p<0.01), and had a much poorer outcome at 90 days (p=0.05) and 1 yr (p=0.01) after thrombolysis. There were no significant differences in sICH between patients with and without LA on MRI. In univariate analysis for the occurrence of poor outcome at 90 days after thrombolysis, the size of ischemic lesion on diffusion weighted images (DWI), [odds ratio (OR), 1.03; 95% confidence interval (95% CI), 1.01-1.04; p<0.01], recanalization (OR, 0.03; 95% CI, 0.01-0.10; p<0.01), sICH (OR, 12.2; 95% CI, 1.54-95.8), neurologic severity (OR, 1.17; 95% CI, 1.09-1.25; p<0.01), blood glucose level (OR, 1.01; 95% CI, 1.00-1.02; p=0.03), and the presence of LA on MRI (OR, 2.01; 95% CI, 1.04-3.01; p=0.04) were statistically significant. In multivariate analysis, neurologic severity (OR, 1.14; 95% CI, 1.04-1.24; p<0.01), recanalization (OR, 0.03; 95% CI, 0.01-0.11; p<0.01), lesion size on DWI (OR, 1.02; 95% CI, 1.01-1.03; p=0.02), serum glucose level (OR, 1.01; 95% CI; 1.01-1.02; p=0.03), and the presence of LA on MRI (OR, 3.2; 95% CI, 1.22-8.48; p<0.01) showed statistically significant differences. These trends persisted up to 1 yr after thrombolysis.

Conclusion

In this study, we demonstrated that the presence of LA on MRI might be related to poor outcome after use of intravenous tissue plasminogen activator in AIS.     

严重脑白质疏松症相关因素的病例对照研究

目的探讨严重脑白质疏松症的相关因素。方法按照筛选标准连续收集2015年4月-2016年2月武汉大学中南医院神经内科住院患者,通过头部核磁共振评估脑白质疏松症Fazekas评分并收集相关临床资料,并应用非条件Logistic回归来分析严重脑白质疏松症的相关因素。结果共纳入608例患者,包括Fazekas评分为0的对照组415例和Fazekas评分为3~6的病例组193例。多因素Logistic回归结果提示:高龄(G3 vs G1:OR10.81,95%CI 2.76~42.38,P=0.001;G4 vs G1:OR 28.40,95%CI 7.02~114.95,P0.05;G5 vs G1:OR 68.79,95%CI 14.22~332.92,P0.05)、脑动脉粥样硬化(OR 1.98,95%CI 1.07~3.65,P=0.029)和高血压病(OR=4.84,95%CI=2.65~8.85,P0.05)与严重脑白质疏松症之间呈显著正相关。结论高龄、脑动脉粥样硬化和高血压病可能是严重脑白质疏松症的独立危险因素。     

脑白质疏松对脑血管事件和认知功能的影响

目的 评估脑白质疏松（leukoaraiosis,LA）的危险因素,以及对老年患者后期脑血管事件和认知功能障碍发病率的影响。 方法 连续入组北京安贞医院神经内科253例门诊患者,分为LA组和对照组,按照LA的严重程度,LA组分为轻度组、中度组、重度组。将简明精神状态量表（Mini-Mental State Examination,MMSE）和蒙特利尔认知评估量表（Montreal Cognitive Assessment,MoCA）（北京版）作为认知评估工具。分析各组患者一般临床资料和认知功能,随访观察并比较各组患者脑梗死、脑出血以及认知功能障碍的发病率。 结果 LA组与对照组相比,患有高血压、糖尿病的比例显著升高,差异有显著性（P值分别为0.003和0.004）。中、重度LA组与对照组相比,认知障碍的患病率显著升高（P值分别为0.035和0.019）。随访1年,轻、中、重度LA组脑梗死的发病率均高于对照组,差异有显著性（P值分别为0.019、0.024和0.049）。四组间脑出血的发病率无显著差异。轻、中、重度LA组的新发认知障碍的发病率高于对照组,差异有显著性（P值分别为0.048、0.036和0.004）。 结论 老年LA患者认知障碍的患病率高于无白质疏松人群,且1年内新发认知障碍和缺血性卒中的发病率也高于无白质疏松人群。     

Predictive Factors of Social Functioning in Patients with Schizophrenia: Exploration for the Best Combination of Variables Using Data Mining

Objective

This study aimed to use data mining to explore the significantly contributing variables to good social functioning in schizophrenia patients.

Methods

The study cohort comprised 67 schizophrenia patients on stable medication. A total of 51 variables (6 demographic data, 3 illness history, 22 social cognition, 16 neurocognition, 4 psychiatric symptoms) were input into a data-mining decision tree using the Answer Tree program to find the pathway for the best social functioning.

Results

Several contributing factors for good social functioning were found. Continuous attention was the strongest contributing factor. Three variables involving best social functioning included good continuous attention, good theory of mind (TOM), and low sensitivity of disgust emotion.

Conclusion

Our results confirmed the mediating roles of social cognition between neurocognition and functional outcomes, and suggested that social cognition can significantly predict social functioning in schizophrenia patients.     

进展性缺血性卒中相关危险因素分析

目的对进展性缺血性卒中(SIP)相关危险因素进行探讨。方法对我院41例SIP患者的入院时血压、血糖、体温、同型半胱氨酸、周围血白细胞、血脂、血沉、高敏C反应蛋白、梗死部位、动脉狭窄及既往病史等因素进行回顾性分析。结果SIP患者与对照组比较,入院时体温、白细胞计数、同型半胱氨酸及脑梗死部位等差异有统计学意义(P<0.05)。结论SIP多与入院时体温升高、高同型半胱氨酸及分水岭区脑梗死相关。     

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

Objective

Many applications such as biomedical signals require selecting a subset of the input features in order to represent the whole set of features. A feature selection algorithm has recently been proposed as a new approach for feature subset selection.

Methods

Feature selection process using ant colony optimization (ACO) for 6 channel pre-treatment electroencephalogram (EEG) data from theta and delta frequency bands is combined with back propagation neural network (BPNN) classification method for 147 major depressive disorder (MDD) subjects.

Results

BPNN classified R subjects with 91.83% overall accuracy and 95.55% subjects detection sensitivity. Area under ROC curve (AUC) value after feature selection increased from 0.8531 to 0.911. The features selected by the optimization algorithm were Fp1, Fp2, F7, F8, F3 for theta frequency band and eliminated 7 features from 12 to 5 feature subset.

Conclusion

ACO feature selection algorithm improves the classification accuracy of BPNN. Using other feature selection algorithms or classifiers to compare the performance for each approach is important to underline the validity and versatility of the designed combination.