代谢综合征对皮质下缺血性脑血管病影像学损害的影响

目的 探讨代谢综合征及其各因子对皮质下缺血性脑血管病(SIVD)影像学损害的影响. 方法 选取120例SIVD患者(SIVD组),年龄其中包括非代谢综合征患者25例,代谢综合征倾向患者25例,代谢综合征患者70例.代谢综合征的诊断标准采用美国国家胆固醇教育计划成人治疗专家组Ⅲ(NCEP-ATPⅢ)标准.SIVD影像学损害采用改良Scheltens量表对头颅MRI进行评价,分为脑室旁、脑白质、基底节三个脑区评定并计算总分. 结果 代谢综合征倾向组脑室旁、脑白质、基底节评分、Scheltens总分[(3.75±1.60)分、(10.67±5.26)分、(3.21±2.62)分、(17.62±8.32)分]和代谢综合征组[(4.21±1.09)分、(13.79±5.25)分、(6.90±4.25)分、(24.90±9.25)分]均显著高于非代谢综合征组[(2.76±1.62)分、(6.36±3.93)分、(1.52±1.50)分、(10.58±5.89)分,均P＜0.05].腰围与脑白质得分及Scheltens总分呈显著正相关(r=0.185,P=0.046; r=0.488,P＜0.001);三酰甘油(TG)与脑白质、基底节得分有显著正相关(r=0.188,P=0.042; r=0.311,P=0.001);空腹血糖与脑白质、基底节得分以及Scheltens总分呈显著正相关(r=0.235,P=0.011; r=0.229,P=0.013; r=0.206,P=0.027);高密度脂蛋白胆同醇(HDL C)与脑白质、基底节以及Schehens总分呈显著负相关(r=-0.238,P=0.010; r=-0.189,P=0.042;r=-0.335,P＜0.001).进一步多元线性逐步回归分析结果发现空腹血糖、HDL C与脑白质评分显著相关(P均＜0.05);TG与基底节评分显著相关(P＜0.05);腰围、空腹血糖、HDL-C与Scheltens总分显著相关(P均＜0.05). 结论 代谢综合征及其各因子与SIVD影像学损害相关,其中腹型肥胖、TG、空腹血糖、HDL-C是SIVD的重要危险因素.     

Cardiovascular autonomic function analysis using approximate entropy from 24‐h heart rate variability and its frequency components in patients with type 2 diabetes

Aims/Introduction

The principal aim of the present study was to investigate the cardiovascular autonomic system status of diabetes patients using approximate entropy (ApEn) extracted from 24-h heart rate variability (HRV) and its frequency components.

Materials and Methods

A total of 29 healthy controls and 63 type 2 diabetes patients were included. Participants’ 24-h HRV signals were recorded, and decomposed and reconstructed into four frequency components: high, low, very low and ultra low. The total 24-h HRV and its four components were divided into 24 1-h segments. ApEn values were extracted and statistically analyzed. Four traditional HRV indices, namely standard deviation of the RR intervals, root mean square of successive differences, coefficient of variance of RR intervals and ratio of low to high power of HRV, were also calculated.

Results

The low-frequency component contained the most abundant non-linear information, so was potentially most suitable for studying the cardiovascular system status with non-linear methods. ApEn values extracted from low- and high-frequency components of healthy controls were higher than those of diabetes patients. Except for root mean square of successive differences, standard deviation of the RR intervals, low to high power of HRV and coefficient of variance of RR intervals of healthy controls were all higher than those of diabetes patients.

Conclusions

The results showed that ApEn contained information on disorders of autonomic system function of diabetes patients as traditional HRV indices in time and frequency domains. ApEn and three traditional indices showed accordance to some degree. Non-linear information in subcomponents of HRV was shown, which is potentially more effective for distinguishing healthy individuals and diabetes patients than that extracted from the total HRV. Compared with diabetes patients, the cardiovascular system of healthy controls showed information of higher complexity, and better regulation function in response to changes of environment.     

影像后处理技术在神经外科教学查房中的应用

目的 评价以问题为基础的教学法(problem-based learning,PBL)联合影像后处理技术在神经外科教学查房中的应用效果.方法 选择神经外科典型病例,以病例为基础,以问题为导向布置课前预习内容,联合影像后处理技术在教学查房中以导向问题为主线实施教学培训,与传统教学方法相比评价教学效果.结果 PBL联合影像...     

高危型HPV及阴道镜检查136例ASC-US患者

目的 探讨高危型HPV(HR HPV)、阴道镜在无明确诊断意义的非典型鳞状上皮细胞(ASC-US)处理中的作用.方法 对液基细胞学(LCT)检测为ASC-US的136例患者,采用HC-2 检测HR HPV、阴道镜下行宫颈活检.结果 136例ASC-US患者,宫颈活检病理:宫颈炎80例;宫颈上皮内瘤变(CIN)56例,其中CIN I 35例、CINⅡ 14例、CINⅢ 5例、宫颈鳞癌(SCC)2例,其中CINⅡ及CINⅢ占33.9%.阴道镜拟诊宫颈病变76例(55.9%),与病理诊断符合34例:其中CINI 25例、CINⅡ 3例、CINⅢ 5例、SCC 1例,符合率43.4%.HR HPV阳性者86例(63.2%),其中CINⅡ、CINⅢ共17例(19.8%).结论 HR HPV检测、阴道镜下多点活检是处理ASC-US的正确方法.     

皮肤感觉神经与创面组织相互作用的研究

【摘要】皮肤感觉神经对创面愈合过程中的炎性介质反应、新血管形成、肉芽增生和愈合后重塑均有重要调控作用,同时创面的组织细胞又能反作用于皮肤感觉神经。对皮肤感觉神经的合理干预能够有效改善创面的转归。     

应用Heath-Carter法分析辽宁汉族成人的体型特征

目的:了解辽宁汉族成人的体型特征.方法:应用Heath-Carter法对1497名(男745名,女752名)辽宁汉族成人进行体型特征分析.结果:辽宁汉族成人男性平均体型值为4.6-4.5-1.5,属内胚层-中胚层均衡体型,女性平均体型值为6.2-3.9-1.3,属偏中胚层的内胚层体型;辽宁汉族成人体型的性别差异表现为女...     

睡眠呼吸暂停综合征患者的睡眠分期算法研究

针对可穿戴睡眠监测缺乏有效的自动睡眠分期和睡眠质量评价方法这一问题,提出一种适用于睡眠呼吸暂停综合征患者的自动睡眠分期方法。通过心电图R-R间期序列,分别得到心率变异性、呼吸幅度变异性和呼吸率变异性信号。以此为基础,提取时域、频域及非线性特征共55个。利用门控循环单元网络,分别构建清醒-睡眠二分类、清醒-快速眼动-非快速眼动睡眠三分类、清醒-快速眼动-浅睡-慢波睡眠四分类、清醒-快速眼动-非快速眼动Ⅰ-Ⅱ-Ⅲ期五分类等共4个不同分类粒度的睡眠分期模型;采用损失函数类别加权方法,有效降低数据非平衡对分期结果的影响。验证数据来自SHRS数据库的274例患者。借助准确率、Cohen's Kappa系数和睡眠结构指标对该睡眠分期方法进行性能评价。结果表明4个分类器的准确率分别为85.06%、75.44%、63.80%、62.13%,Cohen's Kappa系数达到了0.54、0.49、0.41、0.41,睡眠结构分析评估与临床结果之间的差异无统计学意义。所提出的方法基本满足睡眠质量评估的需求,适用于可穿戴睡眠监测应用。