神经内镜手术与小骨窗开颅手术治疗高血压脑出血疗效对比的回顾性研究

摘要 目的：回顾性对比神经内镜手术与小骨窗开颅手术治疗高血压脑出血（HICH）疗效。方法：回顾性选取2018年7月~2021年3月期间在联勤保障部队第909医院治疗的83例HICH患者的临床资料。根据手术方式的不同,将患者分为A组（n=41）和B组（n=42）,A组患者采用小骨窗开颅手术治疗,B组患者采用神经内镜手术治疗,对比两组围术期指标、并发症发生率、神经功能、生活能力、神经损伤指标及预后。结果：与A组相比, B组的手术时间、住院时间明显缩短,术中出血量减少,血肿清除率升高（P<0.05）。B组术后1周美国国立卫生研究院卒中量表（NIHSS）评分低于A组,Barthel指数评分高于A组（P<0.05）。B组术后1周神经元特异性烯醇化酶（NSE）、S100B 蛋白（S100B）、髓鞘碱性蛋白（MBP）、胶质纤维酸性蛋白（GFAP）水平低于A组（P<0.05）。B组的并发症发生率小于A组（P<0.05）。B组的预后良好率高于A组（P<0.05）。结论：神经内镜手术、小骨窗开颅手术治疗HICH均可获得较好的疗效,其中神经内镜手术在缩短手术时间、住院时间,减少术中出血量和并发症发生率,提高血肿清除率,减轻神经功能损伤,促进患者生活能力改善,改善患者预后方面的效果更为显著。     

Plasma N-glycome composition associates with chronic low back pain

Background

Low back pain (LBP) is the symptom of a group of syndromes with heterogeneous underlying mechanisms and molecular pathologies, making treatment selection and patient prognosis very challenging. Moreover, symptoms and prognosis of LBP are influenced by age, gender, occupation, habits, and psychological factors. LBP may be characterized by an underlying inflammatory process. Previous studies indicated a connection between inflammatory response and total plasma N-glycosylation. We wanted to identify potential changes in total plasma N-glycosylation pattern connected with chronic low back pain (CLBP), which could give an insight into the pathogenic mechanisms of the disease.

肝炎后肝硬化患者肝癌发生的保护因素与危险因素研究

目的:通过回顾性病例对照研究,探讨多种因素在病毒性肝炎后肝化门静脉高压症患者HCC发生过程中的作用以及脾切除是否抑制了肝癌的发生进程。方法:收集第四军医大学西京医院病案统计室检索2002年1月～2008年12月之间出院诊断为病毒性肝炎后(HBV/HCV)肝硬化门脉高压的病例2300余例,收集所有病例的一般资料,临床及实验室检查数据,影象学检查结果,以及在治疗过程中的脾切除手术史。采用病例对照,按年龄、性别两个指标进行1:1配对,根据研究对象是否合并HCC将其分为合并HCC组(组1),未合并HCC组(组2),采用SPSS17.0进行单因素分析及多因素logistic回归分析。结果:描述性统计结果显示,两组的ALB、AST、TP、ALP、GGT等差异有统计学意义(P<0.05),而PLT、ALT、TBIL等在两组间差异无统计学意义(P>0.05)。将单因素分析有意义的研究因素纳入多因素logistic回归方程得知,AST、ALP、GGT异常升高增加了肝癌发生的危险性,而行脾切除和门奇断流术明显降低了肝癌发生的危险性,仅为无手术患者肝癌发生危险性的57.1%(OR:0.571,95%CI:0.394～0.825)。...     

54例慢性淋巴细胞白血病的临床回顾性分析

目的：本研究旨在探讨慢性淋巴细胞白血病（CLL）的实验室检查特点及特征性临床表现。方法：利用血细胞分析仪、流式细胞术、骨髓形态分析及R显带技术等对我院2002年4月．2012年4月收治的54例慢性淋巴细胞白血病患者的相关临床资料如血细胞计数、骨髓形态、染色体及免疫表型等进行检测并对结果进行回顾性分析。结果：CLL多发于老年患者,男性多见,中位年龄65岁（45．82岁）。大部分患者初诊时可出现典型的临床表现,37例（68％）患者初诊时淋巴结大,49例（91％）初诊时白细胞≥10×109、L,淋巴细胞绝对值≥5×109／L。13例（24％）初诊时肝脾或者脾大,17例（31％）初诊时乏力、消瘦。34（63％）例患者可见典型的CLL免疫表型,CD5、CDl9．CD23、CD20的阳性率分别为90％、87％、72％、67％。32例患者染色体检测结果表明：13q-2例,17p．2例,11q-1例,＋12有1例,6q-1例,t（14,16）1例。2例患者发生了自身免疫性溶血性贫血（AIHA）。1例患者发生了Richter转化,肿大淋巴结活检显示部分区域为弥漫性大B细胞淋巴瘤,其高表达CD20、CDl9、CD22。结论：慢性淋巴细胞白血病具有其典型的临床表现、免疫表型及遗传学改变,并且对诊断及治疗有重要意义。     

Logistic Bayesian LASSO for identifying association with rare haplotypes and application to age-related macular degeneration

Rare variants have been heralded as key to uncovering "missing heritability" in complex diseases. These variants can now be genotyped using next-generation sequencing technologies; nonetheless, rare haplotypes may also result from combination of common single nucleotide polymorphisms available from genome-wide association studies (GWAS). The National Eye Institute's data on age-related macular degeneration (AMD) is such an example. Studies on AMD had identified potential rare variants; however, due to lack of appropriate statistical tools, effects of individual rare haplotypes were never studied. Here we develop a method for identifying association with rare haplotypes for case-control design. A logistic regression based retrospective likelihood is formulated and is regularized using logistic Bayesian LASSO (LBL). In particular, we penalize the regression coefficients using appropriate priors to weed out unassociated haplotypes, making it possible for the rare associated ones to stand out. We applied LBL to the AMD data and identified common and rare haplotypes in the complement factor H gene, gaining insights into rare variants' contributions to AMD beyond the current literature. This analysis also demonstrates the richness of GWAS data for mapping rare haplotypes-a potential largely unexplored. Additionally, we conducted simulations to investigate the performance of LBL and compare it with Hapassoc. Our results show that LBL is much more powerful in identifying rare associated haplotypes when the false positive rates for both approaches are kept the same.     

Sampling for conditional inference on case-control data

The problem of exact conditional inference for discrete multivariate case-control data has two forms. The first is grouped case-control data, where Monte Carlo computations can be done using the importance sampling method of Booth and Butler (1999, Biometrika86, 321-332), or a proposed alternative sequential importance sampling method. The second form is matched case-control data. For this analysis we propose a new exact sampling method based on the conditional-Poisson distribution for conditional testing with one binary and one integral ordered covariate. This method makes computations on data sets with large numbers of matched sets fast and accurate. We provide detailed derivation of the constraints and conditional distributions for conditional inference on grouped and matched data. The methods are illustrated on several new and old data sets.     

Optimal sampling in retrospective logistic regression via two-stage method

Case-control sampling is popular in epidemiological research because of its cost and time saving. In a logistic regression model, with limited knowledge on the covariance matrix of the point estimator of the regression coefficients a priori, there exists no fixed sample size analysis. In this study, we propose a two-stage sequential analysis, in which the optimal sample fraction and the required sample size to achieve a predetermined volume of a joint confidence set are estimated in an interim analysis. Additionally required observations are collected in the second stage according to the estimated optimal sample fraction. At the end of the experiment, data from these two stages are combined and analyzed for statistical inference. Simulation studies are conducted to justify the proposed two-stage procedure and an example is presented for illustration. It is found that the proposed two-stage procedure performs adequately in the sense that the resultant joint confidence set has a well-controlled volume and achieves the required coverage probability. Furthermore, the optimal sample fractions among all the selected scenarios are close to one. Hence, the proposed procedure can be simplified by always considering a balance design.     

Potential impact of harvesting on the population dynamics of two epiphytic bromeliads

Large numbers of epiphytes are extracted from cloud forests for ornamental use and illegal trade in Latin America. We examined the potential effects of different harvesting regimes on the population dynamics of the epiphytic bromeliads Tillandsia multicaulis and Tillandsia punctulata. The population dynamics of these species were studied over a 2-year period in a tropical montane cloud forest in Veracruz, Mexico. Prospective and retrospective analyses were used to identify which demographic processes and life-cycle stages make the largest relative contribution to variation in population growth rate (λ). The effect of simulated harvesting levels on population growth rates was analysed for both species. λ of both populations was highly influenced by survival (stasis), to a lesser extent by growth, and only slightly by fecundity. Vegetative growth played a central role in the population dynamics of these organisms. The λ value of the studied populations did not differ significantly from unity: T. multicaulis λ (95% confidence interval) = 0.982 (0.897–1.060) and T. punctulata λ = 0.967 (0.815–1.051), suggesting population stability. However, numerical simulation of different levels of extraction showed that λ would drop substantially even under very low (2%) harvesting levels. Matrix analysis revealed that T. multicaulis and T. punctulata populations are likely to decline and therefore commercial harvesting would be unsustainable. Based on these findings, management recommendations are outlined.