PINP在诊断骨质疏松症中的应用

目的 探讨用于诊断骨质疏松症的较敏感生化指标。方法 采用放免法测定46例骨质疏松性骨痛。34例非重力骨折及24例健康者血PINP水平和其它相关指标。结果 骨痛和骨折两组患者PINP水平均明显高于正常对照组(P<0.01);PINP与其它骨形成指标有较好相关性。结论 PINP由于在血循环中较稳定,可作为诊断骨质疏松症的较敏感指标。     

判断误诊的相对标准

判断误诊与否,需要有一个相对的标准,参阅现有误诊文献及对误诊断作的理论研究,作者提出如下判断误诊的标准：首先,误诊必须是经过医生诊断过程一所做出的与疾病本质不一致的结论,其二,不能以时间长短作为判定误诊与否的惟一标准,只要作出与疾病本质不一致的诊断,不论是否导致不良后果,均应视作误诊。     

朱砂安神丸高效液相色谱数字化指纹图谱研究

目的建立朱砂安神丸(Zhusha Anshen Wan,ZSASW)HPLC数字化指纹图谱,作为其整体质量控制的一个判据标准。方法采用反相HPLC法,使用Century SIL C18BDS柱(200 mm×4.6 mm,5μm),以0.2%H3PO4溶液(A)-0.1%H3PO4乙腈溶液(B)为流动相进行梯度洗脱(0~10 min,0→15%B;10~30 min,15%→30%B;30~50 min,30%→70%B;50~60 min,70%→85%B),流速1.0 mL.min-1,检测波长203 nm,柱温(30±0.15)℃,进样量5μL。以色谱指纹图分离量指数(chromatographic fingerprint resolution index,RF)为目标函数优化试验条件,用"中药色谱指纹图谱超信息特征数字化评价系统3.0"软件进行数字化评价。结果以盐酸小檗碱(berberine hydrochloride,BBR)为参照物峰,确定57个共有指纹峰,获得判别其质量的重要数字化信息,以系统指纹定量法鉴别出S1、S2、S3、S4、S9和S12质量极好,S5、S6和S10质量很好,S11质量好,S7和S8质量为劣。结论所建立的ZSASW-HPLC数字化指纹图谱可清晰反映ZSASW的局部和整体指纹的质量变异,用数字化指纹图谱控制中药质量准确可行。     

男性不育患者精液质量指标和精浆电解质浓度的测定与分析

目的探讨男性不育患者精液质量指标以及精浆电解质的变化。方法所有病例均选自男科门诊。分为：（1）延迟液化组（B组）20例;（2）少精子组（C组）34例;（3）无精子组（D组）15例;选择正常生育健康志愿者对照组（A组）17例。分别测定各组精液质量指标和精浆中钾、钠、钙、氯等离子浓度。结果延迟液化组和少精子组在精子密度、精子计数精子活动度及精子活动性低于正常生育组;各组精浆电解质K^＋、Na^＋、Ca^2＋、Cl^-浓度比较,差异有统计学意义。结论男性不育患者与健康正常组相比,精液质量指标有显著变化,精浆K^＋、Na^＋、Ca^2＋、Cl^-差异有统计学意义。     

应用ROC曲线制定XE-2100血液分析仪的白细胞分类复检标准

目的 应用ROC曲线分析建立XE-2100血液分析仪白细胞分类（difference of cell,DC）的复检标准。方法以手工法为金标准,对416份患者分别进行仪器和手工计数分类,对仪器结果进行判断,应用ROC（receiver operating characteristic curve）建立DC的复检标准,并评价复检标准。结果白细胞分类的复检标准为中性粒细胞（N）〉75％、淋巴细胞（L）〉45％、嗜酸性粒细胞（Eo）〉10％、嗜碱性粒细胞（B）〉2％、单核细胞（M）〉13％;血细胞形态异常：原始细胞（Blast）或异常淋巴细胞（Alan-BL）报警且研究参数other〉2％、或变异淋巴（Atypical Ly）报警且L≥50％且M≥13％,IG报警且研究参数IG〉3％、NRBC（有核红细胞）报警且N≥2个／100WBC。结论仪器对M、B、血细胞形态异常的报警提示较为敏感,建立适当的复检标准可以减少白细胞分类的复检率,提高实验室的工作效率。     

睡眠障碍的诊断标准与方法

目的了解近年来国内外睡眠障碍的诊断标准与方法的研究进展及动态。方法以近年来国内外有关睡眠障碍的研究成果为基础,采用文献研究法分析与总结有关研究。结果呈现出有关睡眠障碍的诊断标准与方法的研究进展及动态。结论加强针对不同类型睡眠障碍的治疗方法的研究对预防及治疗睡眠障碍具有深远意义。     

医疗设备租赁在军队等级医院评审中的作用研究

介绍了通过建立日常医疗设备租赁制度健全医疗设备应急调配体制的做法和经验,从对检查标准和细则的理解、扣分项目等角度,结合实际检查过程探讨医疗设备租赁制度在军队等级医院评审中的作用和体会.     

A Bayesian semiparametric model for bivariate sparse longitudinal data

Mixed‐effects models have recently become popular for analyzing sparse longitudinal data that arise naturally in biological, agricultural and biomedical studies. Traditional approaches assume independent residuals over time and explain the longitudinal dependence by random effects. However, when bivariate or multivariate traits are measured longitudinally, this fundamental assumption is likely to be violated because of intertrait dependence over time. We provide a more general framework where the dependence of the observations from the same subject over time is not assumed to be explained completely by the random effects of the model. We propose a novel, mixed model‐based approach and estimate the error–covariance structure nonparametrically under a generalized linear model framework. We use penalized splines to model the general effect of time, and we consider a Dirichlet process mixture of normal prior for the random‐effects distribution. We analyze blood pressure data from the Framingham Heart Study where body mass index, gender and time are treated as covariates. We compare our method with traditional methods including parametric modeling of the random effects and independent residual errors over time. We conduct extensive simulation studies to investigate the practical usefulness of the proposed method. The current approach is very helpful in analyzing bivariate irregular longitudinal traits. Copyright © 2013 John Wiley & Sons, Ltd.     

fMRI investigation of speed-accuracy strategy switching

Switching between rapid and accurate responses is an important aspect of decision-making. However, the brain mechanisms important to smoothly change the speed-accuracy strategy remain mostly unclear. This issue was addressed here by using functional magnetic resonance imaging (fMRI). On each trial, right-handed healthy participants had to stress speed or accuracy in performing a color discrimination task on a target stimulus according to the instructions given by an initial cue. Participants were capable of trading speed for accuracy and vice versa. Analyses of cue-related fMRI activations revealed a significant recruitment of left middle frontal gyrus and right cerebellum when switching from speed to accuracy. The left superior parietal lobule was activated in the same switching condition but only after the target onset. The anterior cingulate cortex was more recruited, also after target presentation, when speed had to be maintained from one trial to the next. These results are interpreted within a theoretical framework that attributes a role in criterion-setting to the left lateral prefrontal cortex, perceptual evidence accumulation to the superior parietal lobule, and action energization to the anterior cingulate cortex, extending previous findings to the domain of speed-accuracy tradeoff regulations.