脑梗死患者血小板四项参数的变化及其意义

脑组织因血管阻塞而引起缺血性坏死或软化即为脑梗死．引起脑梗死的原凶有血管阻塞及脑部血液循环障碍两大类。血小板具黏附、聚集特性．在止血和血栓形成过程中占有相当重要的地位,血小板参数的变化亦是血液凝固的重要凶素之一。为探讨血小板计数（PLT）、平均血小板体积（MPV）、血小板分布宽度（PDW）、大血小板比率（P-LCR）四项参数在脑梗死患者中的变化及临床意义．本研究测定了脑梗死、短暂性脑缺血发作患者血小板四项指标,并与正常组进行比较、分析．现报告如下。[第一段]     

川崎病血小板四项参数及血液流变学变化与冠状动脉病变的关系

目的通过研究川崎病患儿血小板参数及血液流变学指标的变化,探讨血小板异常在冠状动脉病变发生、发展中的作用。方法选择年龄及性别相匹配的48例川崎病伴冠状动脉病变患儿及46例川崎病无冠状动脉病变患儿,另选49名健康儿为对照组,患儿于诊断明确后立即采血,健康儿与患儿同时采血,分别测血小板参数及血液流变学指标,每次采血后均在2 h内完成全部指标测定。结果冠状动脉病变组及无冠状动脉病变组血小板数目高于正常对照组(P0.01),以冠状动脉病变组增高更为明显,冠状动脉病变组及无冠脉病变组血小板压积、平均血小板体积、血小板分布宽度均高于正常对照组(P0.05或0.01),以冠状动脉病变组增加更为明显。冠状动脉病变组及无冠状动脉病变组全血黏度高切、低切,血浆黏度,红细胞压积,红细胞聚集指数,血沉,血沉方程K值均高于正常对照组(P0.05或P0.01),以冠状动脉病变组更为明显。结论血小板功能亢进和高血黏滞状态在川崎病冠状动脉病变的发生、发展中起很重要的作用。血液黏稠度可能与川崎病冠状动脉病变的严重程度有关,如能早期改善血小板功能及血液流变学紊乱,可预防川崎病冠状动脉损害与发展。     

应用 CLSI EP10-A2文件对 DXI800化学发光仪性能评价的结果分析

目的：应用CLSI EP10-A2文件初步评价DXI800化学发光仪的分析性能。方法严格按照 EP10-A2文件要求,连续5 d按特定顺序测定高、中、低浓度质控血清中的人生长激素（hG H ）浓度,采用 Excel软件计算hG H测定的偏差、总不精密度及每天的多元回归分析参数（即截距、斜率、非线性、携带污染率及漂移度）。结果当质控血清hGH浓度为2．15、5．47、10．80 mmol/L时,hGH测定值与靶值间线性良好（Y ＝0．992X＋0．083,r2＝0．978）;偏差分别为0．066、0．265、0．055 mmol/L ;总不精密度分别为6．57％、8．53％、4．56％;采用单样本 t检验,每个多元回归分析参数5 d的值与其预测值相比,差异均无统计学意义（ P＞0．05）。结论 DXI800化学发光仪测定hG H ,其偏差及总不精密度均在允许范围内,线性关系良好,携带污染率较低,稳定性良好,能满足临床及科研需求。     

利用校准周期图建立日立7600生化仪检测系统校准周期

目的利用校准周期图建立日立7600生化仪检测系统校准周期。方法利用校准周期图,更换试剂后对日立7600生化仪检测系统进行校准,每2 h检测一批质控血清,每批3种水平,每个水平做4次重复检测,以累积CV小于CLIA′88允许误差的1/6作为评价标准。结果肌酐从校准后8 h即有低水平的质控血清累积CV>2.59,其校准周期最短,ISE离子类校准周期每12 h需要校准一次,酶类校准周期可达30 d以上。结论在确立检测系统的校准周期时,一定要选用接近于检测下限的质控血清,选用高浓度的质控血清可能会造成确立的校准周期过长。     

Evaluation of the detection ability of uropathogen morphology and vaginal contamination by the Atellica UAS800 automated urine microscopy analyzer and its effectiveness

BackgroundTo help combat the worldwide spread of multidrug‐resistant Enterobacterales, which are responsible for many causes of urinary tract infection (UTI), we evaluated the ability of the Atellica UAS800 automated microscopy system, the only one offering the capability of bacterial morphological differentiation, to determine its effectiveness.MethodsWe examined 118 outpatient spot urine samples in which pyuria and bacteriuria were observed using flow cytometry (training set: 81; cross‐validation set: 37). The ability of the Atellica UAS800 to differentiate between bacilli and cocci was verified. To improve its ability, multiple logistic regression analysis was used to construct a prediction formula.ResultsThis instrument''s detection sensitivity was 106 CFU/ml, and reproducibility in that range was good, but data reliability for the number of cocci was low. Multiple logistic regression analysis with each explanatory variable (14 items from the Atellica UAS800, age and sex) showed the best prediction formula for discrimination of uropathogen morphology was a model with 5 explanatory variables: number of bacilli (p < 0.001), squamous epithelial cells (p = 0.004), age (p = 0.039), number of cocci (p = 0.107), and erythrocytes (p = 0.111). For a predicted cutoff value of 0.449, sensitivity was 0.879 and specificity was 0.854. In the cross‐validation set, sensitivity was 0.813 and specificity was 0.857.ConclusionsThe Atellica UAS800 could detect squamous epithelial cells, an indicator of vaginal contamination, with high sensitivity, which further improved performance. Simultaneous use of this probability prediction formula with urinalysis results may facilitate real‐time prediction of uropathogens and vaginal contamination, thus providing helpful information for empiric therapy.