我国特殊蛋白质检验指标允许总误差和允许不精密度的初步研究

目的初步探讨如何通过室间质量评价(EQA)和室内质量控制(IQC)数据,结合米兰会议最新确定的性能规范设定模式,为我国特殊蛋白质各检验指标推荐允许总误差(TEa)和允许不精密度(允许CV)。方法采用基于Web方式的EQA软件,收集参加国家卫生与计划生育委员会临床检验中心2015年第1次全国特殊蛋白质指标EQA活动的925家实验室数据以及上报当月IQC结果的742家实验室数据。用Excel 2010和SP_SS 19.0软件分别统计Ig A、Ig G、Ig M、补体3(C3)、补体4(C4)、C反应蛋白(CRP_)、类风湿因子(RF)、转铁蛋白、前清蛋白、Ig E、抗链球菌溶血素O(ASO)共11个指标的EQA数据,按批号计算每个实验室的"百分差值"及其P_10、P_90。分别统计11个指标的IQC数据,按批号计算所有实验室"在控变异系数(CV)"的P_80。前9个指标的EQA"百分差值"和IQC"在控CV"分别与基于生物学变异推导出的TEa和允许CV进行比较。结果 EQA数据显示,仅转铁蛋白、Ig E和ASO 3个指标采用基于当前技术水平推导出的TEa(分别为9.38%、12.02%和9.92%)作为各自TEa的推荐标准;其他指标均有80%以上的实验室达到基于生物学变异推导出的TEa的要求,可用基于生物学变异推导出的TEa作为推荐标准。IQC数据显示,CRP_和前清蛋白指标有80%以上实验室分别满足基于生物学变异推导出的最佳和适当水平允许CV的要求,而其他指标均不足80%的实验室满足基于生物学变异推导出的最低水平允许CV的要求,进而除CRP_和前清蛋白指标外,其他指标均使用基于当前技术水平推导出的允许CV作为推荐标准。结论初步研究了我国特殊蛋白质检验指标在当前技术水平下所能达到的性能水平,并为各指标推荐符合我国现状的TEa和允许CV。     

生物学变异允许总误差在血脂检测中的质量管理

目的探讨生物学变异允许总误差在血脂检测中的质量管理。方法对2015年参加原卫生部脂类正确度验证的胆固醇(CHOL)、三酰甘油(TG)、高密度脂蛋白(HDL-C)、低密度脂蛋白(LDL-C)进行σ分值、质量目标指数(QGI)、优先改进措施及性能评定等指标进行评价,对成绩不理想的CHOL作原因分析。结果生物学变异设定的质量规范3个层次,当允许总误差处于适当的水平时,TG、HDL-C、LDL-C的σ分值已满足6,无需改进。而CHOL的分析性能为差,需优先改进正确度。当允许总误差处于最佳水平时,4个项目中只有TG的σ分值可达到良,可进行精密度改进。当允许总误差处于最低水平时,TG、HDL-C、LDL-C的σ分值远大于6,分析性能达到优,CHOL的σ分值(2.9)已接近3σ水平,应从正确度进行纠正。结论 6σ质量理论可反映检测项目的性能,且能有效提高分析质量。     

上海市23项临床化学检验项目的允许误差范围

目的调查分析上海市二、三级医院，23项临床化学检验在常规条件下的变异系数(RCV)现状。探讨今后上海地区临床化学室内质量控制的要求。方法按美国CLIA’88可接受范围的四分之一作为上海地区拟推荐要求。对上海市2003年147家临床实验室23项常规临床化学3570336个室内质量控制数据进行整理和统计分析，计算出各项目变异系数(CV)百分位数的均数，与卫生部1985年推荐的RCV的统计分析结果进行比较。结果上海地区138家临床实验室(占94．0％)CV小于卫生部1985年推荐的RCV，约有111家临床实验室(占75．5％)符合上海地区拟推荐的要求。结论拟定的推荐要求基本适宜，不仅可被临床接受，而且已有75．5％单位符合要求，但尚有24．5％单位须努力才能达到要求。     

上海地区肿瘤标志物室间质量评价中允许总误差适宜性的探讨

目的分析上海地区肿瘤标志物室间质评的方法变异及实际允许误差范围,并比较与不同国际标准及生物学变异要求提供的允许总误差(TEa)的差异,探讨上海地区肿瘤标志物TEa设置对当前分析质量水平的适宜性。方法以上海市2010至2012年的肿瘤标志物室间质量评价的数据为基础,计算不同方法组在6次室间质评计划中30个样本的合成变异系数(CV),根据合成CV计算上海地区肿瘤标志物室间质评的实际TEa,比较其与德国Rilibak质控指南、澳大利亚皇家病理学会(RCPA)质量要求和生物学变异数据合成的TEa的差异。结果在6次室间质评计划中,血清甲胎蛋白(AFP)、癌胚抗原(CEA)、糖类抗原(CA)125、CA153、CA19-9、前列特异性抗原(PSA)的实际TEa分别为22.63%、22.43%、19.30%、21.56%、27.43%和19.55%,与Rilibak的TEa比较接近,能达到生物学变异数据合成的适合水平的TEa要求,但高于RCPA的TEa范围。结论上海地区的肿瘤标志物室间质评计划的实际TEa水平接近或符合德国Rilibak的要求,略低于比较严格的澳大利亚RCPA的TEa要求,TEa设置方法能够满足当前的质量水平分析。     

Error budget calculations in laboratory medicine: linking the concepts of biological variation and allowable medical errors

BACKGROUND: Random, systematic and sporadic errors, which unfortunately are not uncommon in laboratory medicine, can have a considerable impact on the well being of patients. Although somewhat difficult to attain, our main goal should be to prevent all possible errors. A good insight on error-prone steps in the laboratory process is essential to achieving a structured system for error reduction. METHODS: Here, the process of laboratory medicine is divided into phases, and for each phase, an error frequency is presented. While error frequencies in the laboratory (pre-analytical to post-analytical) have been reported elsewhere, we also include them in the present paper. In order to investigate error frequencies in the pre-pre- and post-post-analytical phases, clinicians were asked to carefully answer questions concerning their ordering strategies for laboratory investigation and their interpretation of results. RESULTS: In the present study, the overall error rate in laboratory medicine was found to be 20.0%. The error percentages in the pre-pre- and post-post-analytical phase were about 12.0% and 5.0%, respectively. This indicates that, also on the clinical side, error reduction is desirable, especially in the requesting of laboratory investigation. Error reduction can be achieved through process redesigning by, for example, applying the Hazard Analysis and Critical Control Points approach. The error budget that clinicians might spend, based upon critical differences, is 26.9%. For the same test set and production circumstances, the overall biological variation is 7.9%. Clinicians thus take the error rates into account in their practical, daily use, and the ultimate achievable in laboratory medicine is biological variation. CONCLUSIONS: Several currently available software applications can aid error reduction in clinical chemistry. Both laboratory consultants and the use of information and communication technology are essential tools in optimizing the efficiency of laboratory medicine.     

不同允许总误差在特定蛋白检测性能评价与质量控制规则选择中的应用

目的评估不同国际标准提供的允许总误差(TEa)下特定蛋白检测的分析性能差异,运用6西格玛(σ)参数选择和优化质量控制规则。方法收集2009和2010年的室内质量控制数据以及参加卫生部临床检验中心的能力比对实验的数据,计算各检测项目的不精密度和偏倚(Bias)。TEa分别引用美国临床试验室修正法案(CLIA’88)、德国Rilibak质控指南以及生物学变异的要求。根据变异系数(CV)、Bias和TEa计算σ值,同时绘制标准化σ性能评价图。计算未达6σ的质量目标指数(QGI),查找导致性能不佳的主要原因,以判断优先改进精密度或准确度。结果 2009年IgA、IgG、IgM、C3、C4、C反应蛋白(CRP)6个检测项目根据3种不同的TEa要求计算的σ水平从0.53～6.95不等,除生物学变异要求下的CRPσ值为6.95,其余均未达到6σ。2010年6个项目的σ水平从1.33～29.39不等,除IgG项目和生物学变异要求下的IgA和C3未达到6σ要求外,其余均达到了6σ要求。结论根据σ水平可以评价实验室的分析性能并选择室内质量控制规则,经济合理的开展室内质量控制。     

Analytical quality goals for parathyroid hormone based on biological variation

BACKGROUND: Measurement of parathyroid hormone (PTH) is central in the investigation of pathologies of bone and mineral ion metabolism. Knowledge of the biological variation of an analyte forms an essential part of evaluating a new analyte, enabling the objective assessment of changes in serial results and the utility of reference intervals, as well as establishing laboratory quality specifications. METHODS: This study determined the biological variation of PTH in 20 healthy individuals, which was calculated according to the familiar methods outlined by Fraser and Harris. RESULTS: The within-subject variation was 25.3% and the between-subject variation was 43.4%. The critical difference for sequential values significant at p<0.05 was calculated as 72%. The within-subject variation forms a relatively small part of the reference interval, shown by the low index of individuality of 0.58. Objective analytical quality goals have also been established, revealing achievable optimum performance for imprecision of approximately 6%. The desirable analytical bias goal was approximately 12%. CONCLUSIONS: This study has objectively shown that the analytical precision of current instruments is being achieved contrary to the known problems surrounding the analytical bias for PTH assays. The limitations of using reference intervals for PTH, both in diagnoses and monitoring, are shown.     

Analytical goals for coagulation tests based on biological variation.

Allowable imprecision and bias reference limits for laboratory data can be calculated based on measurements of biological variation. Although biological variation of clinical chemical data has been reported from many laboratories, there have been few reports of biological variation in coagulation tests. In this study, we calculated the biological variation of 13 coagulation tests in the clinical laboratory of Kyushu University Hospital and determined allowable imprecision and bias limits of variation. The participating subjects were 17 healthy individuals: three males and two females in their 20s, two males and two females in their 30s, one male and four females in their 40s, and two males and one female in their 50s. Monthly measurements were performed before breakfast 12 times from June 2001 to May 2002 and allowable imprecision and bias limits were calculated. Taken together with coefficient of variation of control plasma used in daily laboratory work at the hospital, the allowable imprecision limits of intra-laboratory variation determined in this study appear to be in attainable ranges.     

Analytical quality goals for 25-vitamin D based on biological variation

Background: Measurement of 25‐hydroxyvitamin D, (25D) is central in the investigation of pathologies of bone and mineral ion metabolism and in determining a patient's vitamin D status. More recently much research interest has lead to investigating the role it can play in decreasing the risk of many chronic illnesses, including common cancers, autoimmune diseases, infectious diseases, and cardiovascular disease. Knowledge of the biological variation of an analyte forms an essential part of evaluating a new analyte enabling the objective assessment of the changes in serial results, the utility of reference intervals as well as establishing laboratory quality specifications. Methods: This study determined the biological variation of 25D in 20 healthy individuals that was calculated according to the familiar methods outlined by Fraser and Harris. Results: The within‐subject variation was 12.1% and the between subject variation was 40.3%. The critical difference for sequential values significant at P<0.05 was calculated as 38.4%. The within‐subject variation forms a relatively small part of the reference interval shown by the low index of individuality of 0.3. Objective analytical quality goals have also been established which have shown achievable minimum performance for imprecision of ～6%. The desirable analytical bias goal was ～10%. Conclusion: This study has objectively shown that the analytical precision of current instruments is being achieved contrary to the known problems surrounding the analytical bias for 25D assays. The limitations of using reference intervals for 25D, both in diagnoses and monitoring are shown. J. Clin. Lab. Anal. 25:130–133, 2011. © 2011 Wiley‐Liss, Inc.     

MR image reconstruction based on framelets and nonlocal total variation using split Bregman method

Purpose

An efficient algorithm for magnetic resonance (MR) image reconstruction is needed, especially when sparse sampling is employed to accelerate data acquisition. The aim of this paper is to solve the sparse MRI problem based on nonlocal total variation (NLTV) and framelet sparsity using the split Bregman algorithm. A new method was developed and tested in a variety of MR image acquisitions.

Methods

The proposed method minimizes a linear combination of NLTV, least square data fitting and framelet terms to reconstruct the MR images from undersampled $k$ -space data. The NLTV and framelet sparsity are taken as the $L_{1}$ -regularization functional and solved by using the split Bregman method. Experiments were conducted to compare the proposed algorithm with several different reconstruction methods, including the operator splitting algorithm, variable splitting method, composite splitting algorithm and its accelerated version called the fast composite splitting algorithm. A detailed evaluation study was done on the reconstruction of MR images which represent varying degrees of object structural complexity. Both qualitative visualization-based and quantitative metric-based evaluations were done.

Results

Numerical results on various data corresponding to different sampling rates showed the advantages of the new method in preserving geometrical features, textures and fine structures. The proposed algorithm was compared with previous methods in terms of the reconstruction accuracy and computational complexity with favorable results.

Conclusion

An efficient new algorithm was developed for compressed MR image reconstruction based on NLTV and framelet sparsity. The algorithm effectively solves a hybrid regularizer based on framelet sparsity and NLTV using the split Bregman method. NLTV makes the recovered image quality sharper by preserving the edges or boundaries more accurately, and framelets often improve image quality. The comparison with alternative method yielded results that demonstrate the superiority of the proposed algorithm for compressed MR image reconstruction.     

Variability of the biological variation

A great diversity among within-subject and between-subject biological variation data is shown from previously published works. Consequently, most of the proposed applications of biological variation to set metrological goals or requirements should be revisited.     

Change detection in SAR images based on the logarithmic transformation and total variation denoising method

Noise interference and the need to process massive image data present challenges to change detection in synthetic aperture radar (SAR) images. In order to improve the change detection accuracy and decrease the processing time, this paper proposes a novel unsupervised change detection algorithm for SAR images. The logarithmic transformation is applied to transform images into the logarithmic domain, while the multiplicative noise in images is transformed into additive noise. The total variation (TV) denoising algorithm is then used to reduce image noise, and the difference operator in the logarithmic domain is employed to provide the difference image. The k-means clustering algorithm, which does not require consideration of the statistical properties of an image, is employed to cluster the difference image into two disjointed classes: changed and unchanged. The experimental results demonstrate that change detection results achieved by the proposed algorithm offer great improvement over existing algorithms in terms of objective quantitative indices and the visual effect.     

Interpretation of creatine kinase and aldolase for statin-induced myopathy: Reliance on serial testing based on biological variation

BACKGROUND: Statins are widely used drugs to reduce LDL cholesterol and risk for cardiovascular disease. Varying degrees of myopathies occur with statin use, ranging from mild myalgic symptoms alone to documented muscle damage and rhabdomyolysis. The activity of creatine kinase (CK) above a population-based reference range has been used to differentiate myalgias from documented myositic injury due to statins. However, because normal ranges for CK depend on gender, exercise, and ethnicity and are necessarily broad, it is possible for a patient to have myositic injury with a result that is within the reference range. Therefore, serial testing relative to baseline levels may be more effective in detecting mild increases in CK. METHODS: To properly interpret results of serial testing, we determined the biologic variation of CK and aldolase, another enzyme released from muscle, from biweekly blood collections for 8 weeks from 17 healthy subjects. RESULTS: Using log transformation, we calculated a reference change value of about +140% and -60% for both CK and aldolase. CONCLUSIONS: The use of calculated RCV could help to improve the detection of those statin side effects promoting variation in CK values, which must be determined in clinical studies. The clinical significance of detecting more cases of statin-induced myopathy must also be examined.     

An image space approach to Cartesian based parallel MR imaging with total variation regularization

The Cartesian parallel magnetic imaging problem is formulated variationally using a high-order penalty for coil sensitivities and a total variation like penalty for the reconstructed image. Then the optimality system is derived and numerically discretized. The objective function used is non-convex, but it possesses a bilinear structure that allows the ambiguity among solutions to be resolved technically by regularization and practically by normalizing a pre-estimated norm of the reconstructed image. Since the objective function is convex in each single argument, convex analysis is used to formulate the optimality condition for the image in terms of a primal-dual system. To solve the optimality system, a nonlinear Gauss-Seidel outer iteration is used in which the objective function is minimized with respect to one variable after the other using an inner generalized Newton iteration. Computational results for in vivo MR imaging data show that a significant improvement in reconstruction quality can be obtained by using the proposed regularization methods in relation to alternative approaches.     

A next generation enzymatic magnesium assay on the Abbott ARCHITECT chemistry system meets performance goals based on biological variation

ObjectiveTo evaluate the performance of the Abbott ARCHITECT enzymatic assay for magnesium (3P68) in serum/plasma and urine against analytical goals based on biological variation.MethodsAnalytical performance was evaluated according to CLSI protocols. Precision was examined using commercial chemistry controls. Accuracy was assessed against NIST SRM 956c, electrolytes in human serum. Correlation with the arsenazo Mg assay (7D70) was completed using patient samples (plasma, N = 101; urine, N = 90). Common interferences were examined in pooled patient specimens with high and low magnesium concentrations.ResultsThe enzymatic Mg assay displayed imprecision of 1.7% at 0.72 mmol/L and 1.4% at 1.80 mmol/L (20 days, one calibration, one reagent lot). The linear range was verified between 0.18–7.0 mmol/L (plasma) and 0.01–10.69 mmol/L (urine). Results of the enzymatic assay (x) correlated well with the predicate assay (y) with the relationships y = 0.891x + 0.035, R = 0.967 (plasma) and y = 1.181x + 0.086, R = 0.997 (urine). Mean bias of the NIST SRM 956c samples was − 1.4%. This method showed minimal interference by hemoglobin (3 g/L as hemolysate), lipemia (20 g/L Intralipid), unconjugated bilirubin (531 μmol/L), and ascorbate (680 μmol/L).ConclusionsThe ARCHITECT Magnesium assay 3P68 achieved the desirable analytical quality specification of 4.8% for total allowable error. In comparison to the 7D70 assay, notable improvements are seen in precision, 30-day calibration stability, and minimal interference by hemolyzed and lipemic samples.     

Influence of carbon monoxide leaks on the measurement error of total haemoglobin mass

Total haemoglobin mass (Hb(mass)) can be assessed with low measurement error using carbon monoxide (CO) rebreathing. However, variability in measurement error of Hb(mass) has been reported across laboratories and it has previously been suggested that CO leaks contribute to this variability. As a result of employing a standardized leak monitoring procedure using two CO detectors, we were able to retrospectively examine the impact of CO leaks on Hb(mass) values from past test-retest studies in our laboratory using the optimized CO rebreathing method. Test-retest data were collected to determine measurement error, with subjects tested twice within 5 days. Test-retest data were placed into separate categories based on magnitude and duration of CO leak observed during one of the two tests. The No Leak category contained test-retest data in which no leak occurred during either test. The Minor Leak category contained test-retest data in which one of the tests had a CO leak of magnitude less than 30 ppm and less than 5 seconds duration, whereas the Major Leak category included test-retest data in which a leak greater than this magnitude or duration occurred. Measurement error was lowest in the No Leak category (1.9%; 95%CI: 1.6-2.3%; n = 56), approximately doubled in the Minor Leaks category (3.6%; 95%CI: 2.6-6.1%; n = 13), and dramatically increased in the Major Leaks category (9.3%; 95%CI: 6.3-17.6%; n = 10). We recommend careful monitoring of potential CO leaks using multiple detectors. To minimize measurement error, tests in which any CO leak is detected should be excluded.     

The reference change value: a proposal to interpret laboratory reports in serial testing based on biological variation

BACKGROUND: A proposal to calculate and use the reference change value (RCV) as an objective guide for interpreting the numerical results obtained in clinical laboratory serial testing is introduced in this study. METHODS: A database showing the results of a compilation of 191 publications on biological variation and including information on a number of analytes provided the standardized criterion based on biology for calculating the RCVs. RESULTS: For each of the 261 analytes included in the study, the RCV was determined using Harris's formula, replacing analytical imprecision with the desirable specification of analytical quality based on half the within-subject biological variation at 95% probability levels. The result is a guide for a common criterion to identify clinically significant changes in serial results. CONCLUSIONS: The RCV concept is an approach that can be offered by laboratories to assess changes in serial results. The RCV data in this study are presented as a point of departure for a widely applicable objective guide to interpret changes in serial results.     

A new quality control model using performance goals based on biological variation in External Quality Assurance Schemes.

A new quality control model using performance goals based on biological variation in External Quality Assurance Schemes (EQAS) is described. The proposed model aims to use assay (analytical) CV(A), bias and total error available from participation in EQAS to describe assay performance using minimum, desirable and optimum quality specifications based on biological variation. The model provides further analysis of EQAS data and should be useful in better management of laboratory quality control, as it provides further information that can facilitate trouble-shooting. Additionally, it can help in evaluating the performance of current and proposed new laboratory methods by applying a unifying system if different EQAS are used to cover a range of analytes.