Background: Clinical chemistry tests are most widely used in clinical laboratories, and diverse measurement systems for these analyses are available in China. We evaluated the imprecision of clinical chemistry measurement systems based on internal QC (IQC) data. Methods: IQC data for 27 general chemistry analytes were collected in February each year from 2013 to 2022. Four performance specifications were used to calculate pass rates for CVs of IQC data in 2022. Boxplots were drawn to analyze trends of CVs, and differences in CVs among different groups were assessed using the Mann–Whitney U-test or Kruskal– Wallis test. Results: The number of participating laboratories increased significantly from 1,777 in 2013 to 5,425 in 2022. CVs significantly decreased for all 27 analytes, except creatine kinase and lipase. Triglycerides, total bilirubin, direct bilirubin, iron, and γ-glutamyl transferase achieved pass rates > 80% for all goals. Nine analytes with pass rates < 80% based on 1/3 allowable total error were further analyzed; the results indicated that closed systems exhibited lower CVs than open systems for all analytes, except total protein. For all nine analytes, differences were significant between tertiary hospitals and non-tertiary hospitals and between accredited and non-accredited laboratories. Conclusions The CVs of IQC data for clinical chemistry have seen a continuous overall improvement in China. However, there is ample room for imprecision improvement for several analytes, with stricter performance specifications.

Objective:The allowable total error ( TEa),allowable imprecision ( CV)and allowable bias( Bias)were recommended for 34 routine chemistry analytes in China. Methods:According to the performance specification setting mode newly determined at the Milan conference in Italy,the performance specification was derived based on components biological variation (BV)and current state of the art mode. The data(including EQA data and IQC data)of laboratories participating in the routine chemistry and lipids and lipoproteins EQA activities of the national center for clinical laboratories from 2019 to 2021 was collected through clinet-EQA. For the analytes with biological variation(BV)data,compared the'percentage difference′ of EQA data and the'in-control coefficient of variation of the month′ of IQC data of each research analyte with the three levels evaluation criteria derived based on BV,and calculated the percentage difference passing rate and CV passing rate of all batches in each year. When the passing rate reaches 80%,the performance specifications of this level met the requirements of the recommended performance specifications of the analyte. For the analytes without BV data or analytes whose performance specifications at three levels derived based on BV could not be used as recommended standards,the recommended performance specifications are derived based on the current state of the art. After obtaining the recommended TEa and allowable CV for each analyte,used the formula | Bias|≤ TEa-z? CV to derive the recommended allowable bias. Results:The results of TEa ( CV)% recommended by 34 analytes are as follows:K4.7(2),Na4(1.5),Cl4(1.4),Ca5(2),P9.6(3.9),Glu6.4(2.5),Urea8(3),UA12(4.1),Cre11(3.3),TP5(2),Alb5.2(2.4),TC8.6(2.7),TG13.5(5),HDL-C16.5(4.3),LDL-C20.5(6.2),ApoAⅠ16(5.3),ApoB 17.1(5.5),Lp(a) 24.1(10.4),TBil 12.4(5),DBil 20(7.3),ALT16(5),AST13.5(4.8),ALP17.5(4.8),AMY13.1(3.3),CK11.3(3.8),LDH11(3.9),CHE13.4(5.3),LIP20(6.9),Fe13.3(5.2),Mg14(4.5),Cu17.9(6.8),Zn15.1(6.4),γ-GGT10(3.3),α-HBDH18(5.8).The formula | Bias|≤ TEa-z? CV is used to derive the allowable bias of 34 analytes. Conclusions:For 34 clinical routine chemistry quantitative analytes,the allowable total error,allowable imprecision and allowable bias that meet the current state of the art of Chinese laboratories are recommended.

Background: Using commutable external quality assessment (EQA) materials is important for monitoring successful harmonization efforts. We assessed the commutability of four human serum pool (HSP) preparations to identify candidate EQA materials for alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activity measurement. Methods: One set each of 85 clinical samples (CSs) was collected for ALT and AST activity measurement. The 15 candidate EQA materials included four types of HSP preparations (A to D): materials A, C, and D contained human original recombinant (HOR) aminotransferases; materials B was mixed leftover samples. The CSs and 15 candidate EQA materials were analyzed using seven routine assays, and the ln-transformed results were analyzed in 21 assay pairs. Commutability was assessed using Deming regression, with a 95% prediction interval (CLSI approach) and the difference in bias with an error component model (International Federation of Clinical Chemistry and Laboratory Medicine [IFCC] approach). Results: For ALT, all materials were commutable for 14–21 assay pairs according to the CLSI and IFCC approaches. For AST, B01-03 showed commutability for 14-21 assay pairs, and C01-03 and D01-03 showed commutability for no less than 10 assay pairs according to the two approaches. A01-06 were commutable for 9-16 assay pairs according to the CLSI approach, but for 6-9 assay pairs according to the IFCC approach. Conclusions Mixed leftover samples showed desirable commutability characteristics as candidate EQA materials for routine aminotransferase activity measurements. Human serum bases supplemented with HOR were commutable for most routine ALT activity measurements.

Background: Diabetes can complicate hypertension management by increasing the risk of cardiovascular disease (CVD) and all-cause mortality. Studies targeting diabetes detection in hypertensive individuals demonstrating an increased risk of diabetes are lacking.We aimed to assess the performance of hemoglobin A1c (HbA1c) and its cut-off point in detecting diabetes in the abovementioned population. Methods: Data from 4,096 community-dwellers with hypertension but without known diabetes were obtained from the Study on Evaluation of iNnovated Screening tools and determInation of optimal diagnostic cut-off points for type 2 diaBetes in Chinese muLti-Ethnic (SENSIBLE) study; these data were randomly split into exploration (70% of the sample) and internal validation (the remaining 30%) datasets. The optimal HbA1c cut-off point was derived from the exploration dataset and externally validated using another dataset from 2,431 hypertensive individuals. The oral glucose tolerance test was considered the goldstandard for confirming diabetes. Results: The areas under the ROC curves for HbA1c to detect diabetes were 0.842, 0.832, and 0.829 for the exploration, internal validation, and external validation datasets, respectively. An optimal HbA1c cut-off point of 5.8% (40 mmol/mol) yielded a sensitivity of 76.2% and a specificity of 74.5%. Individuals who were not diagnosed as having diabetes by HbA1c at 5.8% (40 mmol/mol) had a lower 10-year CVD risk score than those diagnosed as having diabetes (P = 0.01). HbA1c ≤ 5.1% (32 mmol/mol) and ≥ 6.4% (46 mmol/mol) could indicate the absence and presence of diabetes, respectively. Conclusions HbA1c could detect diabetes effectively in community-dwellers with hypertension.

The laboratory medicine is aimed to support clinical decisions and patient health by providing accurate results. The internal statistical quality control (SQC) can help laboratories detecting the instability of the analytical system and preventing laboratories from reporting the patient results with medically important errors, so it is essential to ensure the quality of testing results and patient safety. The traditional methods of designing SQC strategy are based on the probability of error detection (P_ed) and the probability of false rejection (P_fr). With the introduction of risk management concepts, the design of SQC strategy began to be based on the patient risk parameter [MaxE(N_uf)] proposed by Parvin, which means the maximum increase in the number of unacceptable patient results reported compared to the in-control condition during the existence of an undetected out-of control error condition. MaxE(N_uf) is related to the SQC frequency and patient risk, which is very essential for optimizing the SQC frequency and designing a risk-based SQC strategy.

Objective To investigate the 15 quality indicators at medical institutions in China , and to explore the model of quality specifications .Methods Online questionnaires were sent to 8029 clinical laboratories ,with the results analyzed by SPSS 20 .The 25th percentile ,50th percentile ,and 75th percentile of the distribution ,according to the level of the hospital ,were regarded as the optimum , appropriate and minimum quality specifications for each quality indicator ,respectively .Results As shown in the median ,sigma values of most indicators were greater than 3 .The defect percentages of test uncovered by internal quality control (IQC)and test uncovered by inter-laboratory comparison were 47.46％ and 85.73％ ,respectively ,both too poor to calculate the sigma values. The turnaround time (TAT )differed greatly among the subjects.The longest time of pre-examination TAt and Intra-laboratory TAT were clinical immunity. The minimum quality specifications for the quality indicators were from 3σ to 6σ.Conclusions Laboratories should strengthen their IQc and inter-laboratory comparison with continuing education training to realize the continuous quality improvement .

Objective To investigate the implementation of professional standards for reference intervals in routine biochemistry laboratories.Methods The relevant data of reference intervals from different laboratories including upper and lower limits,sources of reference intervals,verification and grouping rules,etc was submitted by using the software of interval quality assessment (EQA) via WEB application.The background monitor saved all the data as Microsoft Excel 2007 documents.The implementation of reference intervals of professional standards for decreed 18 routine biochemical tests was analyzed.Results The proportion of laboratories in which the reference intervals were derived from professional standards increased largely in 2016 compared with those in 2014.The data of 2016 showed that the reference intervals derived from professional standards were verified in 58.9％ to 67.5％ of laboratories before they were used in clinical diagnosis.The grouping rules for reference intervals in most laboratories (59.1％ to 83.3％) were in accordance with professional standards,except for individual items,including urea (43.4％),creatinine (40.1％) and alkaline phosphatase (35.8％).There were significant differences for the upper and lower limits of the most items between the laboratories using professional standards and those without using professional standards (P ＜ 0.05),except for some items,including lower limit value of kalium,upper limit of phosphorus,upper limit of amylase,upper limit of aspartate aminotransferase and lower limit of ferrum.There was no significant difference in most items between the the upper and lower limits of the reference intervals in the laboratories using professional standards and the reference intervals defined by professional standards,except for individual items,including upper limit of total protein,lower and upper limit of creatine kinase,upper limit of urea and upper limit of creatinine (P ＜ 0.05).Conclusion The implementation of reference intervals from professional standards in most routine biochemistry laboratories could not be satisfactory.Only a small part of laboratories used the professional standards,and the reference intervals of professional standards,were not verified before use in quite a part of laboratories.

Objective To investigate the status of blood specimen acceptability for clinical chemistry tests in routine medical laboratories of China. Methods The questionnaires were assigned to the laboratories which participated in the routine chemistry exter-nal quality assessment (EQA) programs proposed by National Health Commission for Clinical Laboratory. The questionnaires included general information of participants and information about unacceptable blood specimens. Participants were required to record all the in-formation concerning unacceptable blood specimen received from 1stto 31stJuly, 2017. The data from each laboratory were reported and collected via special online system.Results A total of 866 valid questionnaires were collected.Of 15 981 752 specimens received dur-ing the data collection period unqualified 122 00 specimens were rejected with overall rejection rate of 0.076%. The main reasons for unacceptable specimens were hemolysis (33.98%), insufficient specimen quantity (10.78%) and chylemia/lipemia (10.62%). The rejected specimens were related to the original laboratories, types of container and specimen, transportation manner and operating staff of blood collection. Conclusion Certain problems existed in the receiving and management system for unqualified blood specimen in our country and remaining to be perfected. The clinical laboratories should pay more attention for pre-examination stage, including routinely monitoring unacceptable specimens, analyzing related data at the most possible granular levels, identifying the main problem and taking effective measures.

Objective To investigate the reasons of unacceptable external quality assessment results for hemoglobin A1c (HbA1c), and improve quality level.Methods At the end of February 2017, five samples of HbA1c for external quality assessment (EQA) were sent to participated laboratories by post.After testing and reporting results by laboratories , the EQA organizer made statistical analysis and sent results back to laboratories.Meanwhile , messages would be sent to participants those had unacceptable EQA results . Investigating reasons of unacceptable results in 2017 through the EQA System based on web , which was developed by National Central for Clinical Laboratories , calculating the failure rate , analyzing the concrete reasons and combining EQA failure rates with current coefficient of variation .Results The EQA failure rate on HbA1c was 11.2％and reporting rates of reasons for failures was 70.4％(126/179).In the reasons for unacceptable results , technological (27.8％,35/126) and equipment's defects (26.2％,33/126) were the main reason categories , while malfunction ( 12.7％, 16/126 ) and methods defection ( 10.3％, 13/126 ) were the main reason subclass .The unexplainable results after survey account for 8.7％( 11/126 ) .In the group for coefficient of variation ( CV ) over 2％, the percentage of laboratories that had five samples get acceptable results was higher than that of group for CV less than 2％,and the percentage of laboratories that had at most four samples get acceptable results was lower than that of group for CV less than 2％.Conclusions The result of the reasons of unacceptable external quality assessment results for HbA 1c is generally satisfactory.The laboratory, manufacturer and EQA organizers should find and solve the working problems by analyzing EQA data , to improve the testing quality.

Before performing patient testing with commercial microbial test systems,each laboratory must verify that it can obtain performance specifications comparable to those of the manufacturer.This includes trueness,precision (reproducibility),and reportable range of test results,and verifying that the manufacturer's reference ranges are appropriate for the laboratory's patient population.American Clinical and Laboratory Standards Institute has set up a committeeto develop a verification process and a quality assurance program for commercial microbial identification system and antimicrobial susceptibility testing system,in order to provide recommendations for US Food and Drug Administration (FDA).This guidance is applicable to instrument systems widely used in clinical laboratories and can also be used for manual testing of microbiological identification and antimicrobial susceptibility testing.The aim of this article is to provide advice for the microbial identification system and antimicrobial susceptibility testing system verification process,based on principles of microbiological identification and antimicrobial susceptibility and CLSI M52 guideline.