Objective To develop a statistical quality control(SQC)program design software to help laboratories design comprehensive SQC programs based on patient risk.Methods Based on the power function diagram,operation process specification diagram,risk-based multi-level internal quality control(IQC)scheme,and online calculator for IQC frequency,corresponding software modules were integrated and designed,and applied the data of potassium project to the software.Results For the power function diagram,operation process specification,and online calculator for IQC frequency,13s/22s/R4s/41s[Number of quality control measurement values(N)=2]was the best choice for potassium for IQC.In the risk-based multi-level IQC scheme,13s/22s/R4s/41s(N=2)could be selected as the startup quality control event,while different subsequent bracketing quality control events could be obtained based on different expected reporting intervals and maximum workloads to achieve the expected quality requirements.Conclusion The development of statistical quality control program design soft is proves beneficial for clinical laboratories to assess the current quality level and select appropriate quality control approaches,and assists the laboratories in enhancing quality.

Objective To develop a statistical quality control(SQC)program design software to help laboratories design comprehensive SQC programs based on patient risk.Methods Based on the power function diagram,operation process specification diagram,risk-based multi-level internal quality control(IQC)scheme,and online calculator for IQC frequency,corresponding software modules were integrated and designed,and applied the data of potassium project to the software.Results For the power function diagram,operation process specification,and online calculator for IQC frequency,13s/22s/R4s/41s[Number of quality control measurement values(N)=2]was the best choice for potassium for IQC.In the risk-based multi-level IQC scheme,13s/22s/R4s/41s(N=2)could be selected as the startup quality control event,while different subsequent bracketing quality control events could be obtained based on different expected reporting intervals and maximum workloads to achieve the expected quality requirements.Conclusion The development of statistical quality control program design soft is proves beneficial for clinical laboratories to assess the current quality level and select appropriate quality control approaches,and assists the laboratories in enhancing quality.

Objective To understand the situation of interlaboratory comparison for without external quality assessment(EQA)test by analyzing the results of quality indicators related to interlaboratory comparison rate of EQA from 2016 to 2023,in order to provide some suggestions for comparison.Methods The National Center for Clinical Laboratories organized 31 centers of provinces(autonomous re-gions and municipalities directly)to launch a synchronous Quality Indicators(QIs)-EQA program.The data were reported via devel-oped online EQA system.The essential information of the clinical laboratories and the data of quality indicators of interlaboratory com-parison rate were collected.The median(lower quartile,upper quartile)M(Q1,Q3)of the interlaboratory comparison rate was calcu-lated,and the quality level of the laboratory was evaluated by sigma measurement,and the statistics of the classification(tertiary and secondary hospitals)were carried out to understand the differences in the interlaboratory comparison rate among different hospital grades.Mann-Whitney U test was used to compare the two groups(different years or different hospital grades),and P＜0.05(α=0.05)indicated that the difference was statistically significant.Results The number of return laboratories increased from 6 701 in 2016 to 11 579 in 2023.The national median results showed that the interlaboratory comparison rate had been increasing year by year(excluding 2021),from 1.6％in 2016 to 3.8％in 2023.The median grading results showed that the interlaboratory comparison rate of tertiary hospitals was higher than that of secondary hospitals.In 2023,the interlaboratory comparison rate was 10.3％for tertiary hospi-tals and 2.3％for secondary hospitals.The results of all the years were below 3σ level.The median interlaboratory comparison rate of tertiary hospitals in various regions showed that Shanghai,Ningxia,and Sichuan exhibited higher median.The median interlaboratory comparison rate of secondary hospitals showed that Shanghai,Sichuan,and Hainan exhibited higher median.Conclusion At present period,the interlaboratory comparison rate has still been low in those laboratories without EQA tests.Therefore,the medical laborato-ries without EQA tests should strengthen interlaboratory comparisons to verify the reliability of their results.

Objective The performance characteristics of statistical quality control procedures in Westgard sigma rule are analyzed by using the power function graph.Methods According to the drawing principle of power function graph,the internal quality control program design software of clinical laboratory quantitative measurement was developed.and the Westgard sigma rule quality control procedures were simulated with power function graph.The performance of the quality control procedures recommended by Westgard sigma was analyzed by combining different sigma quality levels.Results The rules recommended by Westgard sigma were relatively simple rules that can meet the requirements of error detection probability and false rejection probability.Conclusion The internal quality control procedure design software for quantitative clinical testing has verified the performance of Westgard sigma recommendation rules.The Westgard sigma rule diagram is intuitive and convenient,the laboratory can use the Westgard sigma recommendation rules for internal quality control.

Objective To investigate the clinical value of thromboelastography (TEG) in monitoring the coagulation function change after plasma supplementation in the patients with severe liver cirrhosis diges-tive tract hemorrhage.Methods A total of 48 patients with high risk and extreme high risk liver cirrhosis a-cute upper digestive hemorrhage receiving the treatment in ICU of this hospital from February 2020 to March 2023 were selected as the study subjects.After plasma infusion with the dose of 10 mL/kg,the coagulation function status was detected.The patients were divided into the TEG group (n=20) and the control group (n=28) according to different detection modes of coagulation function.The TEG group simultaneously detec-ted TEG and traditional coagulation function detection,while the control group only conducted the traditional coagulation detection.TEG and coagulation function detection indicators after the infusion of plasma were compared between the two groups.The plasma infusion amounts at 24 h after admitting in ICU were recorded and the control status of digestive tract hemorrhage was evaluated.Results The R value in the TEG group was (8.02±6.09)min,the K vale was 2.5(1.3,5.0)min,the coagulation comprehensive index (CI) was-4.70±6.29,the maximal shear stress coefficient (MA) was 50.35±18.84,LY30 was 0.The Pearson corre-lation analysis showed that MA was positively correlated with FIB and PLT (r=0.470,0.526,P<0.05),and the other indexes had no correlation.Compared with the control group,the plasma infusion amounts in the TEG group was more[(419.00±143.18)mL vs. (400.00±137.54)mL],the digestive tract hemorrhage con-trol rate was higher[75.00％(15/20) vs. 53.57％(15/28)],but the differences were not statistically signifi-cant (P>0.05).The multiple linear regression was MA=-3.427+11.200×Ln(PLT)+10.230×Ln(FIB).Con-clusion In the patients with severe lever cirrhosis acute upper gastrointestinal bleeding,TEG could earlier find the co-agulation function improvement situation after plasma supplementation than the traditional coagulation detection.

Objective To understand the situation of interlaboratory comparison for without external quality assessment(EQA)test by analyzing the results of quality indicators related to interlaboratory comparison rate of EQA from 2016 to 2023,in order to provide some suggestions for comparison.Methods The National Center for Clinical Laboratories organized 31 centers of provinces(autonomous re-gions and municipalities directly)to launch a synchronous Quality Indicators(QIs)-EQA program.The data were reported via devel-oped online EQA system.The essential information of the clinical laboratories and the data of quality indicators of interlaboratory com-parison rate were collected.The median(lower quartile,upper quartile)M(Q1,Q3)of the interlaboratory comparison rate was calcu-lated,and the quality level of the laboratory was evaluated by sigma measurement,and the statistics of the classification(tertiary and secondary hospitals)were carried out to understand the differences in the interlaboratory comparison rate among different hospital grades.Mann-Whitney U test was used to compare the two groups(different years or different hospital grades),and P＜0.05(α=0.05)indicated that the difference was statistically significant.Results The number of return laboratories increased from 6 701 in 2016 to 11 579 in 2023.The national median results showed that the interlaboratory comparison rate had been increasing year by year(excluding 2021),from 1.6％in 2016 to 3.8％in 2023.The median grading results showed that the interlaboratory comparison rate of tertiary hospitals was higher than that of secondary hospitals.In 2023,the interlaboratory comparison rate was 10.3％for tertiary hospi-tals and 2.3％for secondary hospitals.The results of all the years were below 3σ level.The median interlaboratory comparison rate of tertiary hospitals in various regions showed that Shanghai,Ningxia,and Sichuan exhibited higher median.The median interlaboratory comparison rate of secondary hospitals showed that Shanghai,Sichuan,and Hainan exhibited higher median.Conclusion At present period,the interlaboratory comparison rate has still been low in those laboratories without EQA tests.Therefore,the medical laborato-ries without EQA tests should strengthen interlaboratory comparisons to verify the reliability of their results.

Objective:To establish preliminary quality specifications for emergency examination turnaround time (TAT).Methods:The National Center for Clinical Laboratories organized 31 provinces (autonomous regions and municipalities directly) and Xinjiang production and Construction Corps centers to launch a synchronous Quality Indicators (QIs)-External Quality Assessment (EQA) program and the collected data were reported via developed online EQA system. The essential information of the clinical laboratories, the data of pre-examination and intra-laboratory TAT quality indicators of emergency departments at each specialty (biochemistry, automatic immunity, three routines tests and coagulation) and four specific tests (blood potassium, troponin I/T, white blood cell count and international normalized ratio (INR)) were collected from 2019 to 2021. TAT returned the median and 90th percentile ( P90) of the specified month were calculated. The median (lower quartile, upper quartile) of the TAT returned laboratories were calculated and second result grading statistics for 2021 (2 422 tertiary hospital and 5 088 secondary hospital) were performed to understand the difference of pre-examination and the laboratory TAT between different tertiary hospitals. Results:From 2019 to 2021, there were 9 540 laboratories, 9 709 laboratories and 10 653 returned laboratories. The pre-examination TAT of each specialty was similar, and the results were relatively stable. The median distribution was about 15 (10, 30) min, and the monthly P90 distribution was about 20 (10, 30) min. The distribution results of the median intra-laboratory TAT in each specialty were as follows: automatic immunity≥biochemistry>coagulation>three routine tests. The distribution of the latest (second result in 2021) survey results of each specialty were as follows: automatic immunity 53 (30, 60) min, biochemistry 45 (30, 60) min, coagulation 30 (23, 40) min, and three routine tests 20 (11, 30) min. The median results of monthly P90 of intra-laboratory TAT were as follows: 60 min for automatic immunity and biochemistry specialty, about 38 min for coagulation specialty, and about 27 min for three routines tests. The hierarchical statistical results showed that the monthly P90 distribution of laboratory TAT of the pre-examination and intra-laboratory TAT from the tertiary hospital was higher than that of the secondary hospital. The pre-examination TAT of each specialty of the tertiary hospital/secondary hospital was as follows: biochemistry 35 (22, 60)/20 (11, 30) min, automatic immunity 33 (20, 60)/20 (10, 30) min, three routine tests 30 (20, 49)/20 (10, 30) min and coagulation 31 (20, 58)/20 (10, 30) min, the intra-laboratory TAT of each specialty of the tertiary hospital/secondary hospital was as follows: biochemistry 65 (50, 91)/60 (40, 70) min, automatic immunity 75 (55, 113)/60 (40, 90) min, three routine tests 30 (23, 38)/28 (19, 30) min and coagulation 53 (36, 72)/35 (30, 57) min. In terms of the distribution results of the median of intra-laboratory TAT of the four specific tests, 96.76% (9 484/9 801) of the blood potassium and 95.96% (8 733/9 101) of the troponin I/T medical institutions were TAT within 69 min in the laboratories, 95.34% (9 679/10 152) of the white blood cell count medical institutions were TAT within 31 min in the laboratories, and 98.85% (9 462/9 572) of the INR medical institutions were TAT within 66 min in the laboratories. Conclusions:This survey provides a preliminary quality specification for the emergency department turnaround time at each specialty. Lower quartile, median and upper quartile of the monthly P90 at the tertiary and secondary hospitals can be used to define the best, appropriate and minimum performance levels, respectively.

Objective:To analyze the implementation of the external quality assessment plan for quality indicators of clinical laboratories in China from 2016 to 2021, as well as that of the external quality assessment of 15 quality indicators in clinical laboratories, in order to provide reference for quality management of clinical laboratory specialties.Methods:The research data was collected from the external quality assessment plan for quality indicators, which was conducted by the National Center for Clinical Laboratories joining the clinical laboratory centers of 31 provinces (autonomous regions and municipalities directly). The essential information reported by each participating clinical laboratory from 2016 to 2021 and the external quality assessment data of 15 quality indicators in clinical laboratories were collected, followed by a descriptive analysis on the number of participating laboratories and the number of returns for each indicator. Median representation was used for the external quality assessment data of 15 quality indicators in clinical laboratories, and the TOPSIS method was applied to comprehensively evaluate the quality of the total testing process of participating clinical laboratories in each year.Results:From 2016 to 2021, the number of laboratories participating in the external quality assessment plan for quality indicators of clinical laboratory increased from 7 704 to 12 142. Quality indicators in pre-analytical phases: the incorrect sample type rate, incorrect sample container rater, and incorrect fill level rate had been decreasing year by year, reaching 0, 0, and 0.005 8% in 2021, respectively. The anticoagulant samples clotted rate had decreased from 0.068 6% in 2016 to 0.042 8% in 2021, and the blood culture contamination rate from 2017 to 2021 had been 0 without exception. The pre-examination turnaround time had been shortened from 28 minutes in 2016 to 2019 to 24 minutes in 2020 and 2021. Quality indicators in analytical phases: the intra-laboratory turnaround time had been extended from 45 minutes in 2016 to 2019 to 50 minutes in 2020 and 2021. Test covered by an IQC rate had been increasing year by year, reaching 60.61% in 2021. Test with inappropriate IQC performances rate was 0 in 2020 and 2021, the test covered by an EQA-PT control rate was 100%, and unacceptable performances in EQA-PT schemes rate from 2017 to 2021 was 0. The inter-laboratory comparison rate had increased from 1.56% in 2016 to 3.00% in 2021. Quality indicators in post-analytical phases: the incorrect laboratory reports rate, critical values notification rate and timely critical values notification rate had been 0, 100%, and 100%from 2016 to 2021 respectively. The comprehensive evaluation results of TOPSIS method showed that the overall quality level of clinical laboratory testing in 2020 was the highest, with Ci value of 0.850 5, while the lowest Ci value in 2016 was 0.143 6. Conclusions:The quality of clinical laboratory testing in China has been effectively improved. Clinical laboratories should continue to strengthen their monitoring of quality indicators, especially the intra-laboratory turnover time and the inter-laboratory comparison rate, for the purposes of identifying errors, analyzing causes and taking corrective measures to improve quality.

Objective:To assess the relationship between appendicular skeletal muscle mass (ASM) and ankle brachial index (ABI) among patients with type 2 diabetes.Methods:In this cross-sectional study, from July 2018 to March 2019, a total of 278 patients with type 2 diabetes treated in Zhongda Hospital were enrolled in this study, and there were 158 males and 120 females. General information and clinical biochemical parameters and ABI in the patients were collected. The appendicular muscle mass was quantitatively measured with body composition analyzer to achieve ASM. And the appendicular skeletal muscle mass index (ASMI), skeletal muscle index (SMI), and appendicular skeletal muscle mass/body mass index (ASM/BMI) were calculated respectively. Correlation analysis and multiple linear regression analyses with different adjustment models were conducted to analyze the correlation between ABI and above-mentioned indexes.Results:The Pearson correlation analysis showed that ABI had significant positive correlation with ASM, ASMI and ASM/BMI ( r=0.14, 0.13, 0.13, all P<0.05), but a marginal relation with SMI ( r=0.116, P=0.053). Multiple linear regression analysis suggested that ASMI ( β=0.053, 95% CI: 0.006-0.101, P=0.027) and AMI/ABI ( β=0.347, 95% CI: 0.040-0.654, P=0.027) were significantly related to ABI. Conclusion:ASM is positively associated with ABI in patients with type 2 diabetes.

Background:In the clinical setting, the effect of intra-abdominal hypertension on the human body is dependent on time, but its role is not yet clear.Objective:To investigate the effect of the duration of intra-abdominal hypertension (IAH) on the prognosis of critically ill patients.Methods:This prospective cohort study enrolled 256 IAH patients who were admitted to the Surgical ICU of 10 Grade A hospitals in Fujian Province from January 2018 to December 2020. The duration of IAH (DIAH) was obtained after monitoring IAP, and ICU length of stay, duration of mechanical ventilation, duration of continuous renal replacement therapy (CRRT) and average daily energy intake from enteral nutrition during ICU stay were observed and recorded. The correlation was analyzed by Spearman rank correlation. The patients were divided into the survival group and the death group according to their survival state at 60 days after enrollment. Thereafter, clinical characteristics between the two groups were compared. Multivariable logistic regression was used to study and validate the relationship between DIAH and 60-day mortality. The receiver operating characteristics (ROC) curve was established to evaluate the predictive abilities of DIAH on the mortality risk.Results:In critically ill patients, DIAH was positively correlated with duration of mechanical ventilation ( r=0.679, P<0.001), duration of CRRT ( r=0.541, P<0.001) and ICU length of stay ( r=0.794, P<0.001), respectively. In addition, there was a negative correlation between DIAH and average daily energy intake from enteral nutrition ( r=-0.669, P<0.001). After multivariable adjustment, DIAH was an independent risk factor for 60-day mortality in critically patients with IAH ( OR=1.05, 95% CI: 1.01-1.12; P = 0.012), and exhibited a linearity change trend relationship with mortality risk. The ROC curve analysis of DIAH showed that the area under ROC curve (AUC) was 0.825 (95% CI: 0.763~0.886, P<0.01). When the cut-off value was 16.5 days, the sensitivity was 78.4% and the specificity was 75.4%. Conclusions:DIAH is an important risk factor for prognosis in critically ill patients. Early identification and rapid intervention for the etiology of IAH should be performed to shorten DIAH.