1.The causal association between circulating zinc, magnesium, and other minerals with autism spectrum disorder: a Mendelian randomization study.
Bing-Quan ZHU ; Sai-Jing CHEN ; Tian-Miao GU ; Si-Run JIN ; Dan YAO ; Shuang-Shuang ZHENG ; Jie SHAO
Chinese Journal of Contemporary Pediatrics 2025;27(9):1098-1104
OBJECTIVES:
To evaluate the causal association between circulating levels of zinc, magnesium, and other minerals and autism spectrum disorder (ASD).
METHODS:
A two-sample Mendelian randomization (MR) analysis was performed using summary statistics from large-scale genome-wide association studies of European populations, including 18 382 ASD cases and 27 969 controls. Genetic data for iron, calcium, and magnesium were obtained from the UK Biobank, and data for zinc and selenium were sourced from an Australian-British cohort. A total of 351 genetic instrumental variables were selected. Causal inference was performed using inverse-variance weighting as the primary analysis method. Sensitivity analyses were performed by Cochran's Q test and MR-PRESSO global test to assess the robustness of the findings.
RESULTS:
No statistically significant causal effect was observed for circulating zinc, magnesium, calcium, selenium, or iron levels on ASD risk (all P>0.05). The odds ratios and 95% confidence intervals from the inverse-variance weighting analysis were 0.934 (0.869-1.003) for zinc, 1.315 (0.971-1.850) for magnesium, 1.055 (0.960-1.159) for calcium, 1.015 (0.953-1.080) for selenium, and 0.946 (0.687-1.303) for iron. Sensitivity analysis revealed significant heterogeneity in the causal association between circulating calcium and ASD (P=0.006), while the effect estimate remained stable after MR-PRESSO correction (P=0.487). The causal effect estimates for the remaining minerals demonstrated good robustness.
CONCLUSIONS
This study did not find significant evidence supporting a causal association between circulating zinc, magnesium, calcium, selenium, or iron levels and ASD risk, providing important clues for the etiology of ASD and precision nutritional interventions.
Humans
;
Mendelian Randomization Analysis
;
Autism Spectrum Disorder/genetics*
;
Magnesium/blood*
;
Zinc/blood*
;
Minerals/blood*
;
Genome-Wide Association Study
;
Selenium/blood*
2.The Effect of Histone Deacetylase on the Pathogenesis of Burkitt Lymphoma.
Chun-Tuan LI ; Bing-Bing LI ; Dan WENG ; Wan-Lin YANG ; Shao-Xiong WANG ; Yan ZHENG ; Dan WANG ; Xiong-Peng ZHU
Journal of Experimental Hematology 2025;33(3):796-801
OBJECTIVE:
To investigate the effects of histone deacetylase (HDAC) levels on the proliferation and apoptosis of Burkitt lymphoma cells, and the changes in related signaling molecules in the PI3K/AKT/mTOR signaling pathway, so as to explore the pathogenesis of Burkitt lymphoma.
METHODS:
HDAC levels in Burkitt lymphoma were detected by RT-PCR and Western blot. CA46 and RAJI cells were treated with the HDAC selective inhibitor VPA. CCK8 assay was used to detect the proliferation ability of cells. Western Blot was used to measure the expression of apoptosis-related proteins, PI3K/AKT/mTOR signaling pathway proteins and their phosphorylation levels.
RESULTS:
The expression levels of classⅠ HDAC in Burkitt lymphoma were higher than those in normal cells, and the HDAC1 inhibitor VPA could inhibit the proliferation of CA46 and RAJI cells. VPA decreased HDAC expression in CA46 and RAJI cells, inhibited the phosphorylation of PI3K/AKT/mTOR pathway molecules AKT and p70S6K, increased the expression of apoptotic proteins Cleaved Caspase-3, Cleaved Caspase-8, Cleaved Caspase-9 and Bax, and decreased the expression of anti-apoptotic proteins Bcl-2 and PARP.
CONCLUSION
Inhibition of HDAC activity can Attenuate the proliferation of Burkitt lymphoma cells and induce apoptosis by inhibiting the PI3K/AKT/mTOR signaling pathway activity.
Humans
;
Burkitt Lymphoma/pathology*
;
Apoptosis
;
Cell Proliferation
;
Signal Transduction
;
Proto-Oncogene Proteins c-akt/metabolism*
;
Phosphatidylinositol 3-Kinases/metabolism*
;
Cell Line, Tumor
;
Histone Deacetylases/metabolism*
;
TOR Serine-Threonine Kinases/metabolism*
;
Histone Deacetylase Inhibitors/pharmacology*
;
Phosphorylation
3.The predictive value of lipoprotein(a)combined with systemic inflammatory response index for in-stent restenosis in patients with coronary heart disease after PCI
Qiqi SHAO ; Zexin ZHOU ; Bing ZHU ; Ziyu YI ; Zhenyan FU
Chinese Journal of Arteriosclerosis 2025;33(10):859-863,869
Aim To investigate the predictive value of lipoprotein(a)[Lp(a)]combined with systemic inflam-matory response index(SIRI)on in-stent restenosis(ISR)after percutaneous coronary intervention(PCI)in patients with coronary heart disease.Methods The clinical data of 770 patients with coronary heart disease who underwent PCI in the Department of Cardiovascular Medicine of the First Affiliated Hospital of Xinjiang Medical University from May 2012 to December 2024 and underwent coronary angiography six months after surgery were collected.According to the imaging re-sults,the patients were divided into ISR group(n=194)and non-ISR group(n=576).Multivariate Logistic regression and random forest model were used to analyze the independent risk factors of ISR.Risk factors included in the analysis were glycated hemoglobin,SIRI,Lp(a),lymphocyte count,apolipoprotein A1(ApoA1)and residual cholesterol.Results The levels of Lp(a)and SIRI in the ISR group were significantly higher than those in the non-ISR group(P<0.05).ROC curve analysis showed that the area under the curve of the combined indicator of Lp(a)and SIRI was 0.789,which was higher than the 0.652 of the single indicator Lp(a)and 0.778 of SIRI.Conclusion Lp(a)and SIRI are independent risk factors for the occurrence of ISR after PCI,and the combination of Lp(a)and SIRI can better predict the occurrence of ISR.
4.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
5.Symptoms and treatment of benign prostatic hyperplasia patients with upper urinary tract calculi after ureteral stent implantation
Wei LIU ; Hui ZHANG ; Shuang-ning LIU ; Shao-hua BIAN ; Qi-yuan KANG ; Ying-yi LI ; Qiao DU ; Wen-bing YUAN ; Jiang ZHU
National Journal of Andrology 2025;31(7):608-611
Objective:To analyze the symptoms,diagnosis and treatment of upper urinary tract calculi patients combined with mild and moderate benign prostatic hyperplasia(BPH)after ureteral stent implantation.Methods:One hundred and six BPH pa-tients who were hospitalized for upper urinary tract calculi and had ureteral stents retained from January 2019 to December 2022 were selected and divided into 2 weeks group and 4 weeks group according to the time of removal of ureteral stents after surgery.Their gener-al clinical data were analyzed and compared.International Prostatic Symptom Scale(IPSS),postoperative ureteral Stent Symptom Questionnaire(USSQ),and incidence of adverse events after ureteral stent removal were recorded before and after removal.Results:The scores of IPSS were significantly increased in all patients,and symptoms in urinary tract had improved significantly after discharge(P<0.05).Compared with the 2 weeks group,the USSQ score of the 4 weeks group was significantly increased(P<0.05).And no significant adverse event was observed in the 2 weeks group after the removal of ureteral sten.Conclusion:IPSS score and USSQ score increased significantly during stent implantation in BPH patients with lithiasis.And complications increased sig-nificantly over time.Following thorough clinical assessment,early ureteral stent removal demonstrates both safety and efficacy,repre-senting an optimal therapeutic approach in selected cases.
6.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
7.The predictive value of lipoprotein(a)combined with systemic inflammatory response index for in-stent restenosis in patients with coronary heart disease after PCI
Qiqi SHAO ; Zexin ZHOU ; Bing ZHU ; Ziyu YI ; Zhenyan FU
Chinese Journal of Arteriosclerosis 2025;33(10):859-863,869
Aim To investigate the predictive value of lipoprotein(a)[Lp(a)]combined with systemic inflam-matory response index(SIRI)on in-stent restenosis(ISR)after percutaneous coronary intervention(PCI)in patients with coronary heart disease.Methods The clinical data of 770 patients with coronary heart disease who underwent PCI in the Department of Cardiovascular Medicine of the First Affiliated Hospital of Xinjiang Medical University from May 2012 to December 2024 and underwent coronary angiography six months after surgery were collected.According to the imaging re-sults,the patients were divided into ISR group(n=194)and non-ISR group(n=576).Multivariate Logistic regression and random forest model were used to analyze the independent risk factors of ISR.Risk factors included in the analysis were glycated hemoglobin,SIRI,Lp(a),lymphocyte count,apolipoprotein A1(ApoA1)and residual cholesterol.Results The levels of Lp(a)and SIRI in the ISR group were significantly higher than those in the non-ISR group(P<0.05).ROC curve analysis showed that the area under the curve of the combined indicator of Lp(a)and SIRI was 0.789,which was higher than the 0.652 of the single indicator Lp(a)and 0.778 of SIRI.Conclusion Lp(a)and SIRI are independent risk factors for the occurrence of ISR after PCI,and the combination of Lp(a)and SIRI can better predict the occurrence of ISR.
8.Risk factors and predictive model of cerebral edema after road traffic accidents-related traumatic brain injury
Di-You CHEN ; Peng-Fei WU ; Xi-Yan ZHU ; Wen-Bing ZHAO ; Shi-Feng SHAO ; Jing-Ru XIE ; Dan-Feng YUAN ; Liang ZHANG ; Kui LI ; Shu-Nan WANG ; Hui ZHAO
Chinese Journal of Traumatology 2024;27(3):153-162
Purpose::Cerebral edema (CE) is the main secondary injury following traumatic brain injury (TBI) caused by road traffic accidents (RTAs). It is challenging to be predicted timely. In this study, we aimed to develop a prediction model for CE by identifying its risk factors and comparing the timing of edema occurrence in TBI patients with varying levels of injuries.Methods::This case-control study included 218 patients with TBI caused by RTAs. The cohort was divided into CE and non-CE groups, according to CT results within 7 days. Demographic data, imaging data, and clinical data were collected and analyzed. Quantitative variables that follow normal distribution were presented as mean ± standard deviation, those that do not follow normal distribution were presented as median (Q 1, Q 3). Categorical variables were expressed as percentages. The Chi-square test and logistic regression analysis were used to identify risk factors for CE. Logistic curve fitting was performed to predict the time to secondary CE in TBI patients with different levels of injuries. The efficacy of the model was evaluated using the receiver operator characteristic curve. Results::According to the study, almost half (47.3%) of the patients were found to have CE. The risk factors associated with CE were bilateral frontal lobe contusion, unilateral frontal lobe contusion, cerebral contusion, subarachnoid hemorrhage, and abbreviated injury scale (AIS). The odds ratio values for these factors were 7.27 (95% confidence interval ( CI): 2.08 -25.42, p = 0.002), 2.85 (95% CI: 1.11 -7.31, p = 0.030), 2.62 (95% CI: 1.12 -6.13, p = 0.027), 2.44 (95% CI: 1.25 -4.76, p = 0.009), and 1.5 (95% CI: 1.10 -2.04, p = 0.009), respectively. We also observed that patients with mild/moderate TBI (AIS ≤ 3) had a 50% probability of developing CE 19.7 h after injury (χ 2= 13.82, adjusted R2 = 0.51), while patients with severe TBI (AIS > 3) developed CE after 12.5 h (χ 2= 18.48, adjusted R2 = 0.54). Finally, we conducted a receiver operator characteristic curve analysis of CE time, which showed an area under the curve of 0.744 and 0.672 for severe and mild/moderate TBI, respectively. Conclusion::Our study found that the onset of CE in individuals with TBI resulting from RTAs was correlated with the severity of the injury. Specifically, those with more severe injuries experienced an earlier onset of CE. These findings suggest that there is a critical time window for clinical intervention in cases of CE secondary to TBI.
9.Effects of ezrin protein on Helicobacter pylori-induced nodular gastritis
Peng WANG ; Hongwei ZHU ; Shuyuan JIANG ; Xiaolei LIU ; Bing GAO ; Guo SHAO
Chinese Journal of Comparative Medicine 2024;34(7):150-156
The ezrin,radixin,moesin(ERM)protein family plays a pivotal role in cell morphology,migration,and signal transduction.Ezrin,as a prominent member of this family,is highly involved in these processes.Ezrin phosphorylation is particularly crucial,by regulating the interaction between ezrin and the actin cytoskeleton.This interaction is a key mediator of cytotoxicity in host cells infected with Helicobacter pylori,significantly impacting cell morphology.In this review,we comprehensively summarize the multifaceted role of ezrin protein in H.pylori-induced nodular gastritis.We consider the relationships between ezrin's structure,function,signaling pathways,and phosphorylation in the context of nodular gastritis.Moreover,this review highlights the role of ezrin protein as a potential therapeutic target,offering novel insights for the prevention and treatment of nodular gastritis.
10.HbA1c comparison and diagnostic efficacy analysis of multi center different glycosylated hemoglobin detection systems.
Ping LI ; Ying WU ; Yan XIE ; Feng CHEN ; Shao qiang CHEN ; Yun Hao LI ; Qing Qing LU ; Jing LI ; Yong Wei LI ; Dong Xu PEI ; Ya Jun CHEN ; Hui CHEN ; Yan LI ; Wei WANG ; Hai WANG ; He Tao YU ; Zhu BA ; De CHENG ; Le Ping NING ; Chang Liang LUO ; Xiao Song QIN ; Jin ZHANG ; Ning WU ; Hui Jun XIE ; Jina Hua PAN ; Jian SHUI ; Jian WANG ; Jun Ping YANG ; Xing Hui LIU ; Feng Xia XU ; Lei YANG ; Li Yi HU ; Qun ZHANG ; Biao LI ; Qing Lin LIU ; Man ZHANG ; Shou Jun SHEN ; Min Min JIANG ; Yong WU ; Jin Wei HU ; Shuang Quan LIU ; Da Yong GU ; Xiao Bing XIE
Chinese Journal of Preventive Medicine 2023;57(7):1047-1058
Objective: Compare and analyze the results of the domestic Lanyi AH600 glycated hemoglobin analyzer and other different detection systems to understand the comparability of the detection results of different detectors, and establish the best cut point of Lanyi AH600 determination of haemoglobin A1c (HbA1c) in the diagnosis of diabetes. Methods: Multi center cohort study was adopted. The clinical laboratory departments of 18 medical institutions independently collected test samples from their respective hospitals from March to April 2022, and independently completed comparative analysis of the evaluated instrument (Lanyi AH600) and the reference instrument HbA1c. The reference instruments include four different brands of glycosylated hemoglobin meters, including Arkray, Bio-Rad, DOSOH, and Huizhong. Scatter plot was used to calculate the correlation between the results of different detection systems, and the regression equation was calculated. The consistency analysis between the results of different detection systems was evaluated by Bland Altman method. Consistency judgment principles: (1) When the 95% limits of agreement (95% LoA) of the measurement difference was within 0.4% HbA1c and the measurement score was≥80 points, the comparison consistency was good; (2) When the measurement difference of 95% LoA exceeded 0.4% HbA1c, and the measurement score was≥80 points, the comparison consistency was relatively good; (3) The measurement score was less than 80 points, the comparison consistency was poor. The difference between the results of different detection systems was tested by paired sample T test or Wilcoxon paired sign rank sum test; The best cut-off point of diabetes was analyzed by receiver operating characteristic curve (ROC). Results: The correlation coefficient R2 of results between Lanyi AH600 and the reference instrument in 16 hospitals is≥0.99; The Bland Altman consistency analysis showed that the difference of 95% LoA in Nanjing Maternity and Child Health Care Hospital in Jiangsu Province (reference instrument: Arkray HA8180) was -0.486%-0.325%, and the measurement score was 94.6 points (473/500); The difference of 95% LoA in the Tibetan Traditional Medical Hospital of TAR (reference instrument: Bio-Rad Variant II) was -0.727%-0.612%, and the measurement score was 89.8 points; The difference of 95% LoA in the People's Hospital of Chongqing Liang Jiang New Area (reference instrument: Huizhong MQ-2000PT) was -0.231%-0.461%, and the measurement score was 96.6 points; The difference of 95% LoA in the Taihe Hospital of traditional Chinese Medicine in Anhui Province (reference instrument: Huizhong MQ-2000PT) was -0.469%-0.479%, and the measurement score was 91.9 points. The other 14 hospitals, Lanyi AH600, were compared with 4 reference instrument brands, the difference of 95% LoA was less than 0.4% HbA1c, and the scores were all greater than 95 points. The results of paired sample T test or Wilcoxon paired sign rank sum test showed that there was no statistically significant difference between Lanyi AH600 and the reference instrument Arkray HA8180 (Z=1.665,P=0.096), with no statistical difference. The mean difference between the measured values of the two instruments was 0.004%. The comparison data of Lanyi AH600 and the reference instrument of all other institutions had significant differences (all P<0.001), however, it was necessary to consider whether it was within the clinical acceptable range in combination with the results of the Bland-Altman consistency analysis. The ROC curve of HbA1c detected by Lanyi AH600 in 985 patients with diabetes and 3 423 patients with non-diabetes was analyzed, the area under curve (AUC) was 0.877, the standard error was 0.007, and the 95% confidence interval 95%CI was (0.864, 0.891), which was statistically significant (P<0.001). The maximum value of Youden index was 0.634, and the corresponding HbA1c cut point was 6.235%. The sensitivity and specificity of diabetes diagnosis were 76.2% and 87.2%, respectively. Conclusion: Among the hospitals and instruments currently included in this study, among these four hospitals included Nanjing Maternity and Child Health Care Hospital in Jiangsu Province (reference instrument: Arkray HA8180), Tibetan Traditional Medical Hospital of TAR (reference instrument: Bio-Rad Variant Ⅱ), the People's Hospital of Chongqing Liang Jiang New Area (reference instrument: Huizhong MQ-2000PT), and the Taihe Hospital of traditional Chinese Medicine in Anhui Province (reference instrument: Huizhong MQ-2000PT), the comparison between Lanyi AH600 and the reference instruments showed relatively good consistency, while the other 14 hospitals involved four different brands of reference instruments: Arkray, Bio-Rad, DOSOH, and Huizhong, Lanyi AH600 had good consistency with its comparison. The best cut point of the domestic Lanyi AH600 for detecting HbA1c in the diagnosis of diabetes is 6.235%.
Pregnancy
;
Child
;
Humans
;
Female
;
Glycated Hemoglobin
;
Cohort Studies
;
Diabetes Mellitus/diagnosis*
;
Sensitivity and Specificity
;
ROC Curve

Result Analysis
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