Objective To construct an evaluation model for the use of large-scale medical equipment based on the analytic hierarchy process(AHP).Methods The indicators of the evaluation model were determined with considerations on the req-uirements of Accreditation Standard for Tertiary Hospitals(2022 edition),performance assessment standards of municipal departments for large-scale medical equipment in medical institutions over the years,the present situation of medical insti-tutions,key indexes for performance evaluation and the basic operational efficiency of the equipment.The evaluation model was established by calculating the weights of the indicators with AHP and performing the consistency test.The utilization of four CT devices in some hospital in a certain year was used as an example to comprehensively evaluate the rationality and feasibility of the model.Results There were 5 first-level indicators and 14 second-level indicators involved in the large-scale medical equipment usage evaluation model.The first-level indicators were made up of the usage,social benefits,functional utilization,economic benefits,scientific research and teaching benefits,with the weights of 45.156%,21.090%,12.113%,15.983%,and 5.657%,respectively,with all the first-level and second-level indicators passing the consistency test.The analysis of levels indicator weights showed the indicators affecting the operational efficiency included positive rate,expected work rate,utilization rate,etc.Comprehensive evaluation indicated the model was consistent with the traditional evaluation modes when used for ranking the equipment usage.Conclusion The AHP-based large-scale medical equipment usage evaluation model with high practicality facilitates the decision of medical institutions for the utilization,allocation and management of specialized medical equipment.[Chinese Medical Equipment Journal,2025,46(8):86-90]

Objective To design a multi-terminal collaborative medical equipment acceptance management system to enhance the informatized management of medical equipment acceptance.Methods The multi-terminal collaborative medical equipment acceptance management system was designed with the front-end and back-end separation mode.The front end was developed with Flutter framework and Dart language,the back end was implemented with Tornado 6.1 architecture and Python language,the communication between the front-end and the back-end service followed the RESTful design principle and the interaction was carried out through the hypertext transfer protocol(HTTP)request.There were three functional modules involved in the system for user management,basic information management and acceptance management.Results The system developed realized informatized management for medical equipment acceptance process,supported cross-platform management of acceptance reports,related attachments and medical device registration certificates and improved the quality and efficiency of medical equipment acceptance.Conclusion The system developed facilitates multi-terminal collaborative management for medical equipment acceptance,and lays a foundation for the digital and intelligent transformation of hospital medical equipment management.[Chinese Medical Equipment Journal,2025,46(7):39-44]

Objective To construct an evaluation model for the use of large-scale medical equipment based on the analytic hierarchy process(AHP).Methods The indicators of the evaluation model were determined with considerations on the req-uirements of Accreditation Standard for Tertiary Hospitals(2022 edition),performance assessment standards of municipal departments for large-scale medical equipment in medical institutions over the years,the present situation of medical insti-tutions,key indexes for performance evaluation and the basic operational efficiency of the equipment.The evaluation model was established by calculating the weights of the indicators with AHP and performing the consistency test.The utilization of four CT devices in some hospital in a certain year was used as an example to comprehensively evaluate the rationality and feasibility of the model.Results There were 5 first-level indicators and 14 second-level indicators involved in the large-scale medical equipment usage evaluation model.The first-level indicators were made up of the usage,social benefits,functional utilization,economic benefits,scientific research and teaching benefits,with the weights of 45.156%,21.090%,12.113%,15.983%,and 5.657%,respectively,with all the first-level and second-level indicators passing the consistency test.The analysis of levels indicator weights showed the indicators affecting the operational efficiency included positive rate,expected work rate,utilization rate,etc.Comprehensive evaluation indicated the model was consistent with the traditional evaluation modes when used for ranking the equipment usage.Conclusion The AHP-based large-scale medical equipment usage evaluation model with high practicality facilitates the decision of medical institutions for the utilization,allocation and management of specialized medical equipment.[Chinese Medical Equipment Journal,2025,46(8):86-90]

Objective To design a multi-terminal collaborative medical equipment acceptance management system to enhance the informatized management of medical equipment acceptance.Methods The multi-terminal collaborative medical equipment acceptance management system was designed with the front-end and back-end separation mode.The front end was developed with Flutter framework and Dart language,the back end was implemented with Tornado 6.1 architecture and Python language,the communication between the front-end and the back-end service followed the RESTful design principle and the interaction was carried out through the hypertext transfer protocol(HTTP)request.There were three functional modules involved in the system for user management,basic information management and acceptance management.Results The system developed realized informatized management for medical equipment acceptance process,supported cross-platform management of acceptance reports,related attachments and medical device registration certificates and improved the quality and efficiency of medical equipment acceptance.Conclusion The system developed facilitates multi-terminal collaborative management for medical equipment acceptance,and lays a foundation for the digital and intelligent transformation of hospital medical equipment management.[Chinese Medical Equipment Journal,2025,46(7):39-44]

Objective Studies on the relationship between iodine,vitamin A(VA),and vitamin D(VD)and thyroid function are limited.This study aimed to analyze iodine and thyroid-stimulating hormone(TSH)status and their possible relationships with VA,VD,and other factors in postpartum women. Methods A total of 1,311 mothers(896 lactating and 415 non-lactating)from Hebei,Zhejiang,and Guangxi provinces were included in this study.The urinary iodine concentration(UIC),TSH,VA,and VD were measured. Results The median UIC of total and lactating participants were 142.00 μg/L and 139.95 μg/L,respectively.The median TSH,VA,and VD levels in all the participants were 1.89 mIU/L,0.44 μg/mL,and 24.04 ng/mL,respectively.No differences in the UIC were found between lactating and non-lactating mothers.UIC and TSH levels were significantly different among the three provinces.The rural UIC was higher than the urban UIC.Obese mothers had a higher UIC and a higher prevalence of excessive TSH.Higher UICs and TSHs levels were observed in both the VD deficiency and insufficiency groups than in the VD-sufficient group.After adjustment,no linear correlation was observed between UIC and VA/VD.No interaction was found between vitamins A/D and UIC on TSH levels. Conclusion The mothers in the present study had no iodine deficiency.Region,area type,BMI,and VD may be related to the iodine status or TSH levels.

Three-dimensional ordered porous carbon materials exhibit potential application prospects as excellent drug supports in drug delivery systems due to their high specific surface area, tunable pore structure, and excellent biocompatibility. In this study, three-dimensional ordered porous carbon materials were prepared using Acanthopanax senticosus herbal residues as raw material and KOH as activating agent through a one-step pyrolysis method. The prepared carbon-based material was systematically characterized by powder X-ray diffraction, scanning electron microscopy, N₂ adsorption-desorption and Fourier-transform infrared spectroscopy. The results show that the three-dimensional ordered porous carbon materials prepared with KOH as the activator via pyrolysis possess abundant functional groups, high porosity, and high specific surface area, with a specific surface area of 1 471.6 m²·g^-1. The three-dimensional ordered porous carbon materials prepared at 800 ℃ exhibits a high drug loading capacity (78.0%) and drug release rate (86.8%) for 5-fluorouracil. Three-dimensional orderly porous carbon materials show significant application advantages in drug construction, and their high specific surface area and adjustable pore size structure significantly improve the drug load rate and drug release rate, providing a solid foundation for the development of efficient and accurate drug delivery system.

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

OBJECTIVE: This study was aimed at investigating the carrier rate of, and molecular variation in, α- and β-globin gene mutations in Hunan Province. METHODS: We recruited 25,946 individuals attending premarital screening from 42 districts and counties in all 14 cities of Hunan Province. Hematological screening was performed, and molecular parameters were assessed. RESULTS: The overall carrier rate of thalassemia was 7.1%, including 4.83% for α-thalassemia, 2.15% for β-thalassemia, and 0.12% for both α- and β-thalassemia. The highest carrier rate of thalassemia was in Yongzhou (14.57%). The most abundant genotype of α-thalassemia and β-thalassemia was -α ^3.7/αα (50.23%) and β ^IVS-II-654/β ^N (28.23%), respectively. Four α-globin mutations [CD108 (ACC>AAC), CAP +29 (G>C), Hb Agrinio and Hb Cervantes] and six β-globin mutations [CAP +8 (C>T), IVS-II-848 (C>T), -56 (G>C), beta nt-77 (G>C), codon 20/21 (-TGGA) and Hb Knossos] had not previously been identified in China. Furthermore, this study provides the first report of the carrier rates of abnormal hemoglobin variants and α-globin triplication in Hunan Province, which were 0.49% and 1.99%, respectively. CONCLUSION Our study demonstrates the high complexity and diversity of thalassemia gene mutations in the Hunan population. The results should facilitate genetic counselling and the prevention of severe thalassemia in this region.
Humans ; beta-Thalassemia/genetics* ; alpha-Thalassemia/genetics* ; Hemoglobinopathies/genetics* ; China/epidemiology* ; High-Throughput Nucleotide Sequencing

Objective: This study aimed to explore the prognostic value of the revised international prognostic scoring system (IPSS-R) and the WHO prognostic scoring system (WPSS) in patients with myelodysplastic syndrome (MDS) undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods: The clinical data of 184 patients with MDS who received allo-HSCT from July 2016 to June 2019 were retrospectively analyzed. IPSS-R and WPSS were performed at diagnosis and before transplantation. The prognostic values of IPSS-R and WPSS and potential risk factors were explored. Results: With a median follow-up of 21.9 (0.5-47.5) months, the two-year overall survival (OS) and progression-free survival (PFS) rates were (75.1±3.4)% and (71.6±3.6)% , respectively. The two-year cumulative relapse rate and nonrelapse mortality rate were (11.9±0.1)% and (16.5±0.1)% , respectively. There were no significant differences in OS and PFS between the IPSS-R ≤3.5 and >3.5 groups at diagnosis (P=0.409; P=0.724). No significant differences in OS and PFS between the WPSS ≤2 and >2 groups (P=0.426; P=0.726) were observed as well. When the patients were reevaluated before transplantation, the OS and PFS of the IPSS-R ≤3.5 group were significantly better than >3.5 group [OS: (88.6±4.1)% vs (65.8±5.3)% , P=0.003; PFS: (87.6±4.2)% vs (60.5±5.8)% , P=0.002]. However, there were no significant differences in OS and PFS among the WPSS ≤2 and >2 groups (P=0.584; P=0.565). In addition, the OS and PFS of the improved group based on IPSS-R were significantly better than those of the unimproved group before transplantation [OS: (83.8±4.6)% vs (69.3±5.8)% , P=0.027; PFS: (82.8±4.4)% vs. (64.0±7.2)% , P=0.006]. Multivariate analysis indicated that a pretransplant IPSS-R of >3.5 (P=0.021, HR=2.510, 95% CI 1.151-5.476) and TP53 mutation (P=0.047, HR=2.460, 95% CI 1.014-5.971) were independent risk factors for OS, whereas a pretransplant IPSS-R of >3.5 (P=0.017, HR=2.457, 95% CI 1.175-5.141) and pretransplant cytogenetic poor and very poor (P=0.008, HR=2.765, 95% CI 1.305-5.856) were independent risk factors for PFS. Conclusion: A pretransplantation evaluation of IPSS-R could help determine the prognosis of patients with MDS undergoing allo-HSCT. In addition, patients with improved IPSS-R scores before undergoing allo-HSCT had a better prognosis.
Hematopoietic Stem Cell Transplantation ; Humans ; Myelodysplastic Syndromes/therapy* ; Prognosis ; Retrospective Studies ; Risk Factors