OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVES: To explore the mechanism of cinnamic acid (CA) for improving doxorubicin-induced myocardial injury (DIC) in mice. METHODS: Network pharmacology analysis was used to obtain the key targets of CA and DIC. Male C57BL/6J mice were randomized into Sham, DOX, CA (25, 50 and 100 mg/kg)+DOX, and CA+Ferrostatin-1+DOX groups, and their myocardial function and pathology were examined by echocardiography and HE staining. Serum levels of CK-MB, LDH, MDA, IL-6, TNF‑α and myocardial ROS level were detected, and the expression levels of TLR4 and ferroptosis pathway proteins in myocardial tissue were detected by Western blotting. Cultured murine cardiomyocytes (HL-1 cells) with or without transfection with a small interfering RNA targeting TLR4 (si-TLR4) were treated with DOX or Erastin, and the cellular ROS content was measured by DCFH-DA staining; the expression level of GPX4 was detected using immunofluorescence staining. RESULTS: Network pharmacology analysis suggested that CA may improve DIC through TLR4 signaling. DOX treatment caused obvious myocardial injury in mice, which showed significantly increased serum levels of CK-MB, LDH, MDA, IL-6, TNF-α and myocardial ROS level with decreased myocardial levels of SLC7A11 and GPX4 proteins and increased levels of TLR4 and PTGS2 proteins. All these changes in the mouse models were significantly alleviated by treatment with CA, and the mice receiving CA or ferrostatin-1 treatment exhibited increased myocardial expressions of SLC7A11 and GPX4 proteins and lowered expressions of TLR4 and PTGS2 proteins. In cultured HL-1 cells, treatment with DOX and Erastin both obviously increased intracellular ROS level and decreased cellular GPX4 expression level, and these changes were strongly attenuated by TLR4 interference. CONCLUSIONS CA, as a potent herbal monomer, can effectively alleviate DIC in mice by inhibiting TLR4-mediated ferroptosis.
Animals ; Ferroptosis/drug effects* ; Toll-Like Receptor 4/metabolism* ; Myocytes, Cardiac/metabolism* ; Mice, Inbred C57BL ; Mice ; Male ; Doxorubicin/adverse effects* ; Cinnamates/pharmacology* ; Signal Transduction ; Reactive Oxygen Species/metabolism*

Objective:To investigate the anemia conditions and characteristics of iron metabolism during different stages of pregnancy in women with different genotypes of thalassemia.Methods:This cohort study selected 3 303 singleton pregnant women who underwent regular prenatal examinations and genetic tests of thalassemia and were delivered at Maternal & Child Health Hospital of Guangxi Zhuang Autonomous Region from January 2019 to December 2023. According to the results of thalassemia gene testing, the women were divided into groups: those without thalassemia genes served as the control group (1 539 cases), and those with thalassemia genes (1 764 cases) were further divided based on genotype into the -α/αα group (326 cases), --/αα or -α/-α group (649 cases), point mutation α-thalassemia group (201 cases), β 0-thalassemia group (368 cases), β +-thalassemia group (91 cases), and α combined with β-thalassemia group (129 cases). Hemoglobin (Hb) and serum ferritin (SF) levels were measured in the first, second, and third trimester of pregnancy. Differences in anemia and iron reserves among the groups at different pregnancy stages were compared using repeated measures analysis of variance, LSD test, Kruskal-Wallis rank-sum test, and Bonferroni correction. Results:Compared to the first trimester, Hb levels decreased in the second and third trimester across all groups (LSD test, all P<0.05), and the severity of anemia increased (Bonferroni correction, all P<0.017). The severity of anemia varied among the groups at the same pregnancy stage ( Hfirst trimester=918.20, Hsecond trimester=1 224.50, Hthird trimester=980.19; all P<0.001), and Hb levels also differed ( Ffirst trimester=282.54, Fsecond trimester=352.31, Fthird trimester=239.02; all P<0.001). The β 0-thalassemia group had higher rates of moderate anemia in the first, second, and third trimester of pregnancy [38.6% (142/368), 85.3% (314/368), and 73.6% (271/368)] compared to other groups (Bonferroni correction, all P<0.002), and lower Hb levels [(102.1±8.9), (92.0±7.3), and (94.6±7.7) g/L] than other groups (LSD test, all P<0.05). As pregnancy progresses, SF levels in each group of pregnant women gradually decreased (LSD test, all P<0.05), and the degree of iron deficiency worsened (Bonferroni correction, all P<0.05). The iron deficiency rate in thalassemia pregnant women during the third trimester ranges from 21.5% (79/368) to 46.0% (150/326). The degree of iron deficiency varies among groups within the same gestational period ( Hfirst trimester=79.13, Hsecond trimester=203.98, Hthird trimester=130.55; all P<0.001), and SF levels also differ ( Ffirst trimester=17.28, Fsecond trimester=44.60, Fthird trimester=31.87; all P<0.001). Among them, the β 0-thalassemia group had the lowest iron deficiency rates in the second, and third trimesters [9.8% (36/368), and 21.5% (79/368)] (Bonferroni correction, all P<0.002). SF levels in the β 0-thalassemia and β +-thalassemia groups were higher than those in other groups during each gestational period (LSD test, all P<0.05). Conclusions:Pregnant women with thalassemia may experience varying degrees of iron deficiency during pregnancy, with the severity of iron deficiency and anemia increasing with gestational age. The degree of iron deficiency and anemia during pregnancy varies among pregnant women with different genotypes of thalassemia. Clinically, individualized management should be provided for pregnant women with thalassemia based on their genotypes, with dynamic monitoring of anemia and iron metabolism changes.

OBJECTIVE To explore and establish the working mechanism for prevention and control of hospital-as-sociated infections in regional oral medical institutions so as to standardize the prevention and control of the hospi-tal-associated infections in the regional oral medical institutions.METHODS Taking an administrative division of Chongqing as example,the matrix evaluation was carried out based on the quality control mode for management of hospital-associated infections in oral medical institutions' action planning,training guidance,quality control super-vision,summary review' organically in combination with'quality control plus law enforcement',a color-co-ded management of the oral medical institutions in the region was implemented,and the effectiveness of improved work in infection control was examined.RESULTS From the perspective of the grade of medical institution,the qualified rates of hospital infection management system construction,architectural layout and process,cleaning,disinfection and sterilization of oral instruments,environmental cleaning and disinfection,isolation,safe injection,use of occupational protection supplies and disposal of medical waste of the primary and unrated medical institu-tions were respectively 26.51％,49.40％,24.10％,37.35％,31.33％,46.99％,67.47％and 51.81％before the improvement and were respectively increased to 67.47％,63.86％,45.78％,66.27％,63.86％,73.49％,84.34％and 66.27％after the improvement,and there were significant differences(P＜0.05).From the perspec-tive of the property of the medical institution,the qualified rates of the above items of the private medical institu-tions were respectively 24.66％,47.95％,21.92％,34.25％,31.51％,45.21％,69.86％and 50.68％before the improvement and were respectively increased to 65.75％,61.64％,42.47％,64.38％,63.01％,71.23％,84.93％and 63.01％after the improvement,and there were significant differences(P＜0.05).CONCLUSION The working mechanism on prevention and control of hospital-associated infections in regional oral medical institu-tions that is established based on'quality control plus law enforcement'with the introduction of social credit can effectively raise the qualified rates of the infection prevention and control measures,which achieves more remarka-ble improvement effectiveness in grass-roots oral medical institutions such as the private,primary and unrat-ed medical institutions.

Objective: To investigate the basic situation of pre-analytical quality management in blood station laboratories in North China, and to provide baseline data for promoting the homogenization and standardization of these pre-analytical processes in each blood station laboratory. Methods: A cross-sectional status survey was designed based on the quality management regulations of blood stations, ISO15189 standards and relevant quality management requirements. This survey covering various aspects including laboratory general situation, sample collection and temporary storage, transportation, reception, and quality continuous improvement situations. Data analysis was performed on the survey results of each laboratory. Results: All the 38 blood station laboratories in North China had established a pre-analytical quality management system framework and implemented basic pre-analytical quality control activities; however, there were differences in implementation. 1) Among the 12 basic quality items, 3 items were monitored by all the investigated laboratories (100%), 6 items were monitored by the vast majority of laboratories (about 90%), and 3 items were monitored by a portion of laboratories (about 60%). There were no significant differences in the monitoring index among the three regions and among different types of laboratories (P>0.05). 2) Among the total of 26 items in the three key processes before testing (sample collection and storage, transportation, reception and processing), 12 items were monitored by all laboratories (100%), 11 items were monitored by the vast majority of laboratories (about 90%), and 3 items were monitored by a portion of laboratories (about 75%). There were no significant differences in monitoring index among different regions and types of laboratories (P>0.05). Conclusion: This survey provides a reference and basis for the gap analysis of the pre-analytical process quality management in 38 blood station laboratories across North China. It facilitates laboratories in identifying pre-analytical quality problems, resolving problems, preventing errors, and ensuring that the quality of blood samples before testing meets the established requirements. It lays a foundation for the homogenization of pre-analytical quality management in regional blood stations.

Objective: To determine the frequency and main reasons of unqualified samples by analyzing the quality of pre-analytical samples in blood stations in North China, thereby providing a reference and basis for gap analysis in the implementation of pre-analytical process quality management for participating laboratories and ensuring that only high-standard and high-quality blood samples proceed to testing. Methods: Data on the quality of pre-analytical samples from blood station laboratories in North China was collected via questionnaire. Statistical analysis were performed on: 1) the basic information of samples quality monitoring in the laboratories; 2) the distribution of the overall pre-analytical unqualified rate of samples and the pre-analytical unqualified rate of samples in each laboratory; 3) the distribution of reasons for sample disqualification. Results: 1) The overall pre-analytical unqualified rate of samples in blood station laboratories in North China was 4.55, with a total sigma level of 5.39σ. The 25th, 50th and 75th percentiles (P25, P50, P75) for the total unqualified rate were 0.00, 1.10 and 5.96, respectively. The corresponding percentiles for the Sigma level were 5.34σ, 5.71σ, and 6.00σ, respectively. The pre-analytical unqualified rate of serological and nucleic acid samples (4.89 vs 4.22) showed a significant difference (χ =9.575, P<0.05). 2) The average unqualified rate of samples in region A, B and C was 1.71, 9.50 and 12.64 (χ =1 590.721, P<0.05), and the sigma level was 5.66σ, 5.21σ and 5.16σ, respectively. 3) The main reasons for unqualified serological samples were chylous blood (72.65%), hemolysis (17.39%), abnormal hematocrit (5.80%), and insufficient volume (3.50%). The main reasons for the unqualified nucleic acid samples were chylous blood (78.26%), hemolysis (8.84%), failure to centrifuge as required (5.01%), abnormal hematocrit (4.66%), and insufficient volume (1.92%). Conclusion: In North China, the quality indicators for the pre-analytical processes in blood station laboratories are generally well-managed. Laboratories in region A outperformed the national average in pre-analytical specimen quality control. However, participating laboratories exhibit gaps in implementing pre-analytical quality management. Through effective analysis of pre-analytical process quality metrics and inter-laboratory comparisons, laboratories can identify discrepancies and address shortcomings. By establishing clear quality objectives, they can achieve continuous improvement and ensure the validity of test results.

Objective: To investigate the assessment criteria and subsequent handling practices of hemolytic and lipemic blood samples before testing in blood screening laboratories in North China, and to provide data to support the standardization of their management in blood station laboratories. Methods: Data on the preanalytical management of hemolytic and lipemic samples from 38 laboratories were collected. The details of management on the criteria and verificatioon for assessment, the assessment methods, and subsequent handling procedures of hemolytic and lipemic samples in blood station laboratories were analyzed. Results: 1) All 38 blood station laboratories monitored serological and nucleic acid samples for hemolysis and lipemia in pre-analytical phase. 2) The criteria and methods for assessing hemolytic and lipemic samples varied among the laboratories of the 38 blood stations. 15 laboratories (39.47%) followed manufacturer's instructions, 9 laboratories (23.68%) formulated their own criteria, and 14 laboratories (36.84%) referred to the criteria of other laboratories. 16 laboratories (42.11%) verified the criteria for assessing hemolytic and lipemic samples, with significant variations in verification rate across laboratories from different regions (P<0.05). For the assessment methods, visual inspection was used by 28 laboratories (73.68%) for hemolytic samples and by 27 laboratories (71.05%) for lipemic samples; the colorimetric card method was used by 10 laboratories (26.32%) for assessing both hemolytic and lipemic samples; the instrumental method was used by 1 laboratory (2.63%) for assessing lipemic samples.3) The handling procedures for hemolytic and lipemic samples varied significantly and followed a gradient distribution pattern among 38 laboratories (including accepting samples for testing, accepting samples for concession testing, re-collecting samples, and rejecting samples and halting testing). With increasing severity of hemolysis and lipemia, more laboratories halted testing, and relatively fewer laboratories accepted samples for normal testing. 5 laboratories (13.16%) applied different handling procedures on serological and nucleic acid samples. Conclusion: This survey provides a reference and basis for analyzing gaps in the management of hemolytic and lipemic samples during the preanalyical phase in blood station laboratories in North China. It enables laboratories to identify the problems and deficiencies in the management of hemolytic and lipemic samples, to ensure preanalytical samples quality meets the established requirements, and to lay a foundation for promoting the homogenization and standardization of the regional sample quality management mode.

Objective:To analyze the comprehensive efficiency of resource allocation in urban public hospitals in 21cities of Guangdong Province from 2019 to 2023,aiming at providing empirical evidence for future medical policy makers and hospital managers in resource allocation and management.Methods:Using Data Envelopment Analysis and Malmquist index to evaluate the efficiency of health resource allocation in public hospitals in Guangdong.Results:From 2019 to 2023,the comprehensive efficiency of urban public hospitals in Guangdong Province was mildly ineffective,only 7 cities showing relative effectiveness,and there were significant regional differences in efficiency.Malmquist index analysis showed that the total factor productivity of health resource allocation in urban public hospitals in the province decreased from 2019 to 2020 and kept increasing from 2020 to 2023,mainly due to the increasing of the technological progress index and the scale efficiency index.Horizontally,the total factor productivity of 9 cities in the province has increased,while the total factor productivity of 12 cities has decreased,with significant regional differences.The input-output redundancy analysis shows that only 6 cities have no input-output redundancy.Conclusion:The overall efficiency of resource allocation in urban public hospitals in Guangdong Province from 2019 to 2023 is relatively low,with significant regional differences.In the future,it is necessary to coordinate and plan resource allocation,focus on refined management,strengthen talent training and technological improvement,improve the operational efficiency of existing resources,and promote high-quality development of hospitals.

Objective:To investigate the anemia conditions and characteristics of iron metabolism during different stages of pregnancy in women with different genotypes of thalassemia.Methods:This cohort study selected 3 303 singleton pregnant women who underwent regular prenatal examinations and genetic tests of thalassemia and were delivered at Maternal & Child Health Hospital of Guangxi Zhuang Autonomous Region from January 2019 to December 2023. According to the results of thalassemia gene testing, the women were divided into groups: those without thalassemia genes served as the control group (1 539 cases), and those with thalassemia genes (1 764 cases) were further divided based on genotype into the -α/αα group (326 cases), --/αα or -α/-α group (649 cases), point mutation α-thalassemia group (201 cases), β 0-thalassemia group (368 cases), β +-thalassemia group (91 cases), and α combined with β-thalassemia group (129 cases). Hemoglobin (Hb) and serum ferritin (SF) levels were measured in the first, second, and third trimester of pregnancy. Differences in anemia and iron reserves among the groups at different pregnancy stages were compared using repeated measures analysis of variance, LSD test, Kruskal-Wallis rank-sum test, and Bonferroni correction. Results:Compared to the first trimester, Hb levels decreased in the second and third trimester across all groups (LSD test, all P<0.05), and the severity of anemia increased (Bonferroni correction, all P<0.017). The severity of anemia varied among the groups at the same pregnancy stage ( Hfirst trimester=918.20, Hsecond trimester=1 224.50, Hthird trimester=980.19; all P<0.001), and Hb levels also differed ( Ffirst trimester=282.54, Fsecond trimester=352.31, Fthird trimester=239.02; all P<0.001). The β 0-thalassemia group had higher rates of moderate anemia in the first, second, and third trimester of pregnancy [38.6% (142/368), 85.3% (314/368), and 73.6% (271/368)] compared to other groups (Bonferroni correction, all P<0.002), and lower Hb levels [(102.1±8.9), (92.0±7.3), and (94.6±7.7) g/L] than other groups (LSD test, all P<0.05). As pregnancy progresses, SF levels in each group of pregnant women gradually decreased (LSD test, all P<0.05), and the degree of iron deficiency worsened (Bonferroni correction, all P<0.05). The iron deficiency rate in thalassemia pregnant women during the third trimester ranges from 21.5% (79/368) to 46.0% (150/326). The degree of iron deficiency varies among groups within the same gestational period ( Hfirst trimester=79.13, Hsecond trimester=203.98, Hthird trimester=130.55; all P<0.001), and SF levels also differ ( Ffirst trimester=17.28, Fsecond trimester=44.60, Fthird trimester=31.87; all P<0.001). Among them, the β 0-thalassemia group had the lowest iron deficiency rates in the second, and third trimesters [9.8% (36/368), and 21.5% (79/368)] (Bonferroni correction, all P<0.002). SF levels in the β 0-thalassemia and β +-thalassemia groups were higher than those in other groups during each gestational period (LSD test, all P<0.05). Conclusions:Pregnant women with thalassemia may experience varying degrees of iron deficiency during pregnancy, with the severity of iron deficiency and anemia increasing with gestational age. The degree of iron deficiency and anemia during pregnancy varies among pregnant women with different genotypes of thalassemia. Clinically, individualized management should be provided for pregnant women with thalassemia based on their genotypes, with dynamic monitoring of anemia and iron metabolism changes.