Background The quality of occupational health technical services is directly linked to the protection of workers' health rights and the efficacy of occupational disease prevention and control. However, the industry still faces critical challenges: sporadic instances of institutional non-compliance and persistent irregularities in professional practice continue to undermine overall service performance. Objective To assess the current quality status of occupational health technical services in Zhejiang Province and propose countermeasures for quality improvement, providing a scientific basis for policy optimization and service delivery quality enhancement. Methods A total of 69 occupational health technical service institutions in Zhejiang Province that obtained formal accreditation as of April 30, 2024, were sampled, including 3 public institutions and 66 private institutions (comprising 3 formerly Class-A, 28 formerly Class-B, 11 formerly Class-C, and 24 newly certified institutions). Following the Technical Protocol for Quality Monitoring of Occupational Health Technical Service in Zhejiang Province and the Technical Protocol for Proficiency Testing of Occupational Health Detection in Zhejiang Province, a quality assessment task force comprising national and provincial experts was established. Evaluation was conducted across four dimensions: qualification maintenance and compliance, standardization of technical services, authenticity of technical services, and proficiency testing, utilizing a combination of document review, on-site inspections, and technical skill assessments. Results The occupational health technical service institutions in Zhejiang Province were predominantly private entities (82.5%), with significant disparities in overall service quality. The pass rates for qualification maintenance and compliance, technical service standardization, technical service authenticity, and the excellence rate for laboratory proficiency testing were 81.5%, 80.7%, 97.3%, and 90.4%, respectively. Regarding qualification maintenance, the pass rates for "environmental conditions" (49.8%, 56.7%) and "instrumentation and equipment" (58.2%、65.6%) were significantly lower for formerly Class-C and newly certified institutions compared to other categories. In terms of technical standardization, "standardized on-site inspections" recorded the lowest pass rate (67.4%), with newly certified institutions at only 48.0%. Regarding technical service authenticity, formerly Class-C institutions exhibited issues such as missing raw chromatograms for blank samples (85.7% pass rate). In laboratory proficiency testing, public and formerly Class-A institutions achieved 100% excellence rates, but the performance of formerly Class-C and newly certified institutions was comparatively weak; specifically, the failure rate for organic analysis in formerly Class-C institutions reached 20%; the failure rate for dust testing items in newly certified institutions was 10.3%. Conclusion The overall quality of occupational health technical services in Zhejiang Province still requires significant improvement, particularly in basic institutional conditions, the standardization of on-site inspections, and laboratory proficiency in organic and dust analysis. Formerly Class-C and newly certified institutions should be the primary focus of quality management efforts. Differentiated regulatory strategies are recommended, alongside strengthening interim and ex-post supervision to gradually enhance the quality of occupational health technical services across all institutions.

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.

Objective To investigate the profile of common oral diseases in the Inner Mongolia region and the im-pact on local residents,and to obtain a clear picture of technology availability for local oral physicians and their needs for oral medical training.This will provide an important basis for optimizing the content of continuing educa-tion program and the direction of counterpart assistance in order to improve the technical level of local oral physi-cians and the practicality of oral medical teaching.Methods The study selected oral physicians from the Inner Mongolia region as subjects and designed a questionnaire to explore the current status of oral diseases and the training needs of oral physicians in this area.The chi-square test or Fisher's exact probability method was used for statistical testing.Results Data collected from the survey questionnaires of 181 oral physicians in the Inner Mongolia region indicated that 56.83%of physicians were engaged in routine oral medicine,reaching 56.83%.Dental caries and peri-odontitis were the most common oral diseases in the region(70.37%and 65.74%respec-tively).The most common impacts of these diseases on patients were pain and discomfort.In terms of clinical skills,diagnostic imaging skills,oral examination skills and root canal therapy were the most important as the ob-jective of training there were 70.17%of respondents expressed expectation to get the learning and training opportu-nity for new technologies and methods.Conclusions Continuing education programs and specific targeted assistance projects should focus on strengthening basic professional training for dental practitioners in Inner Mongolia and the promotion of capacity building in the field of healthcare and promotion of oral health in the region.

[Purpose]To analyze the lifetime risk of developing and dying from lung cancer at global and regional levels.[Methods]Data of lung cancer incidence and mortality were obtained from GLOBOCAN 2022 and the population and all-cause mortality data were obtained from the United Nations.The lifetime risk of developing and dying from lung cancer globally and across different regions was estimated by multiple primary adjustment method.[Results]The global lifetime risk of developing lung cancer was 3.59％[95％confidence interval(CI):3.58％～3.59％],ranking third among all cancer types.There were significant gender and regional differences in lifetime risk values.The risk for male was 4.43％(95％CI:4.42％～4.44％),which was higher than that for female(2.71％,95％CI:2.70％～2.72％),with a male-to-female ratio of 1.63.Among regions with varying human development index(HDI)levels,the risk increased with HDI levels,in very high HDI re-gions risk was 5.36％(95％CI:5.34％～5.37％),while in low HDI regions the risk was 0.34％(95％CI:0.33％～0.34％).Among the 20 global regions,East Asia had the highest lifetime risk of 7.53％(95％CI:7.52％～7.55％),while West Africa had the lowest risk of 0.16％(95％CI:0.16％～0.17％).The global lifetime risk of dying from lung cancer was 2.78％(95％CI:2.78％～2.78％),ranking the first among all cancer types.There were significant sex and regional differ-ences in lifetime death risk values.The risk for male was 3.64％(95％CI:3.63％～3.64％),which was higher than that for female(1.89％,95％CI:1.89％～1.90％),with a male-to-female ratio of 1.93.Among regions with varying HDI levels,the risk increased with HDI levels,in very high HDI re-gions the risk was 3.98％(95％CI:3.97％～3.99％),while in low HDI regions the risk was 0.31％(95％CI:0.31％～0.31％).Among the 20 global regions,the Federated States of Micronesia/Poly-nesia had the highest death risk of 5.80％(95％CI:4.98％～6.62％),while West Africa had the lowest risk of 0.15％(95％CI:0.15％～0.16％).The lifetime risk of developing and dying from lung cancer in China was 7.54％(95％CI:7.52％～7.56％)and 5.88％(95％CI:5.87％～5.90％),respec-tively,both ranking the first among all cancer types.[Conclusion]The lifetime risk of developing and dying from lung cancer remains high globally and across different regions,with a particularly heavy burden in high-HDI areas.In China,both the lifetime risk of developing and dying from lung cancer are higher than the global average.This highlights the need for continued enhance-ment of comprehensive prevention and control measures,including addressing lung cancer-related risk factors,as well as improving screening,early diagnosis,and treatment efforts to reduce the lung cancer burden.

Objective:To investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

Objective:To investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

[Purpose]To analyze the lifetime risk of developing and dying from lung cancer at global and regional levels.[Methods]Data of lung cancer incidence and mortality were obtained from GLOBOCAN 2022 and the population and all-cause mortality data were obtained from the United Nations.The lifetime risk of developing and dying from lung cancer globally and across different regions was estimated by multiple primary adjustment method.[Results]The global lifetime risk of developing lung cancer was 3.59％[95％confidence interval(CI):3.58％～3.59％],ranking third among all cancer types.There were significant gender and regional differences in lifetime risk values.The risk for male was 4.43％(95％CI:4.42％～4.44％),which was higher than that for female(2.71％,95％CI:2.70％～2.72％),with a male-to-female ratio of 1.63.Among regions with varying human development index(HDI)levels,the risk increased with HDI levels,in very high HDI re-gions risk was 5.36％(95％CI:5.34％～5.37％),while in low HDI regions the risk was 0.34％(95％CI:0.33％～0.34％).Among the 20 global regions,East Asia had the highest lifetime risk of 7.53％(95％CI:7.52％～7.55％),while West Africa had the lowest risk of 0.16％(95％CI:0.16％～0.17％).The global lifetime risk of dying from lung cancer was 2.78％(95％CI:2.78％～2.78％),ranking the first among all cancer types.There were significant sex and regional differ-ences in lifetime death risk values.The risk for male was 3.64％(95％CI:3.63％～3.64％),which was higher than that for female(1.89％,95％CI:1.89％～1.90％),with a male-to-female ratio of 1.93.Among regions with varying HDI levels,the risk increased with HDI levels,in very high HDI re-gions the risk was 3.98％(95％CI:3.97％～3.99％),while in low HDI regions the risk was 0.31％(95％CI:0.31％～0.31％).Among the 20 global regions,the Federated States of Micronesia/Poly-nesia had the highest death risk of 5.80％(95％CI:4.98％～6.62％),while West Africa had the lowest risk of 0.15％(95％CI:0.15％～0.16％).The lifetime risk of developing and dying from lung cancer in China was 7.54％(95％CI:7.52％～7.56％)and 5.88％(95％CI:5.87％～5.90％),respec-tively,both ranking the first among all cancer types.[Conclusion]The lifetime risk of developing and dying from lung cancer remains high globally and across different regions,with a particularly heavy burden in high-HDI areas.In China,both the lifetime risk of developing and dying from lung cancer are higher than the global average.This highlights the need for continued enhance-ment of comprehensive prevention and control measures,including addressing lung cancer-related risk factors,as well as improving screening,early diagnosis,and treatment efforts to reduce the lung cancer burden.

【Objective】 To observe the effect of puerarin on the concentration of Ca²⁺ and the expression of brain derived neurotrophic factor (BDNF) in hippocampal neurons of vascular dementia (VD) rats so as to explore the mechanism of puerarin in protecting nerve cells. 【Methods】 Male SD rats were randomly divided into sham operation group, model group, and puerarin intervention group. The vascular dementia model was established by ligating bilateral common carotid arteries at intervals of 3 days. Two weeks after the operation, the learning and memory abilities of the rats were evaluated by Morris water maze, and the expression of BDNF in the hippocampus of the rats was detected by immunohistochemistry and Western blotting. The mean fluorescence intensity was measured by flow cytometry to represent the intracellular free Ca²⁺ concentration. 【Results】 In the puerarin intervention group, the rats’ escape latency in Morris water maze was significantly shortened, the expression of BDNF in the hippocampus was significantly increased, and the concentration of Ca²⁺ in hippocampal neurons was decreased. Compared with the model group, the difference was statistically significant (all P<0.05). 【Conclusion】 Puerarin has neuroprotective effect on VD rats, and its mechanism may be related to the decrease of Ca²⁺ concentration in hippocampal neurons and the up-regulation of BDNF expression.

BACKGROUND: Red-cell transfusion is critical for surgery during the peri-operative period; however, the transfusion threshold remains controversial mainly owing to the diversity among patients. The patient's medical status should be evaluated before making a transfusion decision. Herein, we developed an individualized transfusion strategy using the West-China-Liu's Score based on the physiology of oxygen delivery/consumption balance and designed an open-label, multicenter, randomized clinical trial to verify whether it reduced red cell requirement as compared with that associated with restrictive and liberal strategies safely and effectively, providing valid evidence for peri-operative transfusion. METHODS: Patients aged >14 years undergoing elective non-cardiac surgery with estimated blood loss > 1000 mL or 20% blood volume and hemoglobin concentration <10 g/dL were randomly assigned to an individualized strategy, a restrictive strategy following China's guideline or a liberal strategy with a transfusion threshold of hemoglobin concentration <9.5 g/dL. We evaluated two primary outcomes: the proportion of patients who received red blood cells (superiority test) and a composite of in-hospital complications and all-cause mortality by day 30 (non-inferiority test). RESULTS: We enrolled 1182 patients: 379, 419, and 384 received individualized, restrictive, and liberal strategies, respectively. Approximately 30.6% (116/379) of patients in the individualized strategy received a red-cell transfusion, less than 62.5% (262/419) in the restrictive strategy (absolute risk difference, 31.92%; 97.5% confidence interval [CI]: 24.42-39.42%; odds ratio, 3.78%; 97.5% CI: 2.70-5.30%; P <0.001), and 89.8% (345/384) in the liberal strategy (absolute risk difference, 59.24%; 97.5% CI: 52.91-65.57%; odds ratio, 20.06; 97.5% CI: 12.74-31.57; P <0.001). No statistically significant differences were found in the composite of in-hospital complications and mortality by day 30 among the three strategies. CONCLUSION: The individualized red-cell transfusion strategy using the West-China-Liu's Score reduced red-cell transfusion without increasing in-hospital complications and mortality by day 30 when compared with restrictive and liberal strategies in elective non-cardiac surgeries. TRIAL REGISTRATION ClinicalTrials.gov, NCT01597232.
Humans ; Adult ; Postoperative Complications ; Erythrocyte Transfusion/adverse effects* ; Blood Transfusion ; Hospitals ; Hemoglobins/analysis*