Objective To analyze the epidemiological characteristics of newly diagnosed occupational diseases in Guangdong Province from 2019 to 2023. Methods Data on newly diagnosed occupational diseases reported in Guangdong Province from 2019 to 2023 were collected from the national occupational disease network reporting system. The spectrum of occupational diseases and their distribution by region, industry, and population were analyzed. Results A total of 4 136 newly diagnosed occupational disease cases were reported in Guangdong Province from 2019 to 2023, showing an overall downward trend. Newly diagnosed cases were classified into eight categories and 53 types of occupational diseases. In terms of the number of cases, the top five categories were occupational diseases of the ear, nose, throat and oral cavity;occupational pneumoconiosis and other respiratory diseases; occupational diseases caused by physical factors; occupational chemical poisoning; and occupational tumors, accounting for 98.62% of all cases. The top ten specific disease types were occupational noise-induced deafness, occupational silicosis, occupational other pneumoconiosis, occupational chronic benzene poisoning, occupational heatstroke, occupational hand-arm vibration disease, occupational coal workers′ pneumoconiosis, occupational welders′ pneumoconiosis, occupational tumor (leukemia caused by benzene exposure), and occupational chronic n-hexane poisoning, accounting for 94.85% of all cases. Most of the cases were distributed in the Pearl River Delta region, accounting for 89.19%; as well as manufacturing industry, accounting for 84.89%. Male cases accounted for 87.02%. Most diagnoses occurred in individuals aged >40-60 years, accounting for 74.73%. Conclusion Newly diagnosed occupational diseases in Guangdong Province from 2019 to 2023 showed the following characteristics: concentration of categories and disease types, polarization of regional distribution, industry clustering, and population difference. The disease spectrum is evolving from a dual-disease predominance toward a multi-disease predominance.

Objective To establish a set of scientific and standardized quality control indicator system for occupational pneumoconiosis (hereinafter referred to as "pneumoconiosis") medical care. Methods A research group was set up to establish an indicator pool of quality control indicator system for pneumoconiosis, including three first-level indicators and 48 second-level indicators, based on literature review, analysis and sorting, and the current national quality control indicators of respiratory diseases in disease-specific quality monitoring. Two rounds of consultation were conducted with 15 experts through Delphi method to establish the quality control indicator system for pneumoconiosis medical care. Results The questionnaire recovery rates of the two rounds of expert consultations were 100%, and the effective questionnaire recovery rates of both consultations were 100%. The expert authority coefficient was 0.91, and the expert coordination coefficients were 0.208 and 0.209, respectively (both P<0.001). The coefficient of variation ranged from 0.10 to 0.37, with nine indicators having a coefficient of variation >0.25. The constructed quality control indicator system for pneumoconiosis medical care includes three primary indicators, 15 secondary indicators, and 32 tertiary indicators. Conclusion The constructed quality management indicator system for pneumoconiosis medical care has high scientificity and reliability. It provides a basis for the quality evaluation of pneumoconiosis medical care. However, continuous improvement is needed in practical applications.

Objective To explore the application effect of quality control circle in the quality management improvement of the occupational disease diagnostic and code.Methods To established across departmental team of medical record QCC,we Select 132 cases of the occupational disease departmentin specialized Hospital from May 1,2022 to June31,2022,Analyze the reasons of inaccurate that main diagnosisselection and code mapping.After formulating a series of improvement measures,we Se-lect 71 cases of occupational disease department from November 1,2022 to December 31,2022.To compared effect that before and after the implementation of QCC.Results After6 months of improvement,The utilization rate of main diagnosis mapping Z-code was decreased from 36.3%to 12.7%,goal achievement rate of 106.3%,improvement rate of 65.0%.Enrollment rate of major diagnostic was increased from 53.0%to 86.3%,goal achievement rate of 116.4%,Improvement rate of 62.8%.Conclu-sion We have changed the quality control management mode of diagnosis and coding by the QCC,implement targeted feedback,supervision,and training,establish a reward and punishment mechanism that matches indicators to improved accuracy of enroll-ment.Upgrading the quality management level of medical records and medical safety at the same time.Should continue to pro-mote theimplementation.

Objective:To investigate the impact on image quality of a new deep learning image reconstruction (DLIR) algorithm in dynamic CT myocardial perfusion imaging (CTP) and to explore whether the algorithm affects the quantification of myocardial blood flow (MBF) in swine.Methods:Dynamic CTP imaging was performed in five anesthetized domestic swine [body weight (58.6±1.9) kg], at both rest and stress state. The tube voltages were fixed at 100 kV, and the low-dose and high-dose scanning tube currents were set as 150 mA and 300 mA, respectively. The low-dose (LD) scan data were reconstructed with filtered back projection (FBP) and three different DLIR strengths (low, medium, and high). High-dose (HD) scan data were reconstructed with filtered back projection (FBP) only. Subjective (5-point scale) image quality was evaluated, and objective evaluations included image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) was performed. Linear regression was used to test the linear trend between DLIR algorithm strength and image quality. Data sets normality was determined by the Shapiro-Wilk test. Comparisons between groups were performed using Student′s t test for normally distributed data or the Wilcoxon rank-sum test for non-normally distributed data. Results:The mean effective radiation dose was 7.2 and 3.8 mSv for the HD protocol and the LD protocol, respectively, with statistically significant difference found between two protocols ( t=282.50, P<0.001). The image noise of the images obtained at LD protocol gradually decreased and the image SNR and CNR gradually increased with DLIR algorithm strength increased ( F=60.10,35.87,41.41; P for trend were all<0.001). As for DLIR-high strength (LD) and FBP (HD) images, the image noise values were (31.7±3.1) and (38.2±1.2) HU; SNR were 16.6±2.0 and 13.8±0.8; CNR were 14.5±1.7, 11.6±0.9, respectively, with significant differences found between two groups ( t=5.70, 4.15, 5.68; all P<0.05). The subjective scores of DLIR-high strength (LD) and FBP (HD) images were significantly different (4.8±0.4 and 4.2±0.6, Z=2.12, P<0.05). No significant differences were found between the MBF calculated from FBP (LD) and from DLIR-high strength (LD), with the values as (81.3±17.3) ml·100 ml -1·min -1 vs. (79.9±18.3)ml·100 ml -1·min -1 at rest state; and (99.4±24.9)ml·100 ml -1·min -1 vs. (100.7±27.3) ml·100 ml -1·min -1 at stress state ( t=1.10, 0.89; P>0.05). Conclusion:DLIR-high strength can improve image quality of myocardial CTP in swine, and can reduce radiation dose without influencing the MBF calculation.

Objective: To perform the bacterial endotoxin test of Pulse-Engendering Injection.Methods: The interference actions of the different dilutabilities of injection at the greatest effective diluent range were observed with some sensitivity of TAL. Results: When 0.5EU/ml sensitivity of TAL was used and the dilutability of sample was 1∶8, the injection showed obvious enhancement action, but when 0.25EU/ml senitiity of TAL was used and the dilutability was 1∶16, the enhancement action of injection could be eliminated. Conclusion: The bacterial endoxin test can be carried out with 0.25EU/ml sensitivity of TAL when the dilutability of sample is 1∶16, the limit dose of bacterial endotoxin is controlled thereby.