Objective:To explore the prescription ideas of treating phlegm-drinking disease in Wang Xugao Lin Zheng Yi An; To analyze the medication law of Wang Xugao's clinical treatment of phlegm-drinking disease. Methods:The database was established based on the medical records of the chapter of phlegm, fluid retention and liver wind and phlegm fire contained in Wang Xugao Lin Zheng Yi An. Excel 2017 software was used to analyze the frequency, taste and meridian tropism of all Chinese materia medica. For Chinese materia medica with frequency≥10, IBM SPSS Modeler 18 software was used to analyze the association rules based on Apriori algorithm, and SPSS 25.0 software was used for cluster analysis based on Ochiai algorithm. Results:A total of 80 medical cases were included, involving 114 prescriptions, including 191 flavors of Chinese materia medica . High-frequency Chinese materia medica mainly included Poria, Pinelliae Rhizoma, Citri Reticulatae Pericarpium, Atractylodis Macrocephalae Rhizoma and Armeniacae Semen Amarum, etc. The main properties in Wang Xugao's medication for the treatment of phlegm-drink disease were warm, followed by cold and mild. The main tastes were sweet, bitter and pungent. Drugs mainly belong to the lung meridian and spleen, stomach, liver, kidney meridians; several core medicinal pairs were obtained, such as Farfarae Flos - Armeniacae Semen Amarum, Pinelliae Rhizoma - Zingiberis Rhizoma, Uncariae Ramulus cum Uncis - Haliotidis Concha, etc. Eight groups of core drug combinations could be sorted out by clustering analysis.Conclusions:In the treatment of phlegm-drinking disease, Wang Xugao paid attention to the simultaneous treatment of multiple viscera to coordinate the balance between the viscera, emphasized the complex etiology of phlegm-drinking disease combined with cold, fire and dampness, attached importance to the treatment of healthy qi to retreat pathogens, the regulation of three-energizer to regulate qi flow. The treatment of three-energizer, promoting yang and reducing phlegm, clearing liver and dispelling wind are the main methods. Medication mainly chooses properties of sweet and warm, with bitter and pungent.

Objective To understand the levels and trends of personal doses of occupational external exposure among radiation workers in medical institutions in Huizhou City and to improve radiation protection management. Methods Thermoluminescent dosimetry was employed to monitor the personal doses of occupational external exposure of radiation workers over monitoring cycles spanning three months each. Results From 2019 to 2023, a total of 25 796 monitoring instances were recorded for radiation workers in medical institutions in Huizhou City. Diagnostic radiology workers accounted for the largest proportion of workforce in the occupational categories, followed by interventional radiology workers. The average annual effective dose per person ranged from 0.21 to 0.30 mSv, with an average of 0.26 mSv. The majority of annual effective dose per person was below 1.0 mSv, with no instances exceeding 20 mSv. Among all occupational categories, nuclear medicine workers had the highest average annual effective dose per person at 0.43 mSv, followed by interventional radiology workers at 0.37 mSv. There was a significant difference in the average annual effective dose per person among different occupational categories (P < 0.05), with nuclear medicine and interventional radiology workers having higher doses than workers in diagnostic radiology, dental radiology, and other applications (all P < 0.05). Conclusion The personal dose monitoring results for radiation workers in medical institutions in Huizhou City are at low levels, indicating that the radiation protection in the local medical institutions is sufficient and can effectively protect the occupational health of radiation workers.

Objective:To develop and validate a predictive model of 28-day mortality in sepsis based on lactate dehydrogenase-to-albumin ratio (LAR).Methods:Sepsis patients diagnosed in the department of intensive care medicine of the First Affiliated Hospital of Soochow University from August 1, 2017 to September 1, 2022 were retrospective selected. Clinical data, laboratory indicators, disease severity scores [acute physiology and chronic health evaluation Ⅱ(APACHEⅡ), sequential organ failure assessment (SOFA)] were collected. Patients were divided into death group and survival group according to whether they died at 28 days, and the difference between the two groups was compared. The dataset was randomly divided into training set and validation set according to 7∶3. Lasso regression method was used to screen the risk factors affecting the 28-day death of sepsis patients, and incorporating multivariate Logistic regression analysis (stepwise regression) were included, a prediction model was constructed based on the independent risk factors obtained, and a nomogram was drawn. The nomogram prediction model was established. Receiver operator characteristic curve (ROC curve) was drawn to analyze and evaluate the predictive efficacy of the model. Hosmer-Lemeshow test, calibration curve and decision curve analysis (DCA) were used to evaluate the accuracy and clinical practicability of the model, respectively.Results:A total of 394 patients with sepsis were included, with 248 survivors and 146 non-survivors at 28 days. Compared with the survival group, the age, proportion of chronic obstructive pneumonia, respiratory rate, lactic acid, red blood cell distribution width, prothrombin time, activated partial thromboplastin time, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, creatinine, blood potassium, blood phosphorus, LAR, SOFA score, and APACHEⅡ score in the death group were significantly increased, while oxygenation index, monocyte count, platelet count, fibrinogen, total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein, and blood calcium were significantly reduced. In the training set, LAR, age, oxygenation index, blood urea nitrogen, lactic acid, total cholesterol, fibrinogen, blood potassium and blood phosphorus were screened by Lasso regression. Multivariate Logistic regression analysis finally included LAR [odds ratio ( OR) = 1.029, 95% confidence interval (95% CI) was 1.014-1.047, P < 0.001], age ( OR = 1.023, 95% CI was 1.005-1.043, P = 0.012), lactic acid ( OR = 1.089, 95% CI was 1.003-1.186, P = 0.043), oxygenation index ( OR = 0.996, 95% CI was 0.993-0.998, P = 0.002), total cholesterol ( OR = 0.662, 95% CI was 0.496-0.865, P = 0.003) and blood potassium ( OR = 1.852, 95% CI was 1.169-2.996, P = 0.010). A total of 6 predictor variables were used to establish a prediction model. ROC curve showed that the area under the curve (AUC) of the model in the training set and validation set were 0.773 (95% CI was 0.715-0.831) and 0.793 (95% CI was 0.703-0.884), which was better than APACHEⅡ score (AUC were 0.699 and 0.745) and SOFA score (AUC were 0.644 and 0.650), and the cut-off values were 0.421 and 0.309, the sensitivity were 62.4% and 82.2%, and the specificity were 82.2% and 68.9%, respectively. The results of Hosmer-Lemeshow test and calibration curve showed that the predicted results of the model were in good agreement with the actual clinical observation results, and the DCA showed that the model had good clinical application value. Conclusion:The prediction model based on LAR has a good predictive value for 28-day mortality in patients with sepsis and can guide clinical decision-making.

Objective:To analyze and verify the distribution characteristics of radiation dose on the body surface of surgeons in cardiovascular interventional treatment,so as to provide theoretical basis for studying the characteristics of radiation dose and implementing radiation protection correctly.Methods:During cardiovascular interventional surgery,three pieces of lead protective clothing(designated as lead protective clothing A,B,and C)were provided in the room of digital subtraction angiography(DSA)equipment.Each piece of these protective clothing included one lead scarf,one lead vest and one lead apron,and the lead equivalents of them were all 0.5 mmPb.A thermoluminescence dosimeter was placed on the outer surface of the lead protective clothing that was worn by surgeon,and the radiation dose values of the front and back,vertical and horizontal surfaces of the three pieces of lead protective clothing were compared.Results:The measured average values of the front dosimeter of the three pieces of lead protective clothing were respectively(296.2±31.9)mSv,(196.3±20.2)mSv and(299.4±33.0)mSv,which were significantly higher than those of the back of the lead protective clothing,and the differences were statistically significant(Z=-5.522,-5.115,-4.817,Z=-5.522,-5.115,-4.817,P<0.05).The values of abdominal radiation doses on the vertical plane of the three pieces of lead protective clothing were the highest,which were respectively(356.7±58.2)mSv,(217.7±31.8)mSv and(387.4±46.3)mSv.The measured values of the dosimeter on the left side of the horizontal plane of the A,B of lead protective clothing were respectively(341.6±58.5)mSv and(229.1±32.4)mSv,which were all higher than that on the right side,with statistical significances(Z=5.890,9.068,P<0.05).The measured value of the left side of lead protective clothing was respectively higher than that of the middle side and the right side,and the differences were statistically significant(Z=5.846,9.766,P<0.05).Conclusion:The radiation dose of the front of the body surface of surgeon who undergo DSA intervention is significantly higher than that in the back of that,and the radiation dose of the abdomen on the vertical plane of the body is the highest,and the radiation dose of horizontal plane appears a decreasing trend from left to right.The detected dose data and distribution characteristics of radiation can provide research basis for radiation protection.

Objective:To investigate the value of a preoperatively MRI-based deep learning (DL) radiomics machine learning model to distinguish low-grade and high-grade soft tissue sarcomas (STS).Methods:From November 2007 to May 2019, 151 patients with STS confirmed by pathology in the Affiliated Hospital of Qingdao University were enrolled as training sets, and 131 patients in the Affiliated Hospital of Shandong First Medical University and the Third Hospital of Hebei Medical University were enrolled as external validation sets. According to the French Federation Nationale des Centres de Lutte Contre le Cancer classification (FNCLCC) system, 161 patients with FNCLCC grades Ⅰ and Ⅱ were defined as low-grade and 121 patients with grade Ⅲ were defined as high-grade. The hand-crafted radiomic (HCR) and DL radiomic features of the lesions were extracted respectively. Based on HCR features, DL features, and HCR-DL combined features, respectively, three machine-learning models were established by decision tree, logistic regression, and support vector machine (SVM) classifiers. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each machine learning model and choose the best one. The univariate and multivariate logistic regression were used to establish a clinical-imaging factors model based on demographics and MRI findings. The nomogram was established by combining the optimal radiomics model and the clinical-imaging model. The AUC was used to evaluate the performance of each model and the DeLong test was used for comparison of AUC between every two models. The Kaplan-Meier survival curve and log-rank test were used to evaluate the performance of the optimal machine learning model in the risk stratification of progression free survival (PFS) in STS patients.Results:The SVM radiomics model based on HCR-DL combined features had the optimal predicting power with AUC values of 0.931(95%CI 0.889-0.973) in the training set and 0.951 (95%CI 0.904-0.997) in the validation set. The AUC values of the clinical-imaging model were 0.795 (95%CI 0.724-0.867) and 0.615 (95%CI 0.510-0.720), and of the nomogram was 0.875 (95%CI 0.818-0.932) and 0.786 (95%CI 0.701-0.872) in the training and validation sets, respectively. In validation set, the performance of SVM radiomics model was better than those of the nomogram and clinical-imaging models ( Z=3.16, 6.07; P=0.002,<0.001). Using the optimal radiomics model, there was statistically significant in PFS between the high and low risk groups of STS patients (training sets: χ2=43.50, P<0.001; validation sets: χ2=70.50, P<0.001). Conclusion:Preoperative MRI-based DL radiomics machine learning model has accurate prediction performance in differentiating the histopathological grading of STS. The SVM radiomics model based on HCR-DL combined features has the optimal predicting power and was expected to undergo risk stratification of prognosis in STS patients.

Objective:To investigate the effects of long-term ionizing radiation on peripheral blood cells of nuclear power workers.Methods:In March 2019, a total of 530 radiation exposed workers in the nuclear power industry who underwent in-service radiation occupational health examination in Guangzhou occupational disease prevention and control hospital in 2018 and with service age ≥1 year were selected as the radiation group. At the same time, 545 workers in nuclear power industry were selected as control group. According to the methods and requirements of GBZ 235-2011 ＂technical specification for occupational health monitoring of radiation workers＂ and GBZ 98-2017 ＂health requirements for radiation workers＂, the occupational health monitoring data were collected, and the change rules of peripheral blood cells in the two groups were analyzed.Results:Compared with the control group, the total number of WBC, NEUT, LYMP, Hb, MCV and MCHC in radiation group were lower than those in control group ( P<0.05) , and the difference was statistically significant ( P<0.05) . The MPV increased significantly ( P<0.05) . Compared with the control group, the abnormal rate of WBC and Hb in the radiation group was higher than that in the control group ( P<0.01) , but there was no significant difference in the abnormal rate of RBC and PLT ( P>0.05) . Conclusion:Low dose ionizing radiation has a certain cumulative damage effect on peripheral blood cells of radiation workers in nuclear power industry. The change rules of different cell subtypes are different, and the changes of WBC and PLT appear earlier.

Objective:To investigate the effects of long-term ionizing radiation on peripheral blood cells of nuclear power workers.Methods:In March 2019, a total of 530 radiation exposed workers in the nuclear power industry who underwent in-service radiation occupational health examination in Guangzhou occupational disease prevention and control hospital in 2018 and with service age ≥1 year were selected as the radiation group. At the same time, 545 workers in nuclear power industry were selected as control group. According to the methods and requirements of GBZ 235-2011 ＂technical specification for occupational health monitoring of radiation workers＂ and GBZ 98-2017 ＂health requirements for radiation workers＂, the occupational health monitoring data were collected, and the change rules of peripheral blood cells in the two groups were analyzed.Results:Compared with the control group, the total number of WBC, NEUT, LYMP, Hb, MCV and MCHC in radiation group were lower than those in control group ( P<0.05) , and the difference was statistically significant ( P<0.05) . The MPV increased significantly ( P<0.05) . Compared with the control group, the abnormal rate of WBC and Hb in the radiation group was higher than that in the control group ( P<0.01) , but there was no significant difference in the abnormal rate of RBC and PLT ( P>0.05) . Conclusion:Low dose ionizing radiation has a certain cumulative damage effect on peripheral blood cells of radiation workers in nuclear power industry. The change rules of different cell subtypes are different, and the changes of WBC and PLT appear earlier.

Objective: To explore the impact of welding operations on the health status of workers with low working age, and provide a basis for occupational health risk assessment for workers of low working age. Methods: Used the method of cluster sampling to randomly selected workers from an automobile manufacturing plant in Guangzhou as research subjects: 982 workers with welding posts of 1 year ≤working age ≤5 years were welding groups, 707 workers with simple exposure noise of 1 year ≤working age ≤5 years were assembly groups, and 717 workers in pre-job medical examinations were pre-job groups from June 2017 to September 2018. Then conducted occupational health checks on all subjects, investigated and detected the occupational hazards in welding posts and assembly posts. Results: There was no statistical difference between the noise over-standard rate of welding posts' (59.3%, 16/27) and the assembly posts' (47.4%, 9/19) (P>0.05) . The over-standard rate of welding fume, manganese and its inorganic compounds in welding posts was 11.11% (3/27) . The results of occupational health examination showed that the detection rate of disease or abnormal of the welding group was 78.4% (770/982) higher than 70.2% (496/707) in the assembly group and 53.0% (380/717) in the pre-job group (the value of 2 were 14.92 and 122.37, respectively, P<0.05) . The rate of hearing loss of the assembly group and the welding group were 14.7% (104/707) and 19.3% (190/982) , respectively, which was higher than that of the pre-job group (10.5%, 75/717) , and the hearing loss rate gradually increased with the increase of working age (the value of linear-by-linear association were 12.04 and 44.67, respectively, P<0.01) . Compared with the hearing loss rate of each working age of the assembly group, the hearing loss rate of each working age of the welding group was higher, and when the working age was 3 years, the risk of hearing loss in the welding group was 2.70 times that of the assembly group (P<0.01) . The rate of pulmonary dysfunction in the welding group was 19.2% (189/982) higher than that in the pre-job group (12.6%, 90/717) , and it increased with the increase of working age (the value of linear-by-linear association was 15.97, P<0.01) . Conclusion Welding work seriously damages the health of workers with low working age, increases the hearing loss of workers and the occurrence of pulmonary dysfunction; manganese and its compounds increases noise-induced damage to the hearing system.

OBJECTIVE: To explore the combined effect of noise and other occupational hazards on hearing impairment and electrocardiograph(ECG) of workers in automobile manufacturing enterprises. METHODS: A judgment sampling method was used to select 3 434 workers as study subjects from an automobile manufacture enterprise. According to the exposure to different types of occupational hazardous factors, they were divided into noise series group, noise dust group, noise welding dust group, noise benzene series group, noise nitrogen oxide group and control group, with 716, 693, 1 540, 45, 195 and 245 cases in each group, respectively. The subjects were examined with pure-tone hearing test and ECG. RESULTS: The total rate of high frequency hearing loss was 11.2%(385/3 434), and high frequency hearing loss was the main type of hearing loss among workers in each group. The simple high-frequency hearing loss rates of noise group, noise dust group, noise welding dust group, noise benzene series group, noise nitrogen oxide group and the control group were 10.3%, 11.5%, 12.3%, 26.7%, 10.3% and 4.1% respectively, and the rate of total hearing loss were 13.7%, 14.6%, 14.6%, 31.1%, 16.9% and 6.5% respectively. Compared with the control group, the rate of simple high-frequency hearing loss and total hearing loss were higher in the other 5 groups(P<0.005). The rate of high-frequency hearing loss in noise group was lower than that in noise benzene series group(P<0.005). The rate of arrhythmia was 20.9%(717/3 434). Arrhythmia was the main type of ECG abnormality in all groups. The rates of arrhythmia in noise group, noise dust group, noise welding dust group, noise benzene series group, noise nitrogen oxide group and control group were 16.9%, 16.6%, 27.9%, 17.8%, 13.8% and 6.9%, respectively. The rate of arrhythmia in noise welding dust group was higher than that in noise group(P<0.005). CONCLUSION: The combined effect of noise and benzene series increases the risk of high-frequency hearing loss in workers. The combined effect of noise and welding dust increases the risk of arrhythmia in workers.

Objective To investigate a new clinical classification of hepatolithiasis based on biliary anatomy and pathology in order to guide clinical decision-making.Methods The cases of hepatolithiasis admitted to our hospital from Mar 2015 to Aug 2018 were classified into six types and an additional type according to biliary anatomy,stone site and extent,liver pathological changes,and Oddi sphincter function.Results Of the214 cases of hepatolithiasis,5 cases (2.3％) were type Ⅰ;41 cases (19.2％) were type Ⅱ;76 cases (35.5％) were type Ⅲ;17 cases (7.9％) were type Ⅳ;29 cases (13.5％) were type Ⅴ;46 cases (21.5％) of type Ⅵ.The most common complication was incision infection (28 cases,13.1％),liver failure 0,and perioperative death 0.During the follow-up from 3 months to 3 years,there were 14cases of stone recurrence,the recurrence rate was 7.6％.Conclusion This classification scheme and the "individualized precise anatomical combined hepatectomy or segmental hepatectomy" based on this classification is safe and effective while enhancing the cure rate.