The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Objective:To investigate the value of tumor volume to uterine volume ratio (N/U) combined with the expression of alpha-fetoprotein (AFP), sugar antigen 199 (CA199) and human epididymal secretory protein 4 (HE4) in evaluating the pathologic grade and prognosis of endometrial carcinoma (EC) .Methods:A total of 160 EC patients admitted to Linyi Central Hospital from Jan. 2021 to Dec. 2023 were divided into low-grade group and high-grade group according to FIGO grading method, and were divided into poor prognosis group and good prognosis group according to cancer death, recrudescence. The levels of N/U, AFP, CA199 and HE4 in patients with different pathologic grades and prognosis were compared. COX regression was used to analyze the influencing factors of EC adverse prognosis, ROC curve was used to analyze the value of N/U combined with serum AFP, CA199 and HE4 in predicting EC adverse prognosis, and a nomogram model was constructed.Results:Pathological examination of 160 EC patients showed that 12 cases were non-endometrioid adenocarcinoma, 148 cases were endometrioid adenocarcinoma, 41 cases were high-grade and 119 cases were low-grade.According to the follow-up, 94 of the 160 EC patients had good prognosis and 66 had poor prognosis. The levels of N/U, AFP, CA199 and HE4 in the poor prognosis group were higher than those in the good prognosis group ( P<0.05). COX regression analysis showed that high levels of N/U, AFP, CA199 and HE4 were all factors affecting the poor prognosis of EC patients ( P<0.05). The AUC value of combined detection of N/U, AFP, CA199 and HE4 in predicting adverse prognosis of EC patients was higher than that of single detection ( Z=3.140, 3.658, 4.277, 4.378, P<0.05) .The ROC curve AUC (95% CI) of the training set and the validation set were 0.84 (0.77-0.92) and 0.90 (0.81-0.98) respectively for the training set and the validation set to predict the adverse prognosis of EC patients. Calibration curve results showed that the calibration curve for EC patients predicted by the nomogram model was close to the ideal curve ( P=0.521, 0.743). The DCA curve shows that the probability threshold of the nomogram model has a higher positive net return at 20%~100%. Conclusion:The levels of N/U, AFP, CA199 and HE4 in EC patients are related to the pathologic grade, and the combined detection of these indicators can predict the poor prognosis of EC patients, and the nomogram model constructed based on these indicators has high predictive value.

Objective:To study the implementation progress of the prevention and control measures for drinking water-borne endemic fluorosis and the changing trend of fluorosis conditions in Inner Mongolia Autonomous Region, comprehensively evaluate the effectiveness of prevention and control measures, and provide a basis for the next step of prevention and control of the disease.Methods:In 2015 and 2023, a cross-sectional survey method was used to investigate the water improvement situation, the operation of water improvement projects, the detection of fluoride level in water, and the prevalence of dental fluorosis in children aged 8 to 12 in all affected villages of 11 leagues (cities) in the entire autonomous region. The prevention and control effect of drinking water-borne endemic fluorosis in the entire autonomous region was evaluated.Results:The water improvement rates of all affected villages in the entire autonomous region in 2015 and 2023 were 84.12% (8 218/9 769) and 95.38% (8 944/9 377), respectively. The qualified rates of water fluoride in the villages with water improvement in the entire autonomous region were 66.21% (5 441/8 218) and 91.00% (8 139/8 944), respectively. The water improvement rate and water fluoride qualification rate of water improvement villages in 2023 were both higher than those in 2015, and the differences were statistically significant (χ 2 = 652.96, 1 593.81, P < 0.001). The detection rates of dental fluorosis in children aged 8 to 12 years in the entire autonomous region in 2015 and 2023 were 9.26% (7 548/81 484) and 4.46% (3 441/77 155), respectively. The detection rate of dental fluorosis in children in 2023 was lower than that in 2015, and the difference was statistically significant (χ 2 = 1 418.20, P < 0.001). In 2015 and 2023, the total compliance rate of all affected villages in the entire autonomous region reaching the control standards were 57.94% (5 660/ 9 769) and 92.37% (8 662/9 377), respectively. The total compliance rate of all affected villages in 2023 was higher than that in 2015, and the difference was statistically significant (χ 2 = 3 010.38, P < 0.001). Conclusions:Compared with 2015, the prevention and control measures of drinking water-borne endemic fluorosis in Inner Mongolia Autonomous Region have been effectively implemented in 2023, with a significant decrease in the detection rate of dental fluorosis in children. However, there are still a few affected villages that have not achieved the control standards, and prevention and control work still need to be further strengthened.

Objective:To investigate the characteristics of the population of skeletal fluorosis patients in drinking-tea-borne endemic fluorosis (referred to as drinking-tea-borne fluorosis) areas in Inner Mongolia Autonomous Region (referred to as Inner Mongolia) and the influencing factors of treatment willingness, and to provide a basis for improving the prevention and control measures of drinking-tea-borne fluorosis and the treatment plan of skeletal fluorosis.Methods:From August to October 2022, a face-to-face questionnaire survey was conducted in key areas of drinking-tea-borne fluorosis in Inner Mongolia (administrative villages with an average daily intake of tea fluoride > 3.5 mg and skeletal fluorosis patients identified by the general survey of drinking-tea-borne fluorosis in Inner Mongolia in 2019), and to investigate the demographic, severity, and treatment status of patients with skeletal fluorosis, analyze the demographic characteristics of patients with skeletal fluorosis and the influencing factors of treatment willingness.Results:A total of 734 patients with skeletal fluorosis were investigated, including 543 mild cases, 125 moderate cases and 66 severe cases. The gender ratio of patients with skeletal fluorosis was 0.71 ∶ 1.00 (305/429), the age was concentrated in > 50 - 70 years old (70.57%, 518/734), the proportion of Mongolians was 94.28% (692/734), the proportion of herders was 97.68% (717/734), the educational level was mainly primary school (54.63%, 401/734), and the proportion of poor households and immigrants who had moved to their current residence was 7.08% (52/734) and 8.04% (59/734), respectively. The distribution of the severity of skeletal fluorosis in patients of different ages, genders, and educational levels was compared, and the differences were statistically significant ( P < 0.05). Fifty-three point two seven percent (391/734) of the patients had a willingness to undergo non-pharmacological treatment, of which 69.82% (273/391) had already started non-pharmacological treatment, with a treatment effectiveness rate of 73.99% (202/273). Sixty-five point two six percent (479/734) of the patients had a willingness to receive medication treatment, of which 7.31% (35/479) had already started medication treatment, with a treatment effectiveness rate of 54.29% (19/35). Zero point two seven percent (2/734) of the patients expressed a willingness to undergo surgical treatment, while no patients underwent surgical treatment. Multivariate logistic regression analysis showed that the age, ethnicity, occupation, educational level, poverty status, immigrants status, and the severity of skeletal fluorosis were all influencing factors of non-pharmacological treatment willingness ( P < 0.05). Occupation, educational level, poverty status, immigrants status, and the severity of skeletal fluorosis were all influencing factors of medication treatment willingness ( P < 0.05). Conclusions:Patients with skeletal fluorosis caused by tea drinking in Inner Mongolia are mainly from Mongolian ethnic groups, herders, middle-aged and elderly people, and those with a lower educational levels. The willingness of patients to receive treatment is influenced by various factors, and corresponding intervention measures can be formulated and taken based on these influencing factors to effectively improve the disease prevention awareness and treatment willingness of patients and the public.

Objective:To preliminarily establish a sample clot warning model for coagulation screening tests using 5 machine learning methods.Methods:This cross-sectional study collected 7 401 routine screening test samples from Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, from January 1st, 2015, to August 18th, 2024, including 4 786 clotted (positive) and 2 615 qualified (negative) samples for model development. The dataset was divided into Dataset 1 and Dataset 2 based on a reagent change for APTT in December 2018, with separate models developed for each. An additional 2 493 samples (October 31st to November 8th, 2024) were used to evaluate consistency between the model and manual assessment, while 23 200 samples (October 17th to December 31st, 2024) were used for assessing real-world predictive performance. Five machine learning algorithms were employed to develop the clot prediction model: logistic regression (LR), random forest (RF), extreme gradient boosting (XGBoost), naive bayes (NB), and artificial neural network (ANN), with the ANN model constructed using two different hidden layer and neuron parameter settings. Model selection was based on AUC, accuracy, sensitivity, specificity, F1-score, PPV, and NPV, with the optimal model integrated into the LIS for validation.Results:Among the six models using 5 machine learning algorithms, XGBoost demonstrated the highest performance (AUC=0.961, sensitivity=0.945, F1-score=0.934) and robustness to reagent changes ( Z=-1.333, P=0.113). When deployed, the differences between the model's predictions and manual pre-judgment were statistically significant ( Z=-5.289 to 8.933, all P<0.01). The predictive efficacy indices AUC (95% CI), sensitivity, specificity, and accuracy of the XGBoost model deployed in real-world operation of the LIS were 0.939 (0.918—0.960), 0.958, 0.921, and 0.921 respectively. Conclusion:In this study, a clot warning model for coagulation screening samples was established based on the XGBoost algorithm, and its prediction efficacy is good, providing a foundation for intelligent pre-analytical quality control for coagulation screening tests.

Objective:To investigate the value of tumor volume to uterine volume ratio (N/U) combined with the expression of alpha-fetoprotein (AFP), sugar antigen 199 (CA199) and human epididymal secretory protein 4 (HE4) in evaluating the pathologic grade and prognosis of endometrial carcinoma (EC) .Methods:A total of 160 EC patients admitted to Linyi Central Hospital from Jan. 2021 to Dec. 2023 were divided into low-grade group and high-grade group according to FIGO grading method, and were divided into poor prognosis group and good prognosis group according to cancer death, recrudescence. The levels of N/U, AFP, CA199 and HE4 in patients with different pathologic grades and prognosis were compared. COX regression was used to analyze the influencing factors of EC adverse prognosis, ROC curve was used to analyze the value of N/U combined with serum AFP, CA199 and HE4 in predicting EC adverse prognosis, and a nomogram model was constructed.Results:Pathological examination of 160 EC patients showed that 12 cases were non-endometrioid adenocarcinoma, 148 cases were endometrioid adenocarcinoma, 41 cases were high-grade and 119 cases were low-grade.According to the follow-up, 94 of the 160 EC patients had good prognosis and 66 had poor prognosis. The levels of N/U, AFP, CA199 and HE4 in the poor prognosis group were higher than those in the good prognosis group ( P<0.05). COX regression analysis showed that high levels of N/U, AFP, CA199 and HE4 were all factors affecting the poor prognosis of EC patients ( P<0.05). The AUC value of combined detection of N/U, AFP, CA199 and HE4 in predicting adverse prognosis of EC patients was higher than that of single detection ( Z=3.140, 3.658, 4.277, 4.378, P<0.05) .The ROC curve AUC (95% CI) of the training set and the validation set were 0.84 (0.77-0.92) and 0.90 (0.81-0.98) respectively for the training set and the validation set to predict the adverse prognosis of EC patients. Calibration curve results showed that the calibration curve for EC patients predicted by the nomogram model was close to the ideal curve ( P=0.521, 0.743). The DCA curve shows that the probability threshold of the nomogram model has a higher positive net return at 20%~100%. Conclusion:The levels of N/U, AFP, CA199 and HE4 in EC patients are related to the pathologic grade, and the combined detection of these indicators can predict the poor prognosis of EC patients, and the nomogram model constructed based on these indicators has high predictive value.

Objective:To study the implementation progress of the prevention and control measures for drinking water-borne endemic fluorosis and the changing trend of fluorosis conditions in Inner Mongolia Autonomous Region, comprehensively evaluate the effectiveness of prevention and control measures, and provide a basis for the next step of prevention and control of the disease.Methods:In 2015 and 2023, a cross-sectional survey method was used to investigate the water improvement situation, the operation of water improvement projects, the detection of fluoride level in water, and the prevalence of dental fluorosis in children aged 8 to 12 in all affected villages of 11 leagues (cities) in the entire autonomous region. The prevention and control effect of drinking water-borne endemic fluorosis in the entire autonomous region was evaluated.Results:The water improvement rates of all affected villages in the entire autonomous region in 2015 and 2023 were 84.12% (8 218/9 769) and 95.38% (8 944/9 377), respectively. The qualified rates of water fluoride in the villages with water improvement in the entire autonomous region were 66.21% (5 441/8 218) and 91.00% (8 139/8 944), respectively. The water improvement rate and water fluoride qualification rate of water improvement villages in 2023 were both higher than those in 2015, and the differences were statistically significant (χ 2 = 652.96, 1 593.81, P < 0.001). The detection rates of dental fluorosis in children aged 8 to 12 years in the entire autonomous region in 2015 and 2023 were 9.26% (7 548/81 484) and 4.46% (3 441/77 155), respectively. The detection rate of dental fluorosis in children in 2023 was lower than that in 2015, and the difference was statistically significant (χ 2 = 1 418.20, P < 0.001). In 2015 and 2023, the total compliance rate of all affected villages in the entire autonomous region reaching the control standards were 57.94% (5 660/ 9 769) and 92.37% (8 662/9 377), respectively. The total compliance rate of all affected villages in 2023 was higher than that in 2015, and the difference was statistically significant (χ 2 = 3 010.38, P < 0.001). Conclusions:Compared with 2015, the prevention and control measures of drinking water-borne endemic fluorosis in Inner Mongolia Autonomous Region have been effectively implemented in 2023, with a significant decrease in the detection rate of dental fluorosis in children. However, there are still a few affected villages that have not achieved the control standards, and prevention and control work still need to be further strengthened.

Objective:To investigate the characteristics of the population of skeletal fluorosis patients in drinking-tea-borne endemic fluorosis (referred to as drinking-tea-borne fluorosis) areas in Inner Mongolia Autonomous Region (referred to as Inner Mongolia) and the influencing factors of treatment willingness, and to provide a basis for improving the prevention and control measures of drinking-tea-borne fluorosis and the treatment plan of skeletal fluorosis.Methods:From August to October 2022, a face-to-face questionnaire survey was conducted in key areas of drinking-tea-borne fluorosis in Inner Mongolia (administrative villages with an average daily intake of tea fluoride > 3.5 mg and skeletal fluorosis patients identified by the general survey of drinking-tea-borne fluorosis in Inner Mongolia in 2019), and to investigate the demographic, severity, and treatment status of patients with skeletal fluorosis, analyze the demographic characteristics of patients with skeletal fluorosis and the influencing factors of treatment willingness.Results:A total of 734 patients with skeletal fluorosis were investigated, including 543 mild cases, 125 moderate cases and 66 severe cases. The gender ratio of patients with skeletal fluorosis was 0.71 ∶ 1.00 (305/429), the age was concentrated in > 50 - 70 years old (70.57%, 518/734), the proportion of Mongolians was 94.28% (692/734), the proportion of herders was 97.68% (717/734), the educational level was mainly primary school (54.63%, 401/734), and the proportion of poor households and immigrants who had moved to their current residence was 7.08% (52/734) and 8.04% (59/734), respectively. The distribution of the severity of skeletal fluorosis in patients of different ages, genders, and educational levels was compared, and the differences were statistically significant ( P < 0.05). Fifty-three point two seven percent (391/734) of the patients had a willingness to undergo non-pharmacological treatment, of which 69.82% (273/391) had already started non-pharmacological treatment, with a treatment effectiveness rate of 73.99% (202/273). Sixty-five point two six percent (479/734) of the patients had a willingness to receive medication treatment, of which 7.31% (35/479) had already started medication treatment, with a treatment effectiveness rate of 54.29% (19/35). Zero point two seven percent (2/734) of the patients expressed a willingness to undergo surgical treatment, while no patients underwent surgical treatment. Multivariate logistic regression analysis showed that the age, ethnicity, occupation, educational level, poverty status, immigrants status, and the severity of skeletal fluorosis were all influencing factors of non-pharmacological treatment willingness ( P < 0.05). Occupation, educational level, poverty status, immigrants status, and the severity of skeletal fluorosis were all influencing factors of medication treatment willingness ( P < 0.05). Conclusions:Patients with skeletal fluorosis caused by tea drinking in Inner Mongolia are mainly from Mongolian ethnic groups, herders, middle-aged and elderly people, and those with a lower educational levels. The willingness of patients to receive treatment is influenced by various factors, and corresponding intervention measures can be formulated and taken based on these influencing factors to effectively improve the disease prevention awareness and treatment willingness of patients and the public.

Objective:To preliminarily establish a sample clot warning model for coagulation screening tests using 5 machine learning methods.Methods:This cross-sectional study collected 7 401 routine screening test samples from Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, from January 1st, 2015, to August 18th, 2024, including 4 786 clotted (positive) and 2 615 qualified (negative) samples for model development. The dataset was divided into Dataset 1 and Dataset 2 based on a reagent change for APTT in December 2018, with separate models developed for each. An additional 2 493 samples (October 31st to November 8th, 2024) were used to evaluate consistency between the model and manual assessment, while 23 200 samples (October 17th to December 31st, 2024) were used for assessing real-world predictive performance. Five machine learning algorithms were employed to develop the clot prediction model: logistic regression (LR), random forest (RF), extreme gradient boosting (XGBoost), naive bayes (NB), and artificial neural network (ANN), with the ANN model constructed using two different hidden layer and neuron parameter settings. Model selection was based on AUC, accuracy, sensitivity, specificity, F1-score, PPV, and NPV, with the optimal model integrated into the LIS for validation.Results:Among the six models using 5 machine learning algorithms, XGBoost demonstrated the highest performance (AUC=0.961, sensitivity=0.945, F1-score=0.934) and robustness to reagent changes ( Z=-1.333, P=0.113). When deployed, the differences between the model's predictions and manual pre-judgment were statistically significant ( Z=-5.289 to 8.933, all P<0.01). The predictive efficacy indices AUC (95% CI), sensitivity, specificity, and accuracy of the XGBoost model deployed in real-world operation of the LIS were 0.939 (0.918—0.960), 0.958, 0.921, and 0.921 respectively. Conclusion:In this study, a clot warning model for coagulation screening samples was established based on the XGBoost algorithm, and its prediction efficacy is good, providing a foundation for intelligent pre-analytical quality control for coagulation screening tests.

Objective:To investigate the distribution of physical and chemical water improvement areas of drinking water-borne endemic fluorosis in Inner Mongolia Autonomous Region, as well as the use of household water purifiers.Methods:From April to October 2021, a survey was conducted in a drinking water-borne endemic fluorosis areas in Inner Mongolia Autonomous Region where physical and chemical water improvement was carried out. The survey included the basic situation of the affected villages (number of permanent households, number of permanent residents, historical water fluoride content) and the use of residential water purifiers. Household peripheral water samples were collected to test the water fluoride content. Water purifier installation rate, normal usage rate, qualified water fluoride rate in normal usage, and the proportion of households covered by filter replacement departments were calculated.Results:In Inner Mongolia Autonomous Region, the physical and chemical water improvement areas of drinking water-borne endemic fluorosis were distributed in 2 735 villages in 11 leagues (cities) throughout the region, with 192 950 permanent households and 540 216 permanent residents. The average historical water fluoride content in all leagues (cities) was 2.18 mg/L, and the current average water fluoride content was 0.40 mg/L. A total of 134 763 water purifiers were installed, with an installation rate of 69.84% (134 763/192 950). A total of 10 773 households were surveyed, with 10 396 households using water purifiers normally and a normal usage rate of 96.50% (10 396/10 773). Among them, 10 158 households had qualified water fluoride of normal usage, with a qualified water fluoride rate of 97.71% (10 158/10 396). Of the 10 396 households using water purifiers normally, 3 974 households (38.23%) had filter cartridges used within one year, and 3 961 households had qualified water fluoride, with a qualified rate of water fluoride of 99.67% (3 961/3 974). Six thousand four hundred and twenty-two households (61.77%) had filter cartridges used for more than one year, with 6 197 households had qualified water fluoride and a qualified rate of water fluoride of 96.50% (6 197/6 422). There was a statistically significant difference in the qualified rate of water fluoride between purifiers with different filter cartridge usage times (χ 2 = 110.73, P < 0.001). Among the 10 773 surveyed households, the filter cartridges replacement department covered 10 470 households, accounting for 97.19% (10 470/10 773). Conclusions:In Inner Mongolia Autonomous Region, the physical and chemical water improvement areas of drinking water-borne endemic fluorosis are widely distributed, and the normal usage rate of household water purifiers is relatively high. The qualified rate of water fluoride in household water purifiers with filter cartridges used for more than one year is low.