Objective To explore the epidemiological characteristics of gouty arthritis in Northwest China from 2023 to 2025, and to formulate preventive intervention measures. Methods By retrospectively analyzing the case data of medical institutions in Northwest China from January 2023 to June 2025 (a total of 8 139 cases), the incidence trend and population distribution characteristics of gouty arthritis in this area were analyzed. Multivariate logistic regression analysis was performed to identify risk factors. Results From 2023 to 2025, the prevalence rate of gouty arthritis in adult residents in Northwest China was 3.74% (304/8 139). Among the sites affected by gouty arthritis, the metatarsophalangeal joint accounted for the highest proportion (P<0.05). From the perspective of age distribution, the prevalence rate was the highest in 40-59 years old group (5.90%), followed by 66-80 years old group (4.21%) and >80 years old group (2.75%). The incidence rate in 40-65 years old group was higher than that in the other age groups (P<0.05). High blood uric acid and creatinine, alcohol drinking, obesity, high purine diet, concurrent chronic kidney disease and metabolic syndrome were risk factors affecting gouty arthritis in Northwest China (P<0.05). Conclusion High blood uric acid level, high creatinine level, alcohol drinking, obesity, high purine diet, concurrent chronic kidney disease and metabolic syndrome are risk factors influencing gouty arthritis in Northwest China. Based on the above factors, this study proposes comprehensive prevention strategies from the individual, community and public health levels to provide a scientific basis for reducing the incidence rate of gouty arthritis.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

This article summarizes the current application of Traditional Chinese Medicine (TCM) nursing techniques in clinical nursing of obstetrics and gynecology, providing a reference for the clinical nursing and related research of obstetric and gynecological diseases in TCM, and promoting the widespread application of TCM nursing techniques in obstetrics and gynecology.

Objective:To analyze the cardiac dosimetry of lymph node irradiation in the internal breast region after left-sided breast cancer surgery and to assess its impact on patients' quality of life.Methods:The clinical data of 108 patients who underwent inverse intensity modulated radiotherapy (IMRT) after left-sided breast cancer surgery in Cancer Hospital of Nantong University from May 2019 to May 2021 were collected and retrospectively analyzed, and divided into a study group (with internal breast, 55 cases) and a control group (without internal breast, 53 cases) according to whether the postoperative radiotherapy included lymph node irradiation in the internal breast region. The dosimetric indexes of planned target area (PTV) , cardiac tolerance, serum myocardial injury markers and quality of life before and after radiotherapy were compared between the two groups.Results:In terms of PTV dosimetry, the conformality index (CI) of the study group and the control group were 0.73±0.07 and 0.75±0.08, the homogeneity index (HI) were 0.17±0.03 and 0.17±0.02, the D max were (55.69±1.02) Gy and (55.46±1.13) Gy, the D mean were (50.54±0.23) Gy and (50.48±0.21) Gy respectively, there were no statistically significant differences ( t=1.38, P=0.169; t<0.01, P>0.999; t=1.11, P=0.269; t=1.41, P=0.160) . In terms of cardiac receptivity, the D mean of the two groups were (5.93 ± 0.32) Gy, (5.64 ± 0.30) Gy, V 40 were (0.47 ± 0.10) %, (0.41 ± 0.11) %, and V 30 were (2.48 ± 0.51) %, (2.06 ± 0.49) % respectively, and there were statistically significant differences ( t=4.86, P<0.001; t=2.97, P=0.004; t=4.36, P<0.001) . The levels of serum troponin Ⅰ (cTnⅠ) before radiotherapy in the study group and the control group were (0.09±0.02) ng/ml and (0.09±0.01) ng/ml, creatine kinase isoenzyme MB (CK-MB) were (0.27±0.08) U/L and (0.25±0.08) U/L, myoglobin (MYo) were (3.84±1.02) μg/L and (3.69±0.97) μg/L, and brain natriuretic peptide (BNP) were (172.35±16.24) pg/ml and (169.81±15.93) pg/ml respectively, there were no statistically significant differences ( t<0.01, P>0.999; t=1.30, P=0.197; t=0.78, P=0.436; t=0.82, P=0.414) . One month after radiotherapy, the levels of serum cTnⅠ in the two groups were (0.09±0.03) ng/ml and (0.09±0.02) ng/ml, CK-MB were (0.29±0.09) U/L and (0.28±0.08) U/L, MYo were (4.06±1.08) μg/L and (4.01±1.03) μg/L, and BNP were (175.13±17.09) pg/ml, (172.47±16.28) pg/ml respectively, there were no statistically significant differences ( t<0.01, P>0.999; t=0.61, P=0.544; t=0.25, P=0.806; t=0.83, P=0.410) . The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) scores before radiotherapy in the study and the control groups were (60.24±5.13) points and (61.19±5.46) points, (74.12±7.20) points and (75.35±7.88) points at 1 month after radiotherapy, (77.53±7.14) points and (78.95±7.08) points at 6 months after radiotherapy, and (75.02±6.93) points and (76.68±6.74) points at 1 year after radiotherapy respectively, there were no statistically significant differences ( t=0.93, P=0.353; t=0.85, P=0.399; t=1.04, P=0.302; t=1.26, P=0.210) . The EORTC QLQ-C30 scores at 1 month, 6 months, and 1 year after radiotherapy were higher than those before radiotherapy in the two groups, and there were statistically significant differences (all P<0.001) . Conclusion:IMRT containing lymph node irradiation in the internal breast region after left breast cancer surgery brings a certain degree of increased cardiac dose, but it is feasible to control it within a certain range and does not affect the patients' cardiac function or quality of life in the short term.

Objective:To provide a reference for in-depth application and research in the field of coronary heart disease traditional Chinese medicine (TCM) nursing. Based on the CiteSpace software, the development trend and research hotspots of the literature are displayed and analyzed in this field.Methods:The China Knowledge Network (CNKI) database was used to retrieve the literature related to the research in this field published in the past 20 years from January 1st 2001 to October 5th 2021, and CiteSpace was used to visually analyze the number of articles, research institutions, authors and keywords, and to interpret its meaning in combination with the content of the atlas.Results:The amount of research literature in this field was generally on the rise, but the cooperation between various research institutions and authors needs to be strengthened. Research hotspots mainly focused on five areas: coronary heart disease-related symptom care, the application of characteristic TCM nursing techniques, the outcome indicators of the research, the TCM health management of patients with coronary heart disease, and the application model of TCM nursing.Conclusions:It is recommended to strengthen multidisciplinary and teamwork in this field, carry out high-quality randomized controlled studies, and focus on related research on multiple nursing models, evaluation tools, and symptom management.

Objective:To evaluate the usability of gamification coronary heart disease health management platform based on WeChat, so as to provide support for self-management of coronary heart disease patients.Methods:From November to December 2022, 10 patients with coronary heart disease who were treated at Dongzhimen Hospital of Beijing University of Chinese Medicine were selected using convenience sampling. The research subjects registered for the health management platform by scanning the QR code and underwent a 2-month trial experience. Two months later, researchers collected data from the platform and used a combination of questionnaire surveys and qualitative interviews to investigate the user's experience and feedback of the research subjects, in order to evaluate the usability of the platform.Results:Within two months, the health management platform had 226 visits, an average visit time of 26 minutes, and an availability questionnaire score of (71.8±2.8). The research subjects had an acceptable attitude towards the usability of this platform, had a good overall user experience, and had also provided improvement suggestions for the platform while they gained beneficial experiences.Conclusions:The gamification coronary heart disease health management platform based on WeChat has good usability, providing a feasible means for the health management of heart disease patients, and also providing reference for other chronic disease health management projects involving lifestyle changes and incentives.

This paper summarizes the current situation and necessity of the training of traditional Chinese medicine (TCM) nursing specialists in China, as well as the existing achievements and existing problems, and puts forward the prospects and suggestions for the training of TCM nursing team, so as to strengthen the construction of TCM nursing culture, build a high-quality TCM nursing talent team, and promote the high-quality development of TCM nursing.

Objective:To develop and evaluate the Self-rating Identification Scale for Common Syndromic Elements of Coronary Heart Disease.Methods:The item pool of the Self-rating Identification Scale for Common Syndromic Elements of Coronary Heart Disease was formed through literature review and expert consultation. Items were screened by combining frequency, correlation coefficient, Cronbach's α coefficient and factor analysis. Subjective and objective weighting was used to determine the weight of items, and diagnostic threshold was determined by receiver operator characteristic curve. Cronbach's α coefficient and factor analysis were used to test the reliability and validity of the scale.Results:The Self-rating Identification Scale for Common Syndromic Elements of Coronary Heart Disease had a total of 6 syndrome elements and 36 items. It included 3 items of blood stasis, 9 items of phlegm, 7 items of Qi stagnation, 5 items of Qi deficiency, 6 items of Yin deficiency, and 6 items of Yang deficiency, and the diagnostic thresholds were 1.000, 45.300, 36.400, 66.600, 33.900, and 30.500 respectively. The test-retest reliability coefficients of each dimension of the scale were all greater than 0.7, and the internal consistency reliability coefficients of each dimension were 0.540 to 0.848. In the factor analysis, each variable with a common factor load coefficient greater than 0.4 was extracted, and the results were completely consistent with the scale entry settings. The cumulative variance contribution rate was 53.822%.Conclusions:The reliability and validity of the Self-rating Identification Scale for Common Syndromic Elements of Coronary Heart Disease are good, and it has scientific research and clinical application value.

Objective:To investigate the use intention of patients with coronary heart disease for mobile health and understand needs of patients for gamification design of mobile health platform, in order to improve the self-management level of patients with coronary heart disease by building a gamified mobile health platform.Methods:Using the convenient sampling method, a total of 181 hospitalized patients with coronary heart disease (CHD) in Department of Cardiology from July to September 2020 (3 hospitals in Beijing and 1 hospital in Heilongjiang Province) were selected as research objects. Questionnaire on the usage needs of mobile health platform for coronary heart disease was used to investigate them.Results:Only 8 of the 181 patients (4.42%) used cardiac mobile health, and 113 (62.43%) patients never used cardiac mobile health but would consider using it. But 60 (33.15%) patients never used cardiac mobile medical experience and said that they won' t use it in the future, and the reasons included operation, language, safety, need awareness and health concerns. Among 121 patients with coronary heart disease, the top three requirements for gamification design were human-computer interaction encouragement and company (32.23%) , completion of tasks to exchange for real prizes (30.58%) and health ranking (28.10%) .Conclusions:Based on needs of patients, an easy-to-use, scientific and readable gamified mobile health platform for coronary heart disease should be built, mobile health publicity should be increased, and the continuous use rate of the mobile health platform and the self-management of patients should be improved.