To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

To standardize the clinical application of oral Chinese patent medicines （CPMs）， and address the safety issues arising from their dosage form characteristics， irrational clinical use， and the lack of targeted pharmacovigilance systems， the China Association of Chinese Medicine organized the formulation and release of Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines， aiming to inform the safe clinical use of oral CPMs and related pharmacovigilance work. According to the principles of GB/T1.1—2020 and the Drug Administration Law of the People's Republic of China （2019 revision）， the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， led a drafting group comprising 18 institutions. After multiple rounds of expert interviews， literature retrieval， evidence screening， and extensive solicitation of opinions， the Guidelines were registered internationally. Systematic standardization focused on safety monitoring， risk identification， assessment， control， and other aspects. The Guidelines clarified the characteristics of oral CPMs in terms of safety monitoring， known risks， and potential risks， compared to non-oral CPMs. Then， risk control measures were proposed， including medication in special populations and irrational medication. As a special guideline for pharmacovigilance in the clinical application of oral CPMs， the Guidelines systematically construct a technical system in line with the characteristics of traditional Chinese medicine （TCM）， which is essential for improving the clinical safety management of oral CPMs and provides an important reference for medical institutions， pharmaceutical manufacturers， and regulatory authorities.

To standardize the clinical application of oral Chinese patent medicines （CPMs）， and address the safety issues arising from their dosage form characteristics， irrational clinical use， and the lack of targeted pharmacovigilance systems， the China Association of Chinese Medicine organized the formulation and release of Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines， aiming to inform the safe clinical use of oral CPMs and related pharmacovigilance work. According to the principles of GB/T1.1—2020 and the Drug Administration Law of the People's Republic of China （2019 revision）， the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， led a drafting group comprising 18 institutions. After multiple rounds of expert interviews， literature retrieval， evidence screening， and extensive solicitation of opinions， the Guidelines were registered internationally. Systematic standardization focused on safety monitoring， risk identification， assessment， control， and other aspects. The Guidelines clarified the characteristics of oral CPMs in terms of safety monitoring， known risks， and potential risks， compared to non-oral CPMs. Then， risk control measures were proposed， including medication in special populations and irrational medication. As a special guideline for pharmacovigilance in the clinical application of oral CPMs， the Guidelines systematically construct a technical system in line with the characteristics of traditional Chinese medicine （TCM）， which is essential for improving the clinical safety management of oral CPMs and provides an important reference for medical institutions， pharmaceutical manufacturers， and regulatory authorities.

Objective To systematically analyze the characteristics of the disease burden of hypertensive heart disease (HHD) in the elderly (≥60 years) globally and in China from 1990 to 2021, and to predict its future trends from 2022 to 2040, with the aim of providing data support for optimizing comprehensive prevention and control strategies for HHD. Methods Based on the Global Burden of Disease (GBD) 2021 database, the number of prevalent cases and disability-adjusted life years (DALYs) of HHD in the elderly were extracted for the world, China, and five regions categorized by sociodemographic index (SDI). Joinpoint regression was used to analyze the temporal trends of age-standardized prevalence rate and age-standardized DALYs rate of HHD in the elderly. A three-factor decomposition method was applied to evaluate the relative contributions of aging, population growth, and epidemiological changes to the variations in the elderly HHD burden. Additionally, a Bayesian age-period-cohort model was used to predict the elderly HHD burden from 2022 to 2040. Results In 2021, the number of prevalent elderly HHD cases reached 10 283 000 globally and 3 412 400 in China, representing increases of 179.20% and 159.20% respectively, compared with 1990. The DALYs of elderly HHD were 18 812 700 person-years globally and 4 731 400 person-years in China, rising by 76.08% and 29.45% respectively from 1990. Meanwhile, the growth rates of the number of prevalent cases and DALYs of elderly HHD varied across different SDI regions. From 1990 to 2021, the age-standardized prevalence rate of elderly HHD in China, as well as the age-standardized DALYs rate of elderly HHD both globally and in China, showed significant downward trends (all average annual percentage changes<0, all P<0.001). In 2021, the 70-74 years age group accounted for the highest proportion of prevalent cases and DALYs of elderly HHD, both globally and in China. Decomposition analysis revealed that population growth was the dominant factor driving the increase in the elderly HHD burden across all regions. The prediction model results indicated that the number of prevalent cases and DALYs of elderly HHD would continue to rise globally and in China from 2022 to 2040, with the growth rate of the elderly HHD burden in China between 2021 and 2040 expected to exceed the global average. Conclusion Over the past 32 years, although the age-standardized disease rates of elderly HHD have mainly shown a downward trend globally and in China, the absolute number of the disease burden has increased substantially. The projection model indicates a continued upward trajectory, with the growth rate in China higher than the global average. Therefore, there is an urgent need to implement precise prevention and control strategies to effectively mitigate the disease burden of elderly HHD.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective To investigate the safety, economic benefits and psychological effects of day breast conserving surgery for breast cancer. Methods The demographic data and clinical data of breast cancer patients undergoing day (day surgery group) and ward (ward surgery group) breast conserving surgeries in West China Hospital of Sichuan University from March 2020 to June 2021 were retrospectively collected; the demographic data, clinical data, medical and related transportation costs, and preoperative and postoperative BREAST-Q scores of breast cancer patients undergoing day (day surgery group) and ward (ward surgery group) breast conserving surgery in West China Hospital of Sichuan University from June 2021 to June 2022 were prospectively collected. The safety, economic benefit, and psychological satisfaction of day surgery was analyzed. Results A total of 42 women with breast cancer were included in the retrospective study and 39 women with breast cancer were included in the prospective study. In both prospective and retrospective studies, the mean age of patients in both groups were <50 years. There were only statistical differences between the two groups in the aspects of hypertension (P=0.022), neoadjuvant chemotherapy (P=0.037) and postoperative pathological estrogen receptor (P=0.033) in the prospective study. In postoperative complications, there were no statistical differences in the surgical-related complications or anesthesia-related complications between the two groups in either the prospective study or the retrospective study (P>0.05). In terms of the overall cost, we found that the day surgery group was more economical than the ward surgery group in the prospective study (P=0.002). There were no statistical differences in postoperative psychosocical well-being, sexual well-being, satisfaction with breasts or chest condition between the two groups (P>0.05). Conclusion It is safe and reliable to carry out breast conserving surgery in day surgery center under strict management standards, which can save medical costs and will not cause great psychological burden to patients.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.