ObjectiveTo explore the academic characteristics of contemporary renowned Chinese medicine masters in treating diabetic kidney disease （DKD） from the perspectives of principles， methods， formulas， and medications. MethodsIn strict accordance with the Systematic Review of Text and Opinion （SrTO） process developed by the Joanna Briggs Institute （JBI）， an Australian evidence-based healthcare center， the databases including China National Knowledge Infrastructure （CNKI）， VIP Database， Wanfang Data， and China Biomedical Literature Service System （SinoMed） were searched. Based on predefined inclusion and exclusion criteria， text information extraction， quality evaluation， and text information synthesis were conducted sequentially. The data were analyzed and presented in the form of text and figures. ResultsA total of 215 articles related to 43 contemporary renowned experts in the fields of Chinese medicine nephrology and endocrinology were included. The study found that the academic thoughts of these masters in the treatment of DKD are extensive， involving multiple levels such as disease understanding， therapeutic strategies， formula application， and medication use. In terms of disease understanding， the primary pathogenesis is characterized by deficiency in the root and excess in the manifestation. It is emphasized that internal factors， such as congenital endowment deficiency， interact with external factors such as improper diet， emotional disturbances， invasion of exogenous pathogens， and delayed or inappropriate treatment， to jointly induce the disease. This further gives rise to various pathogenetic theories， including obstruction of renal collaterals by blood stasis， toxin-induced damage to renal collaterals， latent wind disturbing the kidney， and internal heat leading to mass formation. In terms of therapeutic strategies and medication use， the principal treatment method is to replenish Qi and nourish Yin. Stage-based and syndrome-differentiated treatments are advocated. Flexible use of insect-derived drugs and wind-dispelling drugs is emphasized， along with proficiency in applying classical formulas and drug pairs. Integrated internal and external treatments， as well as the combined application of multiple therapeutic approaches， are commonly employed for comprehensive management. Meanwhile， the concept of "preventive treatment of disease" is upheld， and individualized long-term management of patients is advocated. ConclusionThrough the SrTO process， the academic thoughts of contemporary renowned Chinese medicine masters in the treatment of DKD have been systematically and standardly synthesized， providing a scientific and standardized basis for future theoretical exploration.

ObjectiveTo explore the academic characteristics of contemporary renowned Chinese medicine masters in treating diabetic kidney disease （DKD） from the perspectives of principles， methods， formulas， and medications. MethodsIn strict accordance with the Systematic Review of Text and Opinion （SrTO） process developed by the Joanna Briggs Institute （JBI）， an Australian evidence-based healthcare center， the databases including China National Knowledge Infrastructure （CNKI）， VIP Database， Wanfang Data， and China Biomedical Literature Service System （SinoMed） were searched. Based on predefined inclusion and exclusion criteria， text information extraction， quality evaluation， and text information synthesis were conducted sequentially. The data were analyzed and presented in the form of text and figures. ResultsA total of 215 articles related to 43 contemporary renowned experts in the fields of Chinese medicine nephrology and endocrinology were included. The study found that the academic thoughts of these masters in the treatment of DKD are extensive， involving multiple levels such as disease understanding， therapeutic strategies， formula application， and medication use. In terms of disease understanding， the primary pathogenesis is characterized by deficiency in the root and excess in the manifestation. It is emphasized that internal factors， such as congenital endowment deficiency， interact with external factors such as improper diet， emotional disturbances， invasion of exogenous pathogens， and delayed or inappropriate treatment， to jointly induce the disease. This further gives rise to various pathogenetic theories， including obstruction of renal collaterals by blood stasis， toxin-induced damage to renal collaterals， latent wind disturbing the kidney， and internal heat leading to mass formation. In terms of therapeutic strategies and medication use， the principal treatment method is to replenish Qi and nourish Yin. Stage-based and syndrome-differentiated treatments are advocated. Flexible use of insect-derived drugs and wind-dispelling drugs is emphasized， along with proficiency in applying classical formulas and drug pairs. Integrated internal and external treatments， as well as the combined application of multiple therapeutic approaches， are commonly employed for comprehensive management. Meanwhile， the concept of "preventive treatment of disease" is upheld， and individualized long-term management of patients is advocated. ConclusionThrough the SrTO process， the academic thoughts of contemporary renowned Chinese medicine masters in the treatment of DKD have been systematically and standardly synthesized， providing a scientific and standardized basis for future theoretical exploration.

Objective:To construct a A medical equipment procurement decision-making model based on multi-source heterogeneous data fusion for procuring medical equipment,so as is constructed based on the fusion of multi-source heterogeneous data to enhance the efficiency of procuring equipment procurement.Methods:The multi-source heterogeneous data included technical performance,market supply and social benefits were integrated,and the XGBoost algorithm was adopted to predict the priority of equipment's cost performance,so as to construct a decision-making model of procuring medical equipment.A total of 344 medical equipment that were procured by Shanghai Chest Hospital from January 2021 to December 2024 were selected.In them,163 medical equipment that were procured during January 2021 and December 2022 were managed by using the decision-making method with subjective review,and 181 medical equipment that were procured during January 2023 to December 2024 were managed by using the management method with decision-making model.The differences of execution rate of procuring equipment,operation quality and cost control for equipment of two kinds of management methods of procurement decision-making were compared.Results:The average values of the average completion rate of procurement,shortening rate of cycle,timeliness rate of delivery and standardization rate of data of the equipment that were managed by using the management method with decision-making model were respectively(96.82±1.66)%,(24.98±8.14)%,(91.77±3.26)%and(96.66±1.81)%,all of which were higher than those of the decision-making management method with subjective review,and the differences were all statistically significant(Z=3.494,3.208,3.648,2.087,P<0.05).The average failure rate of equipment was lower than that of the decision-making management method with subjective review,and the average values of the average utilization rate,completion rate of maintenance and rate of meeting standard of risk control were all higher than those of the decision-making management method with subjective review,and the differences were statistically significant(Z=3.753,2.920,2.815,3.464,P<0.05).The average saving rates of procurement cost,reduction rates of maintenance cost,and saving rates of consumable cost of equipment were all higher than those of the decision-making management method with subjective review,and the differences were statistically significant(Z=3.408,3.464,3.926,P<0.05).Conclusion:The application of the decision-making model based on multi-source heterogeneous data fusion in procuring medical equipment can enhance the execution rate of procuring medical equipment of hospitals,and improve the operational quality of equipment,and reduce equipment's procurement costs,and promote the efficient allocation and sustainable development of medical resources of hospitals.

Objective:To construct a A medical equipment procurement decision-making model based on multi-source heterogeneous data fusion for procuring medical equipment,so as is constructed based on the fusion of multi-source heterogeneous data to enhance the efficiency of procuring equipment procurement.Methods:The multi-source heterogeneous data included technical performance,market supply and social benefits were integrated,and the XGBoost algorithm was adopted to predict the priority of equipment's cost performance,so as to construct a decision-making model of procuring medical equipment.A total of 344 medical equipment that were procured by Shanghai Chest Hospital from January 2021 to December 2024 were selected.In them,163 medical equipment that were procured during January 2021 and December 2022 were managed by using the decision-making method with subjective review,and 181 medical equipment that were procured during January 2023 to December 2024 were managed by using the management method with decision-making model.The differences of execution rate of procuring equipment,operation quality and cost control for equipment of two kinds of management methods of procurement decision-making were compared.Results:The average values of the average completion rate of procurement,shortening rate of cycle,timeliness rate of delivery and standardization rate of data of the equipment that were managed by using the management method with decision-making model were respectively(96.82±1.66)%,(24.98±8.14)%,(91.77±3.26)%and(96.66±1.81)%,all of which were higher than those of the decision-making management method with subjective review,and the differences were all statistically significant(Z=3.494,3.208,3.648,2.087,P<0.05).The average failure rate of equipment was lower than that of the decision-making management method with subjective review,and the average values of the average utilization rate,completion rate of maintenance and rate of meeting standard of risk control were all higher than those of the decision-making management method with subjective review,and the differences were statistically significant(Z=3.753,2.920,2.815,3.464,P<0.05).The average saving rates of procurement cost,reduction rates of maintenance cost,and saving rates of consumable cost of equipment were all higher than those of the decision-making management method with subjective review,and the differences were statistically significant(Z=3.408,3.464,3.926,P<0.05).Conclusion:The application of the decision-making model based on multi-source heterogeneous data fusion in procuring medical equipment can enhance the execution rate of procuring medical equipment of hospitals,and improve the operational quality of equipment,and reduce equipment's procurement costs,and promote the efficient allocation and sustainable development of medical resources of hospitals.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Objective:To evaluate the effect of patent foramen ovale (PFO) on the perioperative complications and survival rate in pediatric patients undergoing living donor liver transplantation.Methods:The medical records from pediatric patients of either sex with biliary atresia, aged<18 yr, who underwent living donor liver transplantation from January 2020 to January 2022, were retrospectively collected. The pediatric patients were divided into PFO group and non-PFO group according to the results of echocardiography before operation. The postreperfusion syndrome, acute lung injury, acute kidney injury, postoperative delirium and 1-year survival rate were recorded.Results:There was no significant difference in the incidence of postreperfusion syndrome, acute lung injury, acute kidney injury, postoperative delirium and one-year survival rate between PFO group and non-PFO group ( P>0.05). Conclusions:PFO has no obvious effect on the incidece of intraoperative and early postoperative complications and 1-year survival rate in pediatric patients undergoing living donor liver transplantation.