ObjectiveTo explore the correlation between general anesthesia and mild cognitive impairment in older adults so as to provide new ideas for early prevention and timely intervention of mild cognitive impairment（MCI）. MethodsBased on the baseline survey of the Hubei memory and aging cohort study（2018-2023）， the participants completed a thorough neuropsychological assessment and physical examination， and self-reported a history of general anesthesia and surgery. The association of general anesthesia and MCI in the elderly was analyzed using the logistic regression model. In addition， the stratification and interaction analysis of anesthesia history， anesthesia number and physical intellectual exercise were conducted separately. ResultsA total of 5 069 older adults aged 65 and above were included in this study， including 3 692 city dwellers and 1 377 rural people， among whom were 2 584 women （51%）. Out of the 1 472 participants with history of general anesthesia， 249 people （17.4%） had MCI. After controlling for confounding factors， there was a 39.6% increased risk of MCI in older adults who underwent general anesthesia ［OR=1.396，95%CI（1.169，1.668），P<0.001］， suggesting that general anesthesia may be an independent influence on MCI. For the older adults who had one general anesthesia ［OR=1.235，95%CI（1.001，1.523），P=0.049］， two general anesthesia ［OR=1.779，95%CI （1.292，2.450），P<0.001］， and three OR more general anesthesia ［OR=2.395，95%CI （1.589，3.610），P<0.001］， their risks of MCI were increased by 23.5%， 77.9%， and 139.5%， respectively. Compared with the older adults without a history of general anesthesia who did not exercise， the risk of developing MCI was significantly negatively correlated with the exercise group， cognitive exercise group， and combined exercise and cognitive exercise groups （all P<0.001）. The risk of developing MCI in the exercise group was 60.2% of that in the no exercise group ［OR = 0.602， 95% CI（0.456， 0.795）］， the risk in the cognitive exercise group was 42.4% of that in the no exercise group ［OR = 0.424， 95% CI（0.294， 0.613）］， and the risk in the combined exercise and cognitive exercise group was 27.0% of that in the no exercise group ［OR = 0.270， 95% CI （0.208， 0.353）］. In the older adults with a history of general anesthesia， compared with the no exercise group， the risk of developing MCI was significantly negatively correlated with the cognitive exercise group and the combined exercise and cognitive exercise group （all P < 0.05）. The risk of developing MCI in the cognitive exercise group was 47.7% of that in the no exercise group ［OR=0.477， 95% CI （0.256，0.892）］， the risk in the combined exercise and cognitive exercise group was 34.5% of that in the no exercise group ［OR=0.345， 95% CI （0.220， 0.540）］， while the risk in the exercise-only group did not show a significant difference. ConclusionThe risk of MCI increased significantly in older adults with a history of general anesthesia， and this risk increased with the times of anesthesia. Physical and mental exercise reduces the risk of MCI. it is recommended that older adults with a history of anesthesia incorporate physical and mental exercise into their daily lives to prevent mild cognitive impairment.

The success of implementation research is closely tied to the institution's pre-implementation readiness. This study aims to explore the organizational readiness for change (ORC) and its influencing factors on primary healthcare settings in the implementation of the "Shared Medical Appointment for Diabetes (SMART) in China: design of an optimization trial" and to enhance ORC and provide insights to support the effective implementation of the program.

This study aimed to localize the workplace readiness questionnaire (WRQ) and validate its applicability for assessing readiness for implementation of evidence-based practices (EBP) in primary care settings in China. The localization of the instrument will provide a practical instrument for assessing organizational readiness for change (ORC).

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective It evaluates the high-quality development policies of public hospitals at the provincial level in China,and provides theoretical basis and countermeasures for formulating and optimizing the high-quality develop-ment policies of public hospitals.Methods The ROST CM 6.0 software was used to conduct text mining for 11 sample policies,and the Policy Modeling Consistency(PMC)index model was constructed to evaluate the sample policies quantitatively.Results The average PMC index of 11 sample policies included in the study was 7.16 points,of which 8 were excellent grades and 3 were qualified grades.The first-level variables X5 service system(0.82),X8 Party leadership(0.91)and X6 organization and operation(0.94)scored higher;X2 policy timeliness(0.52),X7 cultural construction(0.68)and X4 service capability(0.71)scored low.Conclusion The content of the high-quality develop-ment policy of public hospitals at the provincial level is basically in line with the national policy,and is relatively excel-lent in the aspects of organization and operation,service system and party leadership,etc.,but there are some weaknesses in the aspects of policy timeliness,cultural construction and service capacity,etc.,which can be op-timized and improved from the aspects of improving service capacity,supplementing long-term policies and strengthening hospital cultural construction.

Objective To explore the high-quality development path of tertiary public hospitals and provide scientific reference for deepening the reform of public hospitals.Methods Based on SPO theory,it constructed an analytical framework for the high-quality development of tertiary public hospitals,collected data of a quarterly monitoring in-dex for the performance assessment and high-quality development of tertiary public hospitals in a certain province in 2023,and analysed 73 tertiary public hospitals participating in the performance assessment as the object of analy-sis,and adopted the fuzzy-set Qualitative Comparative Analysis to explore different condition sets of high-quality de-velopment of tertiary public hospitals and reveal the path of high-quality development of public hospitals.Results High-quality development is the result of multi-factor interaction.Four configurations were identified to promote the high-quality development of tertiary public hospitals:service quality-technology-driven path,service quality-driven path,comprehensive service-driven path,and service quality-benefit-driven path.Quality safety and functional orientation were found to be the core elements in promoting high-quality development of public hospitals.Conclusion Hospitals at all levels should strengthen the guidance of party building,combine with the actual functional positioning,take quality and safety as the core,and optimize the combination conditions of technical level,personnel structure,service process,and cost control.It is essential to clarify the development strategy of hospitals,implement the dynamic concept,and realize the high-quality development of public hospitals.