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:To revise and evaluate the reliability and validity of the Healthcare Provider Perceptions of Team Effectiveness (Provider-PTE) .Methods:The English version of the Provider-PTE was translated literally and back in accordance with the Brislin translation principles. Questionnaire culture debugging and item revision were conducted through Delphi method and pre-survey. In March 2022, a survey was conducted among 641 nurses from two ClassⅢ Grade A hospitals in Qingdao to test the reliability and validity of the questionnaire. A total of 641 questionnaires were distributed, and 605 valid questionnaires were recovered, with an effective recovery rate of 94.4%.Results:The Chinese version of Provider-PTE included five dimensions, including role development, team support, team meetings, team operations, and care outcomes, with a total of 26 items. Through exploratory factor analysis, the cumulative variance contribution rate of the five common factors was 84.783%. The average scale content validity index of the Provider-PTE was 0.928, and the item content validity index was 0.875 to 1.000. The Cronbach's α coefficient of the Chinese version of Provider-PTE was 0.859, and the retest reliability was 0.873.Conclusions:The Chinese version of Provider-PTE has good reliability and validity, and can be used to assess the team effectiveness of nursing staffs.

Objective To develop a pathway management system for nucleus-related special service recuperation to enhance efficiency and extend function in the pathway management.Methods The system was developed on the basis of military sanatorium information management platform,and constructed with modular and object-oriented method,B/S mode,Oracle 8 database and Java programming languages.Results The system solved the problems of paper pathway management in time consumption,supervision,statistics,regulation and etc.Conclusion The system contributes to the standardization,convenience and precision of the pathway management for nucleus-related special service recuperation,and thus is worthy promoting in the nucleus-related military sanatorium.

Objective:To evaluate the protective immunity by vaccination of BALB/c mice with rLV-HA-GCN4,a recombinant lentivirus expressing the trimeric HA of swine H1N1 influenza virus. Methods:The female mice were randomly divided into rLV-HA-GCN4,rLV-HA,LV and PBS groups. Mice were primed with plasmid and boosted with lentivirus by the administration of intramuscular thigh injections at an interval of two weeks. At day 28 post-prime immunization,mice were inoculated intranasally with 100TCID50 of swine H1N1 influenza virus in a 50 μl volume. The immune levels were assessed by the T lymphocyte transformation test, flow cytometry,indirect ELISA and the indexes of spleen and lung. Results:The spleen lymphocyte transformation rate was 0. 3±0. 11 in the rLV-HA-GCN4 group at day 14 post-boost immunization, showing a statistical significance ( P<0. 01 ) compared to the PBS group. Meanwhile,rLV-HA-GCN4 could cause T lymphocyte response mainly based on the Th1-type CD4+ T cells. The IgG antibody titer reached to 1:8 000 at day 14 post-boost immunization and approximately 1:7 000 at day 14 post challenge. After challenge,the spleen and lung indexes of rLV-HA-GCN4 group were significantly lower than those of PBS group (P<0. 05). The body weight of rLV-HA-GCN4 group demonstrated a slight decrease before 3 days post challenge and then a gradual increase compared to the LV and PBS groups (P<0. 05). Conclusion:rLV-HA-GCN4 can effectively induce cellular and humoral immune response in BALB/c mice against swine H1N1 influenza virus.

Objective To evaluate the efficacy of ancient classical prescriptions treating middle and advanced primary liver cancer.Methods Articles were searched from Pubmed, Embase, SCI, Cochrane Liarary and CNKI, VIP, WanFang Data, CBM databases. Randomized controlled trials about ancient classical prescriptions treating advanced primary liver cancer were collected. Results 17 studies were included, a total of 994 patients. The recent efficiency of ancient classical prescription combined with symptomatic therapy increased by 28% compared with single supportive and symptomatic therapy;the stable rate of life quality increased by 23%;the efficiency of TCM syndrome increased by 29%;the survival rates of 3 months, 6 months and 1 year increased by 16%, 36.7% and 58.5% respectively;the life quality score of later increased by 6.29 on average. Conclusion Ancient classical prescription combined with supportive and symptomatic therapy in advanced primary liver cancers is superior to single supportive and symptomatic therapy on recent efficiency, survival rate (3 months/6 months/1 year), quality of life and TCM syndrome. The conclusion of this study needs randomized controlled trials with larger samples, multicenter and high quality for further verification.