ObjectiveTo construct a family-centered care model for children with tuberculosis based on the double ABC-X model, and to evaluate its clinical effects. MethodsFrom December 2022 to October 2023, 64 newly admitted children with tuberculosis who met the criteria and their caregivers were recruited from the tuberculosis department of Shanghai Public Health Clinical Center were randomly divided into an experimental group (32 cases) and a control group (32 cases).The control group was given a conventional health care, while the experimental group was given a family-centered health care intervention based on the double ABC-X model, in which a multidisciplinary care team provided personalized information and emotional support for the caregivers and their children. Medication adherence of the children, caregiver’s teading burden, and disease management competence were compared between the 2 groups. ResultsA total of 29 cases in the experimental group and 27 cases in the control group completed the intervention. At 12 weeks of intervention, the medication adherence score (7.72±0.45 vs 7.41±0.50, P<0.05) and disease management competence score (36.97±7.85 vs 31.56±7.30, P<0.05) were higher in the experimental group than that in the control group while the caregiving burden score (31.79±13.40 vs 40.04±9.01, P<0.05) and difficulty of disease management score (30.41±12.41 vs 38.56±9.48, P<0.05) were lower than that in the control group. At 24 weeks of intervention, the medication adherence score (7.34±0.97 vs 6.70±1.14, P<0.05) and disease management competence score (42.07±6.93 vs 35.63±7.32, P<0.05) were higher in the experimental group than that in the control group as well, but the caregiving burden score (31.62±11.72 vs 39.63±10.17, P<0.05) and difficulty of disease management score (30.59±10.87 vs 37.81±9.32, P<0.05) were lower than that in the control group. ConclusionFamily-centered care based on the double ABC-X model can effectively promote medication adherence among children with tuberculosis, reduce caregivers’ care burden and disease management difficulties, and improve caregiver’s disease management competence.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Miniscrews are commonly utilized as temporary anchorage devices (TADs) in cases of maxillary protrusion and premolar extraction. This study aimed to investigate the effects and potential side effects of two conventional miniscrew configurations on the maxillary incisors. Methods: Eighty-two adult patients with maxillary dentoalveolar protrusion who had undergone bilateral first premolar extraction were retrospectively divided into three groups: non-TAD, two posterior miniscrews only (P-TADs), and two anterior and two posterior miniscrews combined (AP-TADs). Cone-beam computed tomography was used to evaluate the maxillary central incisors (U1). Results: The APTADs group had significantly greater U1 intrusion (1.99 ± 2.37 mm, n = 50) and less retroclination (1.70° ± 8.80°) compared to the P-TADs (–0.07 ± 1.65 mm and 9.45° ± 10.68°, n = 60) and non-TAD group (0.30 ± 1.61 mm and 1.91° ± 9.39°, n = 54).However, the AP-TADs group suffered from significantly greater apical root resorption (ARR) of U1 (2.69 ± 1.38 mm) than the P-TADs (1.63 ± 1.46 mm) and non-TAD group (0.89 ± 0.97 mm). Notably, the incidence of grade IV ARR was 16.6% in the AP-TADs group, significantly higher than the rates observed in the P-TADs (6.7%) and non-TAD (1.9%) groups. Multiple regression analysis revealed that after excluding tooth movement factors, the AP-TADs configuration resulted in an additional 0.5 mm of ARR compared with the P-TADs group. Conclusions In cases of maxillary protrusion and premolar extraction, the use of combined anterior and posterior miniscrews enhances incisor intrusion and minimizes torque loss of the maxillary incisors. However, this approach results in more severe ARR, likely due to the increased apical movement and composite force exerted.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Miniscrews are commonly utilized as temporary anchorage devices (TADs) in cases of maxillary protrusion and premolar extraction. This study aimed to investigate the effects and potential side effects of two conventional miniscrew configurations on the maxillary incisors. Methods: Eighty-two adult patients with maxillary dentoalveolar protrusion who had undergone bilateral first premolar extraction were retrospectively divided into three groups: non-TAD, two posterior miniscrews only (P-TADs), and two anterior and two posterior miniscrews combined (AP-TADs). Cone-beam computed tomography was used to evaluate the maxillary central incisors (U1). Results: The APTADs group had significantly greater U1 intrusion (1.99 ± 2.37 mm, n = 50) and less retroclination (1.70° ± 8.80°) compared to the P-TADs (–0.07 ± 1.65 mm and 9.45° ± 10.68°, n = 60) and non-TAD group (0.30 ± 1.61 mm and 1.91° ± 9.39°, n = 54).However, the AP-TADs group suffered from significantly greater apical root resorption (ARR) of U1 (2.69 ± 1.38 mm) than the P-TADs (1.63 ± 1.46 mm) and non-TAD group (0.89 ± 0.97 mm). Notably, the incidence of grade IV ARR was 16.6% in the AP-TADs group, significantly higher than the rates observed in the P-TADs (6.7%) and non-TAD (1.9%) groups. Multiple regression analysis revealed that after excluding tooth movement factors, the AP-TADs configuration resulted in an additional 0.5 mm of ARR compared with the P-TADs group. Conclusions In cases of maxillary protrusion and premolar extraction, the use of combined anterior and posterior miniscrews enhances incisor intrusion and minimizes torque loss of the maxillary incisors. However, this approach results in more severe ARR, likely due to the increased apical movement and composite force exerted.

Objective: To investigate the regional differences in the incidence of urothelial carcinoma among kidney transplant recipients between northern and southern China，so as to provide reference for early diagnosis of this disease. Methods: A comprehensive search was conducted across multiple databases，including CNKI，Wanfang，CBM，and PubMed，using the keywords “kidney transplantation” and “tumor” to collect clinical data from qualified kidney transplant centers.The latest and most complete literature data published by 17 transplant centers in northern China and 14 in southern China were included.Statistical analyses were performed to compare the incidence of post-transplant urothelial carcinoma and non-urothelial malignancies. Results: A total of 37 475 kidney transplant recipients were included，among whom 837 (2.23%) developed post-transplant malignancies，including urothelial carcinoma (366/837，43.73%)，non-urothelial carcinoma (444/837，53.05%)，and malignancies with unspecified pathology (27/837，3.23%).The incidence of malignancies was significantly higher in northern China than in southern China [(2.82±1.39)% vs. (1.67±0.83)%，P=0.011]，with a particularly pronounced difference in the incidence of urothelial carcinoma [(1.68±1.12)% vs. (0.32±0.32)%，P<0.001].No significant difference was observed in the incidence of non-urothelial carcinoma between the two regions [(1.11±0.56)% vs. (1.35±0.65)%，P=0.279].Additionally，female transplant recipients exhibited a higher incidence of malignancies than males in both regions (southern China：2.38% vs. 1.80%; northern China：8.93% vs. 2.52%). Conclusion: The incidence of urothelial carcinoma following kidney transplantation is significantly higher in northern China than in southern China，underscoring the importance of implementing regular tumor screening for kidney transplant recipients，particularly for female patients in northern China，to facilitate early diagnosis and timely intervention.

Objective: Miniscrews are commonly utilized as temporary anchorage devices (TADs) in cases of maxillary protrusion and premolar extraction. This study aimed to investigate the effects and potential side effects of two conventional miniscrew configurations on the maxillary incisors. Methods: Eighty-two adult patients with maxillary dentoalveolar protrusion who had undergone bilateral first premolar extraction were retrospectively divided into three groups: non-TAD, two posterior miniscrews only (P-TADs), and two anterior and two posterior miniscrews combined (AP-TADs). Cone-beam computed tomography was used to evaluate the maxillary central incisors (U1). Results: The APTADs group had significantly greater U1 intrusion (1.99 ± 2.37 mm, n = 50) and less retroclination (1.70° ± 8.80°) compared to the P-TADs (–0.07 ± 1.65 mm and 9.45° ± 10.68°, n = 60) and non-TAD group (0.30 ± 1.61 mm and 1.91° ± 9.39°, n = 54).However, the AP-TADs group suffered from significantly greater apical root resorption (ARR) of U1 (2.69 ± 1.38 mm) than the P-TADs (1.63 ± 1.46 mm) and non-TAD group (0.89 ± 0.97 mm). Notably, the incidence of grade IV ARR was 16.6% in the AP-TADs group, significantly higher than the rates observed in the P-TADs (6.7%) and non-TAD (1.9%) groups. Multiple regression analysis revealed that after excluding tooth movement factors, the AP-TADs configuration resulted in an additional 0.5 mm of ARR compared with the P-TADs group. Conclusions In cases of maxillary protrusion and premolar extraction, the use of combined anterior and posterior miniscrews enhances incisor intrusion and minimizes torque loss of the maxillary incisors. However, this approach results in more severe ARR, likely due to the increased apical movement and composite force exerted.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Miniscrews are commonly utilized as temporary anchorage devices (TADs) in cases of maxillary protrusion and premolar extraction. This study aimed to investigate the effects and potential side effects of two conventional miniscrew configurations on the maxillary incisors. Methods: Eighty-two adult patients with maxillary dentoalveolar protrusion who had undergone bilateral first premolar extraction were retrospectively divided into three groups: non-TAD, two posterior miniscrews only (P-TADs), and two anterior and two posterior miniscrews combined (AP-TADs). Cone-beam computed tomography was used to evaluate the maxillary central incisors (U1). Results: The APTADs group had significantly greater U1 intrusion (1.99 ± 2.37 mm, n = 50) and less retroclination (1.70° ± 8.80°) compared to the P-TADs (–0.07 ± 1.65 mm and 9.45° ± 10.68°, n = 60) and non-TAD group (0.30 ± 1.61 mm and 1.91° ± 9.39°, n = 54).However, the AP-TADs group suffered from significantly greater apical root resorption (ARR) of U1 (2.69 ± 1.38 mm) than the P-TADs (1.63 ± 1.46 mm) and non-TAD group (0.89 ± 0.97 mm). Notably, the incidence of grade IV ARR was 16.6% in the AP-TADs group, significantly higher than the rates observed in the P-TADs (6.7%) and non-TAD (1.9%) groups. Multiple regression analysis revealed that after excluding tooth movement factors, the AP-TADs configuration resulted in an additional 0.5 mm of ARR compared with the P-TADs group. Conclusions In cases of maxillary protrusion and premolar extraction, the use of combined anterior and posterior miniscrews enhances incisor intrusion and minimizes torque loss of the maxillary incisors. However, this approach results in more severe ARR, likely due to the increased apical movement and composite force exerted.