Objective To explore the influencing factors of cognitive impairment in non-dialysis patients with chronic kidney disease(CKD).Methods A total of 60 hospitalized non-dialysis patients with CKD in the Department of Nephrology of Northern Jiangsu People's Hospital Affiliated to Yangzhou University from September 2022 to September 2023 were enrolled as research objects.According to the estimated glomerular filtration rate(eGFR),they were divided into stage 1 to 2 of CKD group[eGFR ≥60 mL/(min·1.73 m2)]with 23 cases,the stage 3 of CKD group[eGFR 30～＜60 mL/(min·1.73 m2)]with 20 cases,and stage 4 to 5 of CKD group[eGFR＜30 mL/(min·1.73 m2)]with 17 cases.The Montreal Cognitive Assessment Scale(MoCA)was used to evaluate the cognitive function of the patients.Basic data and common clinical laboratory in-dicators on hospital admission were collected to analyze the differences in cognitive function levels under different renal function statuses and to explore the influencing factors of cognitive impairment.Results The incidence rates of cognitive impairment in the stage 1 to 2 of CKD group,stage 3 of CKD group,and stage 4 to 5 of CKD group were 47.8％,85.0％,and 94.1％respectively,the median MoCA scored 26,24 and 20 respectively,with statistically significant between-group differ-ences(P＜0.05).Cognitive function was significantly negatively correlated with age(r=-0.634,P＜0.001),blood urea nitrogen(BUN)(r=-0.574,P＜0.001),serum creatinine(Cr)(r=-0.417,P＜0.001),cystatin C(Cys-C)(r=-0.327,P=0.011),serum β2-microglobulin(β2-MG)(r=-0.259,P=0.046),and N-terminal pro-brain natriuretic peptide(NT-proBNP)(r=-0.474,P＜0.001),and was significantly positively correlated with hemoglobin(HB)(r=0.401,P=0.001)and eGFR(r=0.485,P＜0.001).Multivariate Logistic regression analysis showed that age(P=0.006)and NT-proBNP(P=0.041)were influencing factors of cognitive im-pairment in non-dialysis patients with CKD.Receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC),sensitivity,and specificity of age for prediction were 0.860,0.864 and 0.812 respectively,the AUC,sensitivity,and specificity of NT-proBNP for pre-diction were 0.808,0.795 and 0.875 respectively,and the combined prediction of age and NT-proBNP had an AUC,sensitivity,and specificity of 0.893,0.955,and 0.750,respectively.Conclusion As renal function deteriorates,the incidence rate and severity of cognitive impairment in non-dialysis patients with CKD tend to increase.Advanced age,renal function deterioration,high NT-proBNP level,and anemia are associated with the occurrence of cognitive impairment in non-di-alysis patients with CKD,among which age and NT-proBNP are influencing factors for cognitive im-pairment.

Objective:To evaluate the accuracy of a self-developed extraoral scanning system based on photogrammetry technology, and to provide evidence for advancing the development and clinical application evaluation of domestically produced scanning devices.Methods:This research group developed a photogrammetry-based implant extraoral scanning system with customized scan bodies. Two distinct edentulous implant resin models were designed and three-dimensional (3D)-printed by Center of Digital Dentistry, Peking University School and Hospital of Stomatology, containing 6 (Model 1) and 8 (Model 2) abutment analogs respectively. Reference data acquisition was performed using a high-precision denture 3D scanner with scan caps mounted on the analogs. Specialized scan bodies were then mounted on the analogs for 3D positional data acquisition using both the self-developed system (experimental group) and the clinically established system (control group). Each system conducted 10 repeated scans per model. Trueness was assessed through root mean square error (RMSE), linear deviation (LD), and angular deviation (AD) relative to reference data, while precision was determined through intra-group RMSE analysis. Systematic comparisons included inter-group performance on identical models and intra-group variability across different models.Results:For Model 1, the experimental group showed statistically significant advantages over controls in intra-group RMSE [(3.10±0.71) μm vs (4.61±1.51) μm, P<0.001], reference-data RMSE [(21.48±0.60) μm vs (32.50±0.63) μm, P<0.001], linear deviation [23.64 (32.35) μm vs 44.86 (55.73) μm, P<0.001], and angular deviation [0.29° (0.29°) vs 0.23° (0.33°), P<0.001]. In Model 2, significant improvements were observed in intra-group RMSE [(4.47±1.58) μm vs (6.21±2.07) μm, P<0.001], reference-data RMSE [(38.84±0.86) μm vs (43.69±1.34) μm, P<0.001], and linear deviation [37.95 (50.68) μm vs 49.71 (58.89) μm, P<0.001]. Both groups exhibited model-dependent variability, with RMSE of precision and trueness of both groups, linear deviation of experimental group, angular deviation of control group showing statistically significant increases (all P<0.001) corresponding to abutment analog quantity. Conclusions:The self-developed scanning system demonstrates superior accuracy in 3D positional acquisition of abutment analogs compared to the contral group system, with implant number identified as a critical determinant of extraoral scanning accuracy.

OBJECTIVES: This study aimed to evaluate the repeatability and reliability of a self-developed domestic wireless surface electromyography (sEMG) system (Oralmetry) in assessing the activity of the temporalis and masseter muscles to provide theoretical support for its clinical application. METHODS: Twenty-two volunteers were recruited. Through multiple repeated measurements, the sEMG signals of bilateral anterior temporalis and masseter muscles during maximum voluntary clenching were collected using the self-developed sEMG device, Oralmetry, and two commercial sEMG devices (Zebris and Teethan), filtered, screened, and standardized. Seven sEMG indicators for assessing masticatory muscle function were calculated. The intraclass correlation coefficient (ICC) was used to evaluate the repeatability of the measurements from the three sEMG devices, and statistical analysis was conducted to compare the consistency of the seven sEMG indicators obtained from the devices. RESULTS: Among the 22 participants, the ICC values of the repeated measurements from the three sEMG devices ranged from 0.88 to 0.99. The measurements of three sEMG indicators (antero-posterior coeffificient, percentage overlapping coeffificient_MM, and percentage overlapping coeffificient_TA) obtained by Zebris were significantly different from those obtained by Oralmetry and Teethan (P<0.05). No significant differences in the measurements of the seven sEMG indicators were found between Oralmetry and Teethan. CONCLUSIONS Oralmetry and the two commercial sEMG devices demonstrated good repeatability in capturing sEMG indicators for evaluating masticatory muscle function. In particular, Oralmetry showed the highest ICC values. All three devices also exhibited good consistency in measuring sEMG indicators, and a high agreement was observed between the two wireless sEMG devices (Oralmetry and Teethan). These findings provide theoretical support for the clinical application of Oralmetry.
Humans ; Electromyography/methods* ; Masseter Muscle/physiology* ; Masticatory Muscles/physiology* ; Wireless Technology ; Reproducibility of Results ; Temporal Muscle/physiology* ; Male ; Adult ; Female ; Young Adult

Objective:To evaluate the accuracy of a self-developed extraoral scanning system based on photogrammetry technology, and to provide evidence for advancing the development and clinical application evaluation of domestically produced scanning devices.Methods:This research group developed a photogrammetry-based implant extraoral scanning system with customized scan bodies. Two distinct edentulous implant resin models were designed and three-dimensional (3D)-printed by Center of Digital Dentistry, Peking University School and Hospital of Stomatology, containing 6 (Model 1) and 8 (Model 2) abutment analogs respectively. Reference data acquisition was performed using a high-precision denture 3D scanner with scan caps mounted on the analogs. Specialized scan bodies were then mounted on the analogs for 3D positional data acquisition using both the self-developed system (experimental group) and the clinically established system (control group). Each system conducted 10 repeated scans per model. Trueness was assessed through root mean square error (RMSE), linear deviation (LD), and angular deviation (AD) relative to reference data, while precision was determined through intra-group RMSE analysis. Systematic comparisons included inter-group performance on identical models and intra-group variability across different models.Results:For Model 1, the experimental group showed statistically significant advantages over controls in intra-group RMSE [(3.10±0.71) μm vs (4.61±1.51) μm, P<0.001], reference-data RMSE [(21.48±0.60) μm vs (32.50±0.63) μm, P<0.001], linear deviation [23.64 (32.35) μm vs 44.86 (55.73) μm, P<0.001], and angular deviation [0.29° (0.29°) vs 0.23° (0.33°), P<0.001]. In Model 2, significant improvements were observed in intra-group RMSE [(4.47±1.58) μm vs (6.21±2.07) μm, P<0.001], reference-data RMSE [(38.84±0.86) μm vs (43.69±1.34) μm, P<0.001], and linear deviation [37.95 (50.68) μm vs 49.71 (58.89) μm, P<0.001]. Both groups exhibited model-dependent variability, with RMSE of precision and trueness of both groups, linear deviation of experimental group, angular deviation of control group showing statistically significant increases (all P<0.001) corresponding to abutment analog quantity. Conclusions:The self-developed scanning system demonstrates superior accuracy in 3D positional acquisition of abutment analogs compared to the contral group system, with implant number identified as a critical determinant of extraoral scanning accuracy.

Objective:To develop an original-mirror alignment associated deep learning algorithm for intelligent registration of three-dimensional maxillofacial point cloud data,by utilizing a dynamic graph-based registration network model(maxillofacial dynamic graph registration network,MDGR-Net),and to provide a valuable reference for digital design and analysis in clinical dental applications.Methods:Four hundred clinical patients without significant deformities were recruited from Peking University School of Stomatology from October 2018 to October 2022.Through data augmentation,a total of 2 000 three-dimensional maxillofacial datasets were generated for training and testing the MDGR-Net algorithm.These were divided into a training set(1 400 cases),a validation set(200 cases),and an internal test set(200 cases).The MDGR-Net model constructed feature vectors for key points in both original and mirror point clouds(X,Y),established correspondences between key points in the X and Y point clouds based on these feature vectors,and calculated rotation and translation matrices using singular value decomposi-tion(SVD).Utilizing the MDGR-Net model,intelligent registration of the original and mirror point clouds were achieved,resulting in a combined point cloud.The principal component analysis(PCA)algorithm was applied to this combined point cloud to obtain the symmetry reference plane associated with the MDGR-Net methodology.Model evaluation for the translation and rotation matrices on the test set was performed using the coefficient of determination(R2).Angle error evaluations for the three-dimensional maxillofacial symmetry reference planes were constructed using the MDGR-Net-associated method and the"ground truth"iterative closest point(ICP)-associated method were conducted on 200 cases in the inter-nal test set and 40 cases in an external test set.Results:Based on testing with the three-dimensional maxillofacial data from the 200-case internal test set,the MDGR-Net model achieved an R2 value of 0.91 for the rotation matrix and 0.98 for the translation matrix.The average angle error on the internal and external test sets were 0.84°±0.55° and 0.58°±0.43°,respectively.The construction of the three-dimensional maxillofacial symmetry reference plane for 40 clinical cases took only 3 seconds,with the model performing optimally in the patients with skeletal Class Ⅲ malocclusion,high angle cases,and Angle Class Ⅲ orthodontic patients.Conclusion:This study proposed the MDGR-Net association method based on intelligent point cloud registration as a novel solution for constructing three-dimensional maxillo-facial symmetry reference planes in clinical dental applications,which can significantly enhance diagnos-tic and therapeutic efficiency and outcomes,while reduce expert dependence.

Objective:To explore the method of obtaining the key parameters of the average value articulator in healthy people based on mandibular movement trajectory data, with a view to providing a reference for the clinical application of the average value articulator.Methods:One hundred healthy volunteers (42 males and 58 females) with individual normal occlusion, aged 18-55 years old, who met the inclusion criteria were recruited from Beijing, and their mandibular movement trajectory data were collected. The left and right sagittal condylar inclination(SCI) and transversal condylar inclination(TCI) were obtained from the values of the articulator parameters which were generated in the mandibular movement analysis system.The SCI and TCI were grouped by gender and calculated separately for the two groups and the overall sample; the gender differences in the two parameters and the differences between the mean values of the two parameters and the average value articulator empirical values (35° for SCI and 15° for TCI) for the overall sample were compared.Results:The differences between SCI (35.8°±7.4°) and TCI [11.2° (11.3°)] in males and the corresponding parameters [35.6°±8.3° and 10.8° (9.5°), respectively] in females were not statistically significant ( t=0.10, P=0.922; Z=-0.60, P=0.552); the overall sample SCI (35.7°±7.9°) did not differ statistically from the average value articulator empirical value ( t=1.23, P=0.221), and the overall sample TCI [10.9° (10.3°)] was significantly smaller than the average value articulator empirical value ( W=5 825.00, P<0.001). Conclusions:The mandibular movement trajectory data of 100 adults with individual normal occlusion in this study shows that the gender factor does not affect the setting of the key parameters of the average value articulator, the SCI of the average value articulator empirical values is appropriate, and the TCI has the possibility of being on the large side. In the clinical use of the articulator to assist in the design of restorations, the parameter values should be rationally adjusted according to the actual situation of the patient′s dentition and mandibular movement.

Objective:To explore the impact of digital technology in constructing a three-dimensional (3D) symmetry reference plane (SRP) for esthetic restoration of anterior teeth and to evaluate its clinical applicability.Methods:A cross-sectional study was conducted from February to May 2024, involving 20 patients [11 males and 9 females, aged (36.8±11.4) years] who underwent anterior esthetic restorations at the Department of Stomatology, People′s Hospital of Ningxia Hui Autonomous Region. Symmetrical reference planes of patients′ 3D facial models were constructed using three different algorithms: weighted Procrustes analysis (WPA), Procrustes analysis (PA) based on the ontology-mirror correlation method, and iterative closest point (ICP). The SRP defined by an associate chief physician served as the control (true-value group). The angular errors between each algorithm group and the true-value group were compared. The optimal algorithm was selected and combined with a three-dimensional digital smile design (DSD) to create virtual patients, followed by designing anterior restorations. The visual analogue scale (VAS) was used by patients to score the aesthetic restoration results of the conventional design (control group) and the algorithm-based design (algorithm group).Results:The angular errors of the WPA, PA, and ICP groups were 1.43°±0.66°, 1.82°±0.88°, and 4.74°±2.03° respectively, with statistically significant differences among the groups ( F=41.10, P<0.001). Pairwise comparisons showed that the WPA group had significantly smaller angular errors compared to the PA and ICP groups ( P<0.05). The VAS scores for aesthetic restoration were significantly higher in the algorithm group (8.09±0.74) compared to the control group (6.30±1.38) ( t=-5.49, P<0.001). Conclusions:The SRP constructed using the WPA algorithm demonstrated minimal angular error when compared to the expert-defined SRP and is considered the optimal choice in clinical practice, yielding high patient satisfaction.

Objective This study proposes a chairside digital design and manufacturing method for band and loop space maintainers and preliminarily validates its clinical feasibility.Methods Clinical cases of 10 children requiring space maintenance caused by premature loss of primary teeth were collected.Intraoral scan data of the affected children were also collected to establish digital models of the missing teeth.Using a pediatric band and loop space maintainer de-sign software developed by our research team,a rapid personalized design of band and loop structures was achieved,and a digital model of an integrated band and loop space maintainer was ultimately generated.A chairside space maintainer was manufactured through metal computer numerical control machining for the experimental group,whereas metal 3D printing in the dental laboratory was used for the control group.A model fitting assessment was conducted for the space maintainers of both groups,and senior pediatric dental experts were invited to evaluate the clinical feasibility of the space maintainers with regard to fit and stability using the visual analogue scale scoring system.Statistical analysis was also performed.Results The time spent in designing and manufacturing the 10 space maintainers of the experimental group was all less than 1 h.Statistical analysis of expert ratings showed that the experimental group outperformed the control group with regard to fit and stability.Both types of space maintainers met clinical requirements.Conclusion The chairside digital design and manufacturing method for pediatric band and loop space maintainers proposed in this study can achieve same-day fitting of space maintainers at the first appointment,demonstrating good clinical feasibility and significant potential for clinical application.

Objective:To establish an intelligent registration algorithm under the framework of original-mirror alignment algorithm to construct three-dimensional (3D) facial midsagittal plane automatically. Dynamic Graph Registration Network (DGRNet) was established to realize the intelligent registration, in order to provide a reference for clinical digital design and analysis.Methods:Two hundred clinical patients without significant facial deformities were collected from October 2020 to October 2022 at Peking University School and Hospital of Stomatology. The DGRNet consists of constructing the feature vectors of key points in point original and mirror point clouds (X, Y), obtaining the correspondence of key points, and calculating the rotation and translation by singular value decomposition. Original and mirror point clouds were registrated and united. The principal component analysis (PCA) algorithm was used to obtain the DGRNet alignment midsagittal plane. The model was evaluated based on the coefficient of determination (R 2) index for the translation and rotation matrix of test set. The angle error was evaluated on the 3D facial midsagittal plane constructed by the DGRNet alignment midsagittal plane and the iterative closet point (ICP) alignment midsagittal plane for 50 cases of clinical facial data. Results:The average angle error of the DGRNet alignment midsagittal plane and ICP alignment midsagittal plane was 1.05°±0.56°, and the minimum angle error was only 0.13°. The successful detection rate was 78% (39/50) within 1.50° and 90% (45/50) within 2.00°.Conclusions:This study proposes a new solution for the construction of 3D facial midsagittal plane based on the DGRNet alignment method with intelligent registration, which can improve the efficiency and effectiveness of treatment to some extent.

With the wide application of digital technology in the field of stomatology, the acquisition of three-dimensional tooth and dentition information through three-dimensional (3D) image data and optical scan data has become an indispensable process in clinical diagnosis and analysis. Cone-beam CT images and optical scanning images have their own characteristics in terms of data acquisition range and the accuracy of data. Single data source is not accurate enough or complete in the delivery of tooth and dental information. At present, two data sources are used to construct a 3D crown root model with high-precision crown and complete root information to meet the requirement of clinical orthodontic functional setup and implant surgical guide design. The integration of tooth crown and root is one of the focused topics of clinical research. This review will summarize the research progress of 3D crown root model construction method, introduce the application of various algorithms, and analyze the characteristics of these approaches, in order to provide reference for clinical application and scientific research.