ObjectiveTo compare the clinical efficacy of traditional Chinese medicine （TCM） manipulative reduction combined with small splint fixation versus surgical treatment for type A distal radius fracture （DRF） and to explore the factors influencing the choice of treatment. MethodsA multi-center retrospective study was conducted， collecting data from 1237 type A DRF patients treated in 11 hospitals in Jiangsu province from September， 2023 to April， 2025. Among them， 851 patients in the TCM group received manipulative reduction combined with small splint fixation， and 386 patients in the surgical group underwent open reduction and internal fixation. Visual analog scale （VAS） scores for pain and radiographic indicators including palmar tilt， ulnar deviation， and radial height were compared before treatment， 5-7 days after treatment， and 4-6 weeks after treatment. The wrist joint function scores including Dienst and Gartland-Werley scores at 12 weeks after treatment were recorded. Subgroup analysis was conducted for the excellent rate of Dienst and Gartland-Werley scores， stratified by age （＜50， 50-59， 60-69， ≥70 years old） and AO subtypes （A1， A2， A3）. A multivariate logistic regression model was used to identify independent factors influencing treatment choice. ResultsOn 5-7 days after treatment， the surgical group had lower VAS scores than the TCM group， while 4-6 weeks after treatment， the TCM group showed lower VAS scores than the surgical group （P＜0.01）. In terms of radiographic indicators， except for the palmar tilt before treatment being higher in the surgical group than in the TCM group （P＜0.01）， there were no significant differences in palmar tilt， ulnar deviation， and radial height at other timepoints （P＞0.05）. Twelve weeks after treatment， the surgical group had a higher average Gartland-Werley score and the excellent rate than the TCM group （P＜0.01）. Subgroup analysis showed that in patients with A2 type DRF aged 50-59 and 60-69 years old， the excellent rates of Dienst and Gartland-Werley scores in the TCM group were higher than those in the surgical group （P＜0.05）. Multivariate logistic regression analysis revealed that age， palmar tilt， ulnar deviation， and the degree of swelling on the affected side were independent factors influencing the choice of treatment （P＜0.05）. ConclusionBoth TCM manipulative reduction combined with small splint fixation and surgical treatment for type A DRF can achieve good therapeutic effects. TCM manipulative reduction combined with small splint fixation has certain advantages in medium- and long-term pain relief， especially in elderly patients， where wrist joint function recovery is more stable. Age， palmar tilt， ulnar deviation， and swelling degree are the main factors influencing the treatment choice.

ObjectiveTo observe the clinical efficacy and radiographic outcomes of manipulative reduction combined with small splint fixation in the treatment of distal radius fractures. MethodsThe clinical data of 1051 patients with distal radius fractures were retrospectively collected from five hospitals included in the Jiangsu Diagnosis and Treatment Data Platform for Traditional Chinese Medicine（TCM） Dominant Diseases. Propensity score matching at a 1∶4 ratio was applied， resulting in 580 cases selected for final analysis， which comprised 448 patients in the TCM group（manipulative reduction plus small splint fixation） and 132 in the surgical treatment group（open reduction and internal fixation）. Each group was further stratified into type A， B， and C subgroups based on AO fracture classification. Radiographic indicators including palmar tilt， radial inclination， and radial height were compared between groups before treatment and 1 day， 1 week， and 4-6 weeks after treatment， and pain visual analog scale（VAS） scores before treatment and 1 week and 4-6 weeks after treatment were also compared. Wrist joint function was assessed 12 weeks after treatment， using the Dienst wrist function score and the Gartland and Werley（G-W） wrist function score. Additionally， the radiographic indicators at different timepoints and the 12-week wrist function levels were compared between groups across different fracture types. ResultsNo statistically significant difference was observed in radiographic indicators and VAS scores at all timepoints before and after treatment， as well as wrist joint function grades assessed by the Dienst score and the G-W score at 12 weeks after treatment （P＞0.05）. Compared to those before treatment， both groups showed increased palmar tilt， radial inclination， and radial height 1 week and 4-6 weeks after treatment， and decreased VAS scores （P＜0.05）. Compared to those 1 week after treatment， both groups showed a decrease in palmar tilt， an increase in radial inclination and radial height， and a reduction in VAS score 4-6 weeks after treatment（P＜0.05）. In type A and B subgroups， the surgical treatment group had a higher radial inclination than the TCM group 4-6 weeks after treatment， while in the type C subgroup， a higher radial height was shown in the surgical treatment group than in the TCM group 4-6 weeks after treatment（P＜0.05）. In type C subgroup， there was significant difference between groups in the wrist joint function by G-W scores 12 weeks after treatment（P＜0.05）. ConclusionManipulative reduction combined with small splint fixation can maintain fracture alignment and alleviate pain in treating distal radius fractures， which achieves therapeutic outcomes comparable to surgical treatment. It is particularly suitable for type A and B fractures and can be considered an effective treatment option for distal radius fractures.

ObjectiveTo construct an automatic measurement model for palmar tilt and radial inclination suitable for traditional Chinese medicine （TCM） clinical scenarios， and to validate its accuracy and efficiency in TCM manipulative reduction settings. MethodsData on anteroposterior （AP） and lateral X-rays of distal radius fractures were collected from patients admitted to 18 TCM/ integrated TCM and western medicine hospitals in Jiangsu province between September 1st， 2023， and September 1st， 2024， via the Jiangsu Diagnosis and Treatment Big Data Platform for TCM Dominant Diseases. A medical image segmentation framework based on multi-scale feature fusion and edge-awareness was employed， combined with anatomical knowledge specific to TCM orthopedics， to optimize the feature extraction strategy of an artificial intelligence （AI） model. This framework enabled automatic segmentation of fracture regions and measurement of distal radius palmar tilt and radial inclination. The accuracy of the AI model in measuring radial inclination and volar tilt was validated， and the measurement time and average time gain rate of the AI model were compared to those of manual measurement. ResultsA total of 15,444 AP and lateral X-ray images of distal radius fractures were collected， and were divided into a training set （11,144 images， 5066 AP and 6078 lateral）， a validation set （3700 images， 1840 AP and 1860 lateral）， and an independent test set （600 images， 300 AP and 300 lateral） after preprocessing. In the measurement of 300 AP X-rays in the independent test set for radial inclination， when the degree error between AI measurement and manual measurement was ＜3° and ＜5°， AI measurement accuracy was 83% and 93%， respectively. In 300 lateral X-rays in the test set for palmar tilt， when AI measurements had an error of ＜3° and ＜5° compared to manual measurements， corresponding accuracy rate was 78% and 90%， respectively. For 50 X-ray images， AI measurement time was （1.37±0.05） min for radial inclination while manual measurement time was （22.57±2.52） min （P＜0.001）； in terms of palmar tilt， the AI measurement time was （1.33±0.14） min， shorter than （23.70±2.80） min for manual measurement time （P＜0.001）. Average time gain rates for manual and AI measurements were 93.93% and 94.39% respectively. ConclusionAn automatic measurement model for palmar tilt and radial inclination in distal radius fractures has been established， enabling more accurate and efficient assessment as well as providing a tool to support the quantitative evaluation of the efficacy of TCM manipulative reduction and large-sample clinical research.

ObjectiveTo explore the effect of the medical-community linkage model on activities of daily living, psychological status and motor function of stroke patients in the community. MethodsA total of 60 stroke patients admitted to two community health service centers and their affiliated stations in Fengtai District, Beijing, from January, 2024 to August, 2025 were enrolled and randomly divided into control group (n = 30) and intervention group (n = 30). The control group received routine medicine, dietary care and rehabilitation management, while the intervention group underwent rehabilitation with the medical-community linkage model, for twelve weeks. They were assessed with modified Barthel Index (MBI), Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD) and Fugl-Meyer Assessment (FMA) before and after intervention. ResultsAfter intervention, the MBI, HAMA, HAMD and FMA scores of patients improved in both groups (|t| > 5.599, P < 0.001), and improved more in the intervention group than in the control group (P < 0.05), except MBI. The HAMA and HAMD scores of family members decreased in both groups (|t| > 10.333, P < 0.001), and decreased more in the intervention group than in the control group (t > 5.681, P < 0.001). ConclusionThe medical-community linkage model can further improve the motor function of stroke patients in community, as well as the psychological status of both patients and their family members.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

OBJECTIVE To provide data support and theoretical reference for drug-regulatory authorities to implement targeted supervision over internet-based pharmaceutical sales.METHODS Using keywords such as “internet-based pharmaceutical sales” and “online drug sales”， the official websites of the People’s Government， drug-regulatory authorities and databases including PKULaw and others were searched， so as to collect typical cases and public disclosure information of administrative penalties related to internet-based pharmaceutical sales from January 2014 to June 2024. Guided by accident-causation theory， the text-mining method was adopted to identify risk factors from four dimensions： human unsafe behaviors， unsafe state of substances， environmental factors and safety management. Grey relational analysis was performed to quantitatively evaluate and screen key risk factors， and targeted governance suggestions were subsequently put forward.RESULTS A total of 617 administrative penalty cases were included. The number of cases increased significantly since 2018. The regional distribution of cases presented a characteristic of “high in the east and low in the west”. Violations were mainly concentrated in the business qualification examination link， and online pharmaceutical retail enterprises were the dominant law-breaking subjects. A risk identification system for internet-based pharmaceutical sales was constructed， covering 4 primary-level， 17 secondary-level and 56 tertiary-level risk factors. Through grey relational analysis， 37 key tertiary-level risk factors （most of which belonged to the safety-management dimension） including inadequate bill management and illegal drug-advertising content， as well as 12 key secondary-level risk factors such as drug-advertising violations and non-standard drug storage， were screened out.CONCLUSIONS Inadequate capabilities and weak compliance awareness of practitioners， illegal drug advertising， non-standard drug storage and transportation， and imperfect quality-management systems of online-drug-sales enterprises and third-party platforms are prominent safety risk factors for internet-based pharmaceutical sales. It is recommended to strengthen qualification examination and competency training for practitioners， standardize drug-information display and drug advertising， improve the management system of drug warehousing and logistics， and refine institutional requirements for key links， so as to improve the supervision efficiency of internet-based pharmaceutical sales.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

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.

BACKGROUND: Severe stroke has high rates of mortality and morbidity. This study aimed to investigate the clinical course, causes of worsening, and outcomes of severe ischemic stroke. METHODS: This prospective, multicenter cohort study enrolled adult patients admitted ≤30 days after ischemic stroke from nine hospitals in China between September 2017 and December 2019. Severe stroke was defined as a score of ≥15 on the National Institutes of Health Stroke Scale (NIHSS). Clinical worsening was defined as an increase of 4 in the NIHSS score from baseline. Unfavorable functional outcome was defined as a modified Rankin scale score ≥3 at 3 months and 1 year after stroke onset, respectively. We performed Logistic regression to explore baseline features and reperfusion therapies associated with clinical worsening and functional outcomes. RESULTS: Among 4201 patients enrolled, 854 patients (20.33%) had severe stroke on admission. Of 3347 patients without severe stroke on admission, 142 (4.24%) patients developed severe stroke in hospital. Of 854 patients with severe stroke on admission, 33.95% (290/854) experienced clinical worsening (median time from stroke onset: 43 h, Q1-Q3: 20-88 h), with brain edema (54.83% [159/290]) as the leading cause; 24.59% (210/854) of these patients died by 30 days, and 81.47% (677/831) and 78.44% (633/807) had unfavorable functional outcomes at 3 months and 1 year respectively. Reperfusion reduced the risk of worsening (adjusted odds ratio [OR]: 0.24, 95% confidence interval [CI]: 0.12-0.49, P  <0.01), 30-day death (adjusted OR: 0.22, 95% CI: 0.11-0.41, P  <0.01), and unfavorable functional outcomes at 3 months (adjusted OR: 0.24, 95% CI: 0.08-0.68, P <0.01) and 1 year (adjusted OR: 0.17, 95% CI: 0.06-0.50, P  <0.01). CONCLUSIONS: Approximately one-fifth of patients with ischemic stroke had severe neurological deficits on admission. Clinical worsening mainly occurred in the first 3 to 4 days after stroke onset, with brain edema as the leading cause of worsening. Reperfusion reduced the risk of clinical worsening and improved functional outcomes. REGISTRATION ClinicalTrials.gov , NCT03222024.
Humans ; Male ; Female ; Prospective Studies ; Ischemic Stroke/mortality* ; Aged ; Middle Aged ; Aged, 80 and over ; Stroke ; Brain Ischemia