ObjectiveTo develop a full-process data platform of renal rehabilitation, diagnosis and quality control information. MethodsA hierarchical architectural design was proposed, adhering to clinical pathway models and standardized data protocols. The platform comprehensively covered assessment, intervention, follow-up and quality control for maintenance hemodialysis (MHD) patients. By integrating multidisciplinary resources and standardizing rehabilitation workflows, it delivered standardized and intelligent rehabilitation services. ResultsThe platform achieved standardized and intelligent management of rehabilitation services, effectively improved the physiological function, psychological state and quality of life convenience for MHD patients, while significantly reduced the economic and care burden on patients' families and society. ConclusionThe rehabilitation service model based on a full-process data platform may provide scientific and systematic support for MHD patients.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To design a VR-based air evacuation training system for simulating the on-board medical treatment process during air evacuation.Methods A VR-based air evacuation training system was developed which used 3D modeling technology to construct models of the medical aircraft cabin,medical devices and virtual characters to achieve scene interaction.The hardware part of the system included server computers,training terminal computers,VR equipment,3D fusion projection equipment,motion capture equipment,etc.The software of the system was developed using C++,UE4 Blueprint and C# programming languages,including two modules for medical treatment unit and medical treatment training process evaluation.The efficacy of the system was verified by the trials in air evacuation.Results The system developed successfully simulated the scenarios of tracheal tube dislodgement and increased intracranial pressure in the scenario model of open severe craniocerebral injury.The expert evaluation showed that the system gained advantages in training efficiency,low cost,safety,sense of immersion and recorded the operation data in real time to optimize the follow-up training.Conclusion The system developed delivers a virtual training environment with high-fidelity replication of real-mission conditions,enabling whole-course and immersive air evacuation drills.[Chinese Medical Equipment Journal,2025,46(3):15-20]

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To explore the safety and efficacy of intraosseous regional administration (IORA) of vancomycin for preventing infection in primary total knee arthroplasty (TKA).Methods:A total of 124 patients with knee osteoarthritis undergoing TKA between February 2024 and May 2024 at nine hospitals were enrolled. Preoperative infection prophylaxis involved either IORA (0.5 g vancomycin administered via intraosseous regional infusion before incision) or intravenous infusion (1 g vancomycin via peripheral vein). The IORA group included 15 males and 47 females with a median age of 66.5 years (range, 60.0-70.0 years), while the intravenous group included 14 males and 48 females with a median age of 66.0 years (range, 61.8-70.3 years) years. Intraoperative samples were collected including fat and synovium tissues after incision, before prosthesis placement, and after tourniquet release; distal femoral cancellous bone during femoral osteotomy; proximal tibial cancellous bone during tibial osteotomy; proximal intercondylar cancellous bone before prosthesis placement; and peripheral blood from non-infused arms at surgery initiation and after tourniquet release. Vancomycin concentrations were measured using liquid chromatography-tandem mass spectrometry. Vital sign changes were recorded from admission to 5~10 minutes post-IORA (IORA group) or post-incision (intravenous group). Follow-ups were conducted on postoperative day 1 and 3, and at 1 and 3 months, to document complications including IORA-related adverse events, periprosthetic joint infections, surgical site infections, red man syndrome, acute kidney injury, deep vein thrombosis and so on.Results:Vancomycin concentrations in bone, fat, and synovial tissue samples were significantly higher in the IORA group than in the intravenous group ( P<0.05), while vancomycin concentrations in blood samples were significantly lower in the IORA group than in the intravenous group ( P<0.05). Only 7.3%(41/558) of tissue samples in the IORA group had vancomycin concentrations below 2.0 μg/g (the minimum inhibitory concentration of vancomycin against coagulase-negative staphylococcus), compared to 59.3%(331/558) in the intravenous group (χ 2=11.285, P<0.001). In the intravenous group, 16.9%(21/124) of blood samples had vancomycin concentrations exceeding 15.0 mg/L (the threshold associated with a significantly increased risk of nephrotoxicity), while all concentrations in the IORA group were below this threshold, the difference was statistically significant (χ 2=22.943, P<0.001). There were no statistically significant difference ( P>0.05) in vital signs changes before and after vancomycin administration between the two groups. Two patients in the intravenous group experienced incision exudate, while no other related complications occurred in either group. Conclusions:Compared to the traditional intravenous infusion of 1 g vancomycin, intraosseous injection of a low dose (0.5 g) of vancomycin achieves higher local tissue concentrations in the knee joint with a lower incidence of adverse reactions and is safe for infection prophylaxis. Despite guidelines not recommending the routine use of vancomycin for preventing infection after primary TKA, intraosseous injection of 0.5 g vancomycin may be considered intraoperatively for primary TKA in the following scenarios: patients in medical institutions with a high prevalence of methicillin-resistant staphylococcus aureus (MRSA) infections, patients with potential preoperative MRSA colonization, or patients with cephalosporin allergy.

Objective:To explore the safety and efficacy of intraosseous regional administration (IORA) of vancomycin for preventing infection in primary total knee arthroplasty (TKA).Methods:A total of 124 patients with knee osteoarthritis undergoing TKA between February 2024 and May 2024 at nine hospitals were enrolled. Preoperative infection prophylaxis involved either IORA (0.5 g vancomycin administered via intraosseous regional infusion before incision) or intravenous infusion (1 g vancomycin via peripheral vein). The IORA group included 15 males and 47 females with a median age of 66.5 years (range, 60.0-70.0 years), while the intravenous group included 14 males and 48 females with a median age of 66.0 years (range, 61.8-70.3 years) years. Intraoperative samples were collected including fat and synovium tissues after incision, before prosthesis placement, and after tourniquet release; distal femoral cancellous bone during femoral osteotomy; proximal tibial cancellous bone during tibial osteotomy; proximal intercondylar cancellous bone before prosthesis placement; and peripheral blood from non-infused arms at surgery initiation and after tourniquet release. Vancomycin concentrations were measured using liquid chromatography-tandem mass spectrometry. Vital sign changes were recorded from admission to 5~10 minutes post-IORA (IORA group) or post-incision (intravenous group). Follow-ups were conducted on postoperative day 1 and 3, and at 1 and 3 months, to document complications including IORA-related adverse events, periprosthetic joint infections, surgical site infections, red man syndrome, acute kidney injury, deep vein thrombosis and so on.Results:Vancomycin concentrations in bone, fat, and synovial tissue samples were significantly higher in the IORA group than in the intravenous group ( P<0.05), while vancomycin concentrations in blood samples were significantly lower in the IORA group than in the intravenous group ( P<0.05). Only 7.3%(41/558) of tissue samples in the IORA group had vancomycin concentrations below 2.0 μg/g (the minimum inhibitory concentration of vancomycin against coagulase-negative staphylococcus), compared to 59.3%(331/558) in the intravenous group (χ 2=11.285, P<0.001). In the intravenous group, 16.9%(21/124) of blood samples had vancomycin concentrations exceeding 15.0 mg/L (the threshold associated with a significantly increased risk of nephrotoxicity), while all concentrations in the IORA group were below this threshold, the difference was statistically significant (χ 2=22.943, P<0.001). There were no statistically significant difference ( P>0.05) in vital signs changes before and after vancomycin administration between the two groups. Two patients in the intravenous group experienced incision exudate, while no other related complications occurred in either group. Conclusions:Compared to the traditional intravenous infusion of 1 g vancomycin, intraosseous injection of a low dose (0.5 g) of vancomycin achieves higher local tissue concentrations in the knee joint with a lower incidence of adverse reactions and is safe for infection prophylaxis. Despite guidelines not recommending the routine use of vancomycin for preventing infection after primary TKA, intraosseous injection of 0.5 g vancomycin may be considered intraoperatively for primary TKA in the following scenarios: patients in medical institutions with a high prevalence of methicillin-resistant staphylococcus aureus (MRSA) infections, patients with potential preoperative MRSA colonization, or patients with cephalosporin allergy.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective To verify the applicability of a pig STR multiplex amplification system for detecting processed foods containing pork and their digestive samples,and to evaluate its potential in food safety and forensic biological evidence analysis.Methods DNA profiles were obtained using the pig STR amplification system from food samples with different levels of processing(raw pork,boiled pork,fried pork,and sausage)and from digestive samples(rat gastric contents).The influence of processing methods on DNA integrity was assessed.The uniformity of large-scale processed ham products,the consistency of DNA profiles from different parts of the same sample,and the DNA degradation patterns after rat digestion were examined.Results STR profiling of pig DNA was successful in all tested samples.Short fragments showed high amplification stability,while long fragment signals weakened with increasing processing complexity.In processed ham products,DNA profiles were consistent across all sampled parts,with fragment drift within±0.5 bp.Analysis of rat gastric contents showed slight DNA degradation within 2 hours;after 3 hours,long fragment signals weakened,and after 4 hours,some loci signals were lost.Conclusion The pig STR multiplex amplification system exhibits excellent performance in detecting processed pork products and their digestive samples.It can meet the requirements of food traceability and forensic biological evidence analysis for processed pork,providing new insights for the advancement of forensic testing techniques in this field.