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 develop radiomics score (RS) based on 18F-FDG PET/CT, and construct the machine learning model combining clinical and other relevant factors for personalized prediction of 2-year event-free survival (2-EFS) in patients with diffuse large B-cell lymphoma (DLBCL), and to perform interpretability analysis of the model. Methods:A total of 91 patients (49 males, 42 females; age (57.8±12.8) years) with pathologically confirmed DLBCL from December 2017 to December 2020 at the First Hospital of Shanxi Medical University were retrospectively analyzed. According to the ratio of 7∶3, patients were randomly divided into training set ( n=63) and test set ( n=28), and divided into non-progression group and progression group according to the follow-up results. The whole-body PET semi-quantitative parameters were calculated from the PET/CT images before treatment, and 328 radiomics features were extracted from the largest target lesions of patients. The least absolute shrinkage and selection operator (LASSO) was used to develop the RS. Clinical and PET characteristic difference analysis was performed through χ2 test and Mann-Whitney U test. Extreme gradient boosting (XGBoost) models were constructed based on clinical, PET radiomics features and RS, and the prediction efficiency of each model was evaluated by ROC AUC. The model interpretability was analyzed by using shapely additive explanation (SHAP). Results:Of all patients, 32 had disease progression and 59 did not. There were no significant differences in baseline characteristics between the training set and the test set ( χ2 values: 0.06-1.84, U values: 665.00-763.00, all P>0.05). The comparison between the progression group and non-progression group in the training set showed statistical differences in the international prognostic index (IPI) score ( χ2=4.87, P=0.027), myelocytomatosis viral oncogene (MYC) protein expression ( χ2=4.29, P=0.038), and metabolic tumor volume (MTV; U=307.00, P=0.038). Seven radiomics features were screened by LASSO. Among XGBoost models with different feature combinations, IPI score, MYC protein expression, MTV combined with RS had the highest predictive efficiency (training set: AUC=0.73; test set: AUC=0.70). Through SHAP analysis, RS was the most predictive feature in the optimal model. Conclusion:The machine learning integrated model of IPI score, MYC protein expression and MTV combined with RS can effectively predict the prognosis of DLBCL patients, and baseline 18F-FDG PET/CT radiomics can be used as a potential means to evaluate the prognosis of DLBCL patients.

Objective: To investigate the characteristics of hospitalized injury cases in Huangpu District, Guangzhou City in 2022, so as to provide evidence for optimizing injury prevention interventions. Methods: Data on hospitalized injury cases admitted between January to December 2022 were collected through the hospitalization registry system from 17 healthcare institutions in Huangpu District. The population distribution characteristics, causes of injury, injury sites, duration of hospital stay, and hospitalization costs were descriptively analyzed. Results: A total of 6 729 hospitalized injury cases were reported in Huangpu District in 2022, including 4 277 males and 2 452 females, with a male-to-female ratio of 1.74∶1. The average age was (49.57±19.82) years, with 2 064 cases (30.67%) aged 45 to <60 years and 1 921 cases (28.55%) aged ≥60 years. The median length of hospitalization was 9.00 (interquartile range, 11.00) days, with median hospitalization costs of 15 968.93 (interquartile range, 25 786.69) yuan. In the months of June to August, there were more cases of injury hospitalization,with 1 904 cases accounting for 28.30%. The top three causes of injury were falls (2 895 cases, 43.02%), transportation accidents (1 247 cases, 18.53%) and exposure to inanimate mechanical forces (1 104 cases, 16.41%). The top three injured sites were lower limb injuries (1 850 cases, 27.49%), upper limb injuries (1 596 cases, 23.72%) and other sites (1 178 cases, 17.51%). The three leading causes of injury with longest hospitalization duration were burns and scalds, transport accidents and falls, with the median duration being 12.00 (interquartile range, 8.00) days, 10.00 (interquartile range, 13.00) days and 10.00 (interquartile range, 11.00) days, respectively. The top three injury sites associated with the longest hospitalization duration were others, lower limb injuries, and head and neck injuries, with the median duration being 11.00 (interquartile range, 13.00) days, 11.00 (interquartile range, 11.00) days, and 10.00 (interquartile range, 12.00) days, respectively. The causes of injury associated with higher hospitalization costs were falls and transportation accidents, with the median hospitalization cost being 23 550.13 (interquartile range, 30 087.76) yuan for falls and 20 301.94 (interquartile range, 30 589.86) yuan for transportation accidents. The injury sites associated with higher hospitalization costs were lower limb injuries and upper limb injuries, with the median hospitalization cost being 24 257.32 (interquartile range, 34 145.54) yuan for lower limb injuries and 16 506.33 (interquartile range, 20 052.27) yuan for upper limb injuries. Conclusions In Huangpu District, hospitalized injury mainly occurred among males and individuals aged ≥45 years, with the higher incidence observed between June and August. Fall was the primary cause of injury, while lower limb injuries was the main injury sites. The injury resulted in substantially higher hospitalization costs.

OBJECTIVE: To evaluate the effectiveness of Poster Fusion Cage combined with xenogeneic bone graft augmentation for bone defect management in distal radius fractures. METHODS: A retrospective analysis was conducted on 20 patients with bone defects complicating distal radius fractures who met the selection criteria and were treated between June 2022 and June 2024. The cohort comprised 2 males and 18 females, aged 54-87 years (mean, 63.3 years). Etiologies included falls in 17 cases, traffic accidents in 2 cases, and crush injury in 1 case. According to AO classification, there were 5 cases of type A, 8 cases of type B, and 7 cases of type C. The interval from injury to operation ranged from 2 to 10 days (mean, 5.8 days). All patients underwent volar plate fixation augmented with Poster Fusion Cage and demineralized xenogeneic bone matrix grafting. The operation time, intraoperative blood loss, fracture healing time, and postoperative complications were recorded. Radiographic parameters, including radial height, volar tilt, and ulnar deviation, were measured on standardized X-ray films obtained immediately postoperatively and at last follow-up, and whether secondary reduction loss occurred was judged. At last follow-up, wrist range of motion (extension, flexion, radial deviation, ulnar deviation, pronation, and supination) and grip strength (expressed as a percentage of the contralateral side) were measured. Wrist function was assessed using the Disabilities of the Arm, Shoulder, and Hand (DASH) score and Patient-Rated Wrist Evaluation (PRWE) score. RESULTS: The operation time was 70-200 minutes (mean, 116.4 minutes), and the intraoperative blood loss was 10-80 mL (mean, 36.5 mL). All surgical incisions healed by first intention, with no neurovascular complications documented. All patients were followed up 9-12 months (mean, 11.6 months). All fractures healed normally, with a healing time of 8-14 weeks (mean, 9.95 weeks). No significant difference was observed in radial height, volar tilt, or ulnar deviation between immediate postoperatively and last follow-up ( P>0.05). All fractures achieved satisfactory reduction, with no secondary loss of reduction or implant failure occurring during follow-up. At last follow-up, the range of motion of the affected wrist joint was 60°-65° (mean, 62.5°) in extension, 67°-75° (mean, 71.1°) in flexion, 18°-23° (mean, 20.4°) in radial deviation, 28°-33° (mean, 30.1°) in ulnar deviation, 69°-80° (mean, 74.7°) in pronation, and 69°-82° (mean, 75.6°) in supination. Grip strength recovered to 75%-85% (mean, 80%) of the contralateral side. Functional scores showed a DASH score of 5-15 (mean, 9.4) and PRWE score of 8.0-12.5 (mean, 10.2). CONCLUSION The combination of Poster Fusion Cage and xenogeneic bone graft augmentation provides a safe and effective treatment for bone defects in distal radius fractures.
Retrospective Studies ; Humans ; Male ; Female ; Middle Aged ; Aged ; Aged, 80 and over ; Treatment Outcome ; Wrist Fractures/surgery* ; Heterografts ; Transplantation, Heterologous/methods* ; Bone Transplantation/methods* ; Operative Time ; Blood Loss, Surgical ; Radius/surgery* ; Fracture Healing ; Time Factors ; Postoperative Complications/etiology* ; Range of Motion, Articular ; Follow-Up Studies ; Internal Fixators ; Fracture Fixation, Internal/methods* ; Combined Modality Therapy

Objective:To investigate the association between frailty and prognosis of elderly patients in the emergency department, and to validate frailty screening tools suitable for the emergency department.Methods:This was a prospective cohort study. Clinical data of elderly patients over 60 years old treated in the emergency department of Beijing Bo'Ai Hospital from January to December 2021 were collected. The Frailty Screening Questionnaire (FSQ), FRAIL Scale (FRAIL) and Clinical Frailty Scale (CFS) were used to score patients, and patients were divided into frail or non-frail group according to the criteria of the above three scales. Twelve-month all-cause mortality was the primary endpoint, dependence and re-admission to the emergency department within 12 months were secondary outcomes. Receiver operating characteristic curves were used to evaluate the ability of the FSQ, FRAIL and CFS scores to predict the primary and secondary endpoints, and the areas under the curve (AUC) were calculated and compared. Survival analysis was performed using Cox hazard proportional regression model, and relative risk was expressed as hazard ratio ( HR) and 95% CI. Results:A total of 406 patients were included in the study. The AUCs (95% CI) of FSQ, FRAIL and CFS scores for predicting 12-month all-cause mortality were 0.879 (0.844-0.909), 0.838 (0.798-0.872), 0.906 (0.873-0.933), respectively (all P<0.001). The AUCs of 3 scores for predicting secondary endpoints ranged from 0.820 to 0.889 (all P<0.001). Pairwise comparisons of the AUCs showed that the CFS was superior to one or both of the other frailty screening scales in predicting 12-month all-cause mortality and dependence except for re-admission to emergency room within 12 months after discharge (all P<0.05). Cox regression analysis revealed that, after adjusting for sex, age, body mass index and comorbidities, frailty as defined by the FSQ, FRAIL, and CFS scales was independently associated with 12-month all-cause mortality, with the HRadj of 3.267 (95% CI: 2.406-4.435), 2.465 (95% CI: 1.819-3.341), 3.523 (95% CI: 2.648-4.687), respectively (all P<0.001). Conclusions:FSQ, FRAIL and CFS scores can predict adverse outcomes, the CFS is a practical frailty screening tool in the emergency department, and frailty screening can improve the risk stratification of older patients.

Objective To evaluate the value of biparametric MRI(bpMRI)radiomics for predicting postoperation Gleason score(GS)upgrade of prostate cancer(PCa).Methods Totally 344 PCa patients who underwent radical prostatectomy(RP)were retrospectively enrolled and divided into training set(n=241)and test set(n=103)at a ratio of 7∶3.T2WI,diffusion weighted imaging(DWI)and apparent diffusion coefficient(ADC)map radiomics signatures were constructed based on preoperative bpMRI,respectively,then logistic regression(LR)algorithm was used to establish bpMRI radiomics model.Univariate and multivariate logistic regression analyses were performed to screen independent risk factors for postoperation GS upgrade of PCa,and a clinical model was constructed.Then a clinical-radiomics combined model was established based on clinical model and bpMRI radiomics model.Receiver operating characteristic curves were drawn,the area under the curves(AUC)were calculated to evaluate the efficacy of each model for predicting postoperation GS upgrade of PCa.Results Elevated preoperative prostate imaging reporting and data system(PI-RADS)score and reduced biopsy Gleason grade group(GG)were both independent risk factors of postoperation GS upgrade of PCa(both P＜0.05).The AUC of bpMRI radiomics model and clinical-radiomics combined model for predicting postoperation GS upgrade of PCa were higher than that of single-sequence radiomics signatures and clinical model(all P＜0.05),while no significant difference was found between the former two(P＞0.05).The clinical-radiomics combined model demonstrated good efficacy for predicting postoperation GS upgrade of PCa with different biopsy GG before operation,with AUC ranging from 0.835 to 0.949 in training set and 0.803 to 0.948 in test set.Conclusion bpMRI radiomics model could effectively predict postoperation GS upgrade of PCa.

Objective To evaluate the value of biparametric MRI(bpMRI)radiomics for predicting postoperation Gleason score(GS)upgrade of prostate cancer(PCa).Methods Totally 344 PCa patients who underwent radical prostatectomy(RP)were retrospectively enrolled and divided into training set(n=241)and test set(n=103)at a ratio of 7∶3.T2WI,diffusion weighted imaging(DWI)and apparent diffusion coefficient(ADC)map radiomics signatures were constructed based on preoperative bpMRI,respectively,then logistic regression(LR)algorithm was used to establish bpMRI radiomics model.Univariate and multivariate logistic regression analyses were performed to screen independent risk factors for postoperation GS upgrade of PCa,and a clinical model was constructed.Then a clinical-radiomics combined model was established based on clinical model and bpMRI radiomics model.Receiver operating characteristic curves were drawn,the area under the curves(AUC)were calculated to evaluate the efficacy of each model for predicting postoperation GS upgrade of PCa.Results Elevated preoperative prostate imaging reporting and data system(PI-RADS)score and reduced biopsy Gleason grade group(GG)were both independent risk factors of postoperation GS upgrade of PCa(both P＜0.05).The AUC of bpMRI radiomics model and clinical-radiomics combined model for predicting postoperation GS upgrade of PCa were higher than that of single-sequence radiomics signatures and clinical model(all P＜0.05),while no significant difference was found between the former two(P＞0.05).The clinical-radiomics combined model demonstrated good efficacy for predicting postoperation GS upgrade of PCa with different biopsy GG before operation,with AUC ranging from 0.835 to 0.949 in training set and 0.803 to 0.948 in test set.Conclusion bpMRI radiomics model could effectively predict postoperation GS upgrade of PCa.

Objective:To develop radiomics score (RS) based on 18F-FDG PET/CT, and construct the machine learning model combining clinical and other relevant factors for personalized prediction of 2-year event-free survival (2-EFS) in patients with diffuse large B-cell lymphoma (DLBCL), and to perform interpretability analysis of the model. Methods:A total of 91 patients (49 males, 42 females; age (57.8±12.8) years) with pathologically confirmed DLBCL from December 2017 to December 2020 at the First Hospital of Shanxi Medical University were retrospectively analyzed. According to the ratio of 7∶3, patients were randomly divided into training set ( n=63) and test set ( n=28), and divided into non-progression group and progression group according to the follow-up results. The whole-body PET semi-quantitative parameters were calculated from the PET/CT images before treatment, and 328 radiomics features were extracted from the largest target lesions of patients. The least absolute shrinkage and selection operator (LASSO) was used to develop the RS. Clinical and PET characteristic difference analysis was performed through χ2 test and Mann-Whitney U test. Extreme gradient boosting (XGBoost) models were constructed based on clinical, PET radiomics features and RS, and the prediction efficiency of each model was evaluated by ROC AUC. The model interpretability was analyzed by using shapely additive explanation (SHAP). Results:Of all patients, 32 had disease progression and 59 did not. There were no significant differences in baseline characteristics between the training set and the test set ( χ2 values: 0.06-1.84, U values: 665.00-763.00, all P>0.05). The comparison between the progression group and non-progression group in the training set showed statistical differences in the international prognostic index (IPI) score ( χ2=4.87, P=0.027), myelocytomatosis viral oncogene (MYC) protein expression ( χ2=4.29, P=0.038), and metabolic tumor volume (MTV; U=307.00, P=0.038). Seven radiomics features were screened by LASSO. Among XGBoost models with different feature combinations, IPI score, MYC protein expression, MTV combined with RS had the highest predictive efficiency (training set: AUC=0.73; test set: AUC=0.70). Through SHAP analysis, RS was the most predictive feature in the optimal model. Conclusion:The machine learning integrated model of IPI score, MYC protein expression and MTV combined with RS can effectively predict the prognosis of DLBCL patients, and baseline 18F-FDG PET/CT radiomics can be used as a potential means to evaluate the prognosis of DLBCL patients.

ObjectiveThe differential expression of microRNAs （miRNAs） between the active stage and the remission stage of ulcerative colitis （UC） was analyzed by bioinformatics method， and the regulatory relationship was constructed by screening the differentially expressed genes （DEGs）. The mechanism of Xizhuo Jiedu recipe in the treatment of UC was speculated and verified by animal experiments. MethodThe miRNAs data set of colonic mucosa tissue of UC patients was obtained from the gene expression database （GEO）， and the most differentially expressed miRNAs were screened by GEO2R， Excel， and other tools as research objects. TargetScan， miRTarbase， miRDB， STRING， TRRUST， and Matescape databases were used to screen key DEGs， predict downstream transcription factors （TFs）， gene ontology （GO）， and conduct Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis. The key signaling pathways were selected for animal experiments. In animal experiments， the UC mouse model was prepared by making the mouse freely drink 2.5% dextran sodium sulfate （DSS）. Xiezhu Jiedu recipe and mesalazine were given by gavage for seven days， and the inflammatory infiltration of colonic mucosa was observed by hematoxylin-eosin （HE） staining. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of miR-155-5p in colon tissue. Immunohistochemistry and Western blot were used to detect the protein expression levels of cytokine signal transduction inhibitor （SOCS1）， phosphorylated transcriptional signal transductor and activator 3 （p-STAT3）， phosphorylated Janus kinase 2 （p-JAK2）， and retinoic acid-associated orphan receptor-γt （ROR-γt）. The expression levels of transforming growth factor-β （TGF-β）， interleukin-17 （IL-17）， interleukin-6 （IL-6）， and interleukin-10 （IL-10） in serum were detected by enzyme linked immunosorbent assay （ELISA）. ResultThe GSE48957 dataset was screened from the GEO database， and miR-155-5p was selected as the research object from the samples in the active and remission stages. 131 DEGs were screened. The GO/KEGG enrichment analysis was closely related to biological processes such as positive regulation of miRNA transcription and protein phosphorylation， as well as signaling pathways such as stem cell signaling pathway， IL-17 signaling pathway， and helper T cell 17 （Th17） cell differentiation. The Matescape database was used to screen out 10 key DEGs， among which SOCS1 was one of the key DEGs of miR-155-5p. Further screening of the TFS of key DEGs revealed that STAT3 was one of the main TFs of SOCS1. The results of animal experiments showed that Xiezhu Jiedu Recipe could effectively down-regulate the mRNA expression of miR-155-5p and protein expression of p-STAT3， p-JAK2， and ROR-γt in colon tissue of UC mice and the expression of IL-17 and IL-6 in serum of UC mice， up-regulate the protein expression of SOCS1 and the expression of TGF-β and IL-10， increase the level of anti-inflammatory factors， and reduce inflammatory cell infiltration. ConclusionIt is speculated that Xizhuo Jiedu recipe may interfere with SOCS1 by regulating the expression of miR-155-5p in UC mice， inhibit the phosphorylation of STAT3， inhibit the differentiation of CD4⁺ T cells into Th17 cells， reduce the levels of pro-inflammatory factors （IL-17 and IL-6）， and increase the levels of anti-inflammatory factors （TGF-β and IL-10）. As a result， the inflammation of colon mucosa in UC mice was alleviated.

Critically ill patients are at high risk for hospital acquired infections, which can significantly increase the mortality rate and treatment costs for these patients. Therefore, in the process of treating the primary disease, strict prevention and control of new hospital infections is an essential component of the treatment for critically ill patients. The treatment of critically ill patients involves multiple steps and requires a concerted effort from various aspects such as theory, management, education, standards, and supervision to achieve effective prevention and control of hospital infections. However, there is currently a lack of unified understanding and standards for hospital infection prevention and control. To address this, in March 2024, a group of experts in critical care medicine, infectious diseases, and hospital infection from China discussed the current situation and issues of hospital infection control in the intensive care unit together. Based on a review of the latest evidence-based medical evidence from both domestic and international sources, 2024 Expert Consensus on Hospital Acquired Infection Control Principles in the Department of Critical Care Medicine was formed, aiming to provide a basis for the development of hospital infection prevention and control strategies in the field of critical care medicine.