Objective:To analyze the association between healthcare workers mental health,institu-tional supplies and facilities,inter-organizational coordination during infectious disease outbreaks,and the healthcare institution resilience.Methods:An online questionnaire survey was conducted among the healthcare workforce from 146 institutions in Beijing from January 13,2023 to February 9,2023,and a total of 1 434 eligible respondents were included.The sample comprised 408 responses from tertiary hos-pitals,117 from secondary hospitals,and 909 from primary care institutions.The resilience indicator for healthcare institutions was defined as the degree to which medical services met patient demands,with in-fluencing factors including physical factors,such as material shortages and facility space adaptation or ex-pansion,organizational factors such as information sharing and patient referral,and psychological factors were evaluated using job satisfaction(extrinsic satisfaction,intrinsic satisfaction),burnout(emotional exhaustion,depersonalization,reduced personal accomplishment),and depression status.Ordered mul-ticlassification Logistic regression was used to examine the impact of various factors on the degree to which healthcare services met patient needs;additionally,demographic factors that might influence institutional resilience were controlled.Results:During the emergency response phase,93％of hospitals maintained the capacity to meet patient needs,though tertiary hospitals demonstrated significantly higher rates of service inadequacy(21.05％).Material shortages were reported across all institutions,with tertiary hos-pitals experiencing more frequent multi-item shortages.Inter-institutional collaboration patterns revealed substantial variation:87.50％of primary care facilities,42.86％of secondary hospitals,and 31.58％of tertiary hospitals.Healthcare workers across all levels reported mild depressive symptoms and moderate-to-severe burnout levels.Regression analysis showed high satisfaction(overall satisfaction β=0.04,ex-trinsic satisfaction β=0.06,and intrinsic satisfaction β=0.08),low degree of job burnout(emotional exhaustion β=-0.04,depersonalization β=-0.07 and reduced personal accomplishment β=0.01),low degree of depression(β=-0.06)were significantly associated with higher healthcare institution re-silience.In addition,material shortages were significantly associated with lower resilience,and renova-tion and expansion of treatment spaces,and information sharing,were all associated with higher resilience.Demographic factors(age,gender,marital status,educational background,etc.)had no sig-nificant impact on resilience.Conclusion:Mental health status significantly influences healthcare institu-tion resilience.As human resources constitute the core asset of healthcare institutions,strategic optimiza-tion of workforce allocation and psychological support interventions can effectively strengthen resilience.Moreover,healthcare institution resilience is positively impacted by orderly material supply chains,timely resource distribution,and adaptive reconfiguration of clinical spaces.Finally,facilitating information sharing also enhances institutional resilience.

Objective: To review the current development of artificial intelligence (AI) technology in the field of transfusion medicine. Methods: A systematic search was conducted in the Clarivate Web of Science Database from inception to December 2024 for literature related to AI and transfusion. A total of 4 775 publications were identified. Based on inclusion and exclusion criteria, 133 original studies were ultimately included and analyzed using a narrative synthesis approach. Results: Research on AI in transfusion has surged since 2020 (accounting for 77% of all publications), with China ranking second globally in publication volume. Among the included studies, 69.2% focused on predicting individual transfusion needs, followed by inventory management (8.3%), diagnosis and prediction of adverse transfusion reactions (6.0%), factors influencing transfusion outcomes (5.3%), blood group identification (5.3%), blood quality testing (4.5%), and precise blood volume measurement (1.5%). Additionally, 4.5% of the studies were published in journals with an impact factor greater than 10; 19.5% developed software or applications; 31.5% were multi-center studies; 48.1% utilized decision tree methods, while 31.5% employed neural network approaches; and 14.2% conducted external validation of the algorithms. Conclusion: AI demonstrates significant potential in transfusion risk prediction, decision support, and blood management. However, challenges remain, including limited model generalizability, insufficient algorithm interpretability, and barriers to clinical translation. The deep integration of AI with transfusion medicine will accelerate the advent of precision transfusion era, maximizing blood resource utilization, reducing waste, and ensuring transfusion safety.

Objective:To examine the interaction between gender and the visceral adiposity index (VAI) in relation to the risk of type 2 diabetes mellitus (T2DM).Methods:This retrospective cohort study utilized data from the public Dryad database derived from the NAGALA (NAFLD in the Gifu Area, Longitudinal Analysis) project (1994-2016). Participants were stratified into quartiles based on VAI levels. A multivariate Cox proportional hazards regression model was employed to evaluate whether VAI independently predicts T2DM risk. Kaplan-Meier survival curves and receiver operating characteristic (ROC) curves were constructed for each VAI quartile. Subgroup analyses were conducted to examine associations across age and body mass index categories. Both multiplicative and additive interaction effects between gender and VAI were assessed. Additionally, gender-specific Cox models were fitted to further explore these associations.Results:A total of 15 453 participants [8 419 males and 7 034 females; mean age, (43.7±8.9) years] were included, with a median follow-up duration of 5.39 years. During follow-up, 373 participants (2.4%) developed T2DM. After adjustment for potential confounders, higher VAI levels were independently associated with increased T2DM risk ( HR=1.16; 95% CI 1.11-1.21), consistent with the results across VAI quartiles. Kaplan-Meier analysis revealed a significant trend of increasing T2DM incidence across VAI quartiles ( P<0.001). The area under the ROC curve for VAI in predicting T2DM at 3, 5, and 10 years was 0.755, 0.735, and 0.696, respectively. Sensitivity analyses showed that elevated VAI was associated with increased T2DM risk across all age and body mass index subgroups (all P<0.05). Regarding interaction analysis, the HR (95% CI) for the multiplicative interaction between VAI and gender was 1.22 (1.19-1.26). The relative excess risk of interaction was -1.08 (95% CI -2.96 to -0.06), the attributable proportion of interaction was -0.54 (95% CI -1.35 to -0.01), and the synergy index was 0.48 (95% CI 0.26-0.91), indicating a negative additive interaction. Using low-VAI women as the reference group, the risk of T2DM in high-VAI women was higher ( HR=2.53, 95% CI 1.59-4.02) compared to high-VAI men ( HR=2.01, 95% CI 1.49-2.72). In gender-specific analyses, increasing VAI remained significantly associated with elevated T2DM risk after adjustment in both females ( HR=1.43, 95% CI 1.21-1.68) and males ( HR=1.16; 95% CI 1.11-1.22), with consistent findings across VAI quartiles. Conclusions:VAI and gender demonstrated multiplicative and additive interaction in relation to T2DM risk. The association between increasing VAI and T2DM risk was more pronounced in women than in men.

Objective:A predictive model for cirrhosis-associated hepatic encephalopathy (HE) was constructed and validated using a machine learning algorithm to evaluate the predictive efficacy of the model.Methods:Clinical data of patients with liver cirrhosis (4 537 cases) in the medical record system and laboratory information system of the First Hospital of Jilin University from January 2018 to December 2019 were collected and analyzed retrospectively. Based on the inclusion and exclusion criteria, 474 patients were finally included in the study. Cohort 1 included patients with cirrhosis without HE (113 cases) and patients with cirrhosis complicated with HE (108 cases) from January to December 2018, and was used for feature screening, model building, optimal algorithm selection, and internal validation of the cirrhosis complicated with HE risk prediction model. Cohort 2 included patients with cirrhosis without HE (133 patients) and patients with cirrhosis complicated with HE (120 patients) from January 2019 to December 2019 for external validation. Lasso regression was utilized to identify key predictive variables, and various models such as extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), random forest (RF), and support vector machine (SVM) were employed for model building and internal validation. The DeLong test was used to compare the predictive efficacy of the four models for HE, and the optimal algorithm was selected by combining the specificity or sensitivity. The area under the ROC curve, calibration curve and decision curve were applied to evaluate the predictive efficacy, accuracy of predicted probabilities and clinical utility of the model.Results:The 46 tests with<30% missing data in Cohort 1 were extracted as variables to be selected for modeling. Seven characteristic variables were obtained using Lasso regression screening, including hemoglobin (Hb), total bile acid (TBA), cholinesterase, total bilirubin, creatinine, prothrombin activity, and circulating platelets. The prediction model built by the LightGBM algorithm (HE-Lab7 model) predicted HE with an area under the curve (AUC) of 0.880, which was higher than that of XGBoost, RF, and SVM (all P<0.05), with a sensitivity of 0.825 and a specificity of 0.836. The Brier score of the calibration curve was 0.147, indicating that the predicted probability of the model is in good agreement with the actual probability of occurrence. Decision curves indicate that the model has a high clinical benefit. In Cohort 2, the HE-Lab7 model predicted HE with an AUC of 0.775, a sensitivity of 0.927, and a specificity of 0.758. Conclusion:The predictive efficacy of the cirrhosis-associated HE risk prediction model developed based on the optimal LightGBM algorithm using the large-scale test data based on four machine learning algorithms is good, which provides a reference basis for early prediction and identification of cirrhosis-associated HE.

With the rapid development of competitive sports, the incidence of anterior cruciate ligament (ACL) injury is on the rise. Such injuries may shorten athletes′ career and lead to other long-term adverse consequences. Although athletes generally recover well after ACL reconstruction, many still struggle to return to their pre-injury performance levels. Advances in the understanding of ACL anatomy and injury mechanisms, along with the evolution of surgical techniques and rehabilitation methods, have provided more individualized and tailored options for athletes following ACL injuries. However, there is currently no consensus in China regarding surgical and rehabilitation strategies for competitive athletes aiming to return to sports after ACL injuries. To this end, the Sports Medicine Committee of the Chinese Research Hospital Association and the Editorial Board of the Chinese Journal of Trauma jointly formulated the Expert consensus on surgical treatment and rehabilitation for competitive sports athletes returning to sports after anterior cruciate ligament injury ( version 2025), and presented 14 recommendations covering surgical indications, preoperative rehabilitation, surgical timing, surgical strategies and postoperative rehabilitation strategies, aiming to improve the surgical treatment and rehabilitation system for ACL injuries in competitive athletes and facilitate their return to high-level sports performance after injury.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

This report presents the management of a critically ill 36-year-old woman diagnosed with Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph +ALL) at 28 weeks of gestation. The patient rapidly deteriorated, developing disseminated intravascular coagulation (DIC) , diffuse alveolar hemorrhage (DAH) , septic shock, and multi-organ dysfunction, necessitating admission to the hematological intensive care unit. Given her critical condition and advanced pregnancy, a chemotherapy-free induction regimen comprising imatinib and dexamethasone was initiated, alongside comprehensive supportive measures, including mechanical ventilation, continuous renal replacement therapy (CRRT) , broad-spectrum antibiotics, and high-dose corticosteroids. During treatment, intrauterine fetal demise occurred, and a stillborn was delivered following obstetric intervention. With aggressive treatment, the patient's respiratory failure, DIC, and DAH gradually resolved, and she achieved complete remission. She subsequently received consolidation chemotherapy, CAR-T cell therapy, and allogeneic hematopoietic stem cell transplantation, achieving sustained complete molecular remission on long-term follow-up. This case demonstrates that for critically ill pregnant patients with Ph + ALL, a chemotherapy-free regimen of targeted therapy and corticosteroids, when combined with intensive supportive care, is a safe and effective approach that may offer a therapeutic option for similar cases.

OBJECTIVE: To investigate the effects of acupuncture on the neurotransmitter levels and gut microbiota in a mouse model of Tourette syndrome (TS). METHODS: Thirty-six male C57/BL6 mice were randomly divided into 4 groups using a random number table method: 3,3'-iminodipropionitrile (IDPN) group, control group, acupuncture group, and tiapride group, with 9 mice in each group. In the IDPN group, acupuncture group, and tiapride group, mice received daily intraperitoneal injections of IDPN (300 mg/kg body weight) for 7 consecutive days to induce stereotyped behaviors. Subsequently, in the acupuncture intervention group, standardized acupuncture treatment was administered for 14 consecutive days to IDPN-induced TS model mice. The selected acupoints included Baihui (DU 20), Yintang (DU 29), Waiguan (SJ 5), and Zulinqi (GB 41). In the tiapride group, mice were administered tiapride (50 mg/kg body weight) via oral gavage daily for 14 consecutive days. The control group, IDPN group, and acupuncture group received the same volume of saline orally for 14 consecutive days. Stereotypic behaviors were quantified through behavioral assessments. Neurotransmitter levels, including dopamine (DA), glutamate (Glu), and aspartate (ASP) in striatal tissue were measured using enzyme-linked immunosorbent assay. Dopamine transporter (DAT) expression levels were additionally quantified through quantitative polymerase chain reaction (qPCR). Gut microbial composition was analyzed through 16S ribosomal RNA gene sequencing, while metabolic profiling was conducted using liquid chromatography-mass spectrometry (LC-MS). RESULTS: Acupuncture administration significantly attenuated stereotypic behaviors, concurrently reducing striatal levels of DA, Glu and ASP concentrations while upregulating DAT expression compared with untreated TS controls (P<0.05 or P<0.01). Comparative analysis identified significant differences in Muribaculaceae (P=0.001), Oscillospiraceae (P=0.049), Desulfovibrionaceae (P=0.001), and Marinifilaceae (P=0.014) following acupuncture intervention. Metabolomic profiling revealed alterations in 7 metabolites and 18 metabolic pathways when compared to the TS mice, which involved various amino acid metabolisms associated with DA, Glu, and ASP. CONCLUSIONS Acupuncture demonstrates significant modulatory effects on both central neurotransmitter systems and gut microbial ecology, thereby highlighting its dual therapeutic potential for TS management through gut-brain axis regulation.
Animals ; Tourette Syndrome/metabolism* ; Gastrointestinal Microbiome ; Neurotransmitter Agents/metabolism* ; Acupuncture Therapy ; Male ; Mice, Inbred C57BL ; Mice

OBJECTIVE: Observational studies have found associations between inflammatory bowel disease (IBD) and the risk of dementia, including Alzheimer's dementia (AD) and vascular dementia (VD); however, these findings are inconsistent. It remains unclear whether these associations are causal. METHODS: We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia. Mendelian randomization (MR) analysis based on summary genome-wide association studies (GWASs) was performed. Genetic correlation and Bayesian co-localization analyses were used to provide robust genetic evidence. RESULTS: Ten observational studies involving 80,565,688 participants were included in this meta-analysis. IBD was significantly associated with dementia (risk ratio [ RR] =1.36, 95% CI = 1.04-1.78; I ² = 84.8%) and VD ( RR = 2.60, 95% CI = 1.18-5.70; only one study), but not with AD ( RR = 2.00, 95% CI = 0.96-4.13; I ² = 99.8%). MR analyses did not supported significant causal associations of IBD with dementia (dementia: odds ratio [ OR] = 1.01, 95% CI = 0.98-1.03; AD: OR = 0.98, 95% CI = 0.95-1.01; VD: OR = 1.02, 95% CI = 0.97-1.07). In addition, genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia. CONCLUSION Our study did not provide genetic evidence for a causal association between IBD and dementia risk. The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.
Humans ; Mendelian Randomization Analysis ; Inflammatory Bowel Diseases/complications* ; Dementia/etiology* ; Observational Studies as Topic ; Genome-Wide Association Study