Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

Objective:To investigate the clinical effect of indocyanine green angiography (ICGA)-assisted design and harvest of expanded flaps for scar reconstruction.Methods:This study was a retrospective observational study. From April 2019 to August 2023, 19 patients with scars (8 males, 11 females; aged 3-38 years) treated at the Plastic Surgery Hospital of Peking Union Medical College and Chinese Academy of Medical Sciences met the inclusion criteria. The scars were distributed on the head, face, trunk, and extremities. In stage Ⅰ surgery, skin soft tissue expanders were implanted in suitable areas around the scars for skin soft tissue expansion. In stage Ⅱ surgery, the scar tissue was excised, resulting in wound areas ranging from 100 to 210 cm 2, and expanded flaps were designed. ICGA was used to identify target perforators and their accompanying veins, and the flap design was adjusted to ensure the inclusion of complete arterial and venous axes. The expanded flap with an area of 120 to 240 cm2 was harvested using unilateral back-cut technique and transferred to the recipient site, and the donor site wound was sutured directly. The durations of the arterial and venous phases of ICGA during flap design were recorded. The length-to-width ratios of the back-cut flaps were calculated for different regions. After stage Ⅱ surgery, the blood perfusion and survival of the flap, the wound healing at the donor site, and the occurrence of complications were observed. During follow-up, the appearance, color, and texture of the patient's flap were observed. Results:The arterial phase of ICGA lasted 10-27 (18±5) s, and the venous phase lasted 78-116 (100±10) s. The length-to-width ratios of the back-cut flaps were 1.22±0.32, 1.63±0.12, and 1.15±0.21 for the head and neck, trunk, and limb regions, respectively. After stage Ⅱ surgery, one patient had a large area of insufficient blood perfusion in the flap. By comparing ICGA images before and after flap transfer, the sutures at the oral commissure were loosened, the blood flow of the flap was restored. The blood perfusion of the flaps in other patients was good. All flaps survived completely, with well-healed donor site wounds and no complications. During 0.5-14.0 months of follow-up, all flaps of patients demonstrated excellent appearance, with color and texture matching the surrounding skin.Conclusions:As a means of superficial blood flow visualization, ICGA can not only clearly show the microvascular distribution of the expanded flap before operation, assist in optimizing the design of the flap, but also evaluate the blood perfusion of the flap after operation, reduce the occurrence of complications, and provide a full-process navigation for the harvesting of expanded flaps, thereby improving the safety of flap transfer for scar reconstruction.

Objective In this study,we investigated the correlation between the scores for different Liebowitz Social Anxiety Scale(LSAS)subscale models and the metabolic activity in specific regions of the brain using 18F-fluorodeoxyglucose(FDG)positron emission tomography/computed tomography(PET/CT)(18F-FDG PET),thereby improving the understanding of the neurobiological characteristics of social anxiety.Methods A total of 39 cognitively normal participants(29 men and 10 women,aged 30-63 years)were enrolled.All participants underwent LSAS assessment and brain 18F-FDG PET scanning.Correlations between metabolic activities in various brain regions and scores from the different LSAS subscales were analyzed accordingly.Results LSAS subscale scores were significantly correlated with metabolic activity in specific brain regions.In the Safren model,the score for the observation by others subscale was positively correlated with the left fusiform gyrus(P<0.001,false discovery rate[FDR]-corrected)and the left caudate tail(P<0.001,FDR-corrected),suggesting a close association between mood states related to observation by others and the metabolic activity in these regions.In the Baker model,the score for the eating and drinking subscale was negatively correlated with the right precuneus(P<0.001,FDR-corrected),while the score for the assertiveness subscale was positively correlated with the left caudate nucleus(P<0.001,FDR-corrected).These findings revealed the complex associative patterns between various mood and behavioral dimensions and metabolic activities in specific brain regions.Conclusion Social anxiety symptoms are closely associated with metabolic changes in specific brain regions,including the left insula,left caudate tail,and right precuneus.Moreover,different social situations activate distinct brain regions.Compared with individuals with social anxiety disorder,normal individuals exhibit involvement of fewer brain regions when experiencing social anxiety.These findings provide new experimental evidence for understanding the neural mechanisms underlying social anxiety.

Lung cancer is one of the malignant tumours with the highest morbidity and mortality rates worldwide today, posing a major threat to human health. Accurate diagnosis and standardised treatment play a crucial role in improving the survival rate of lung cancer patients. In recent years, the rapid rise of artificial intelligence (AI) has brought about significant changes in the medical field, providing a new diagnostic and treatment model for lung cancer, and making a series of breakthroughs in lung cancer diagnostic imaging, pathological diagnosis, surgical oncology, radiotherapy, and drug development and treatment. This article introduces the current status of AI application in the field of lung cancer diagnosis and treatment, and extensively discusses the current challenges and future prospects, hoping to provide references and suggestions for future clinical practice.

Objective To explore the differences in gut microbiota among patients with Parkinson disease(PD),major depressive disorder(MDD)and PD with depression(dPD),as well as their correlation with psychological factors.Methods A cross-sectional control design was used for the study.Fecal samples were collected from 30 PD patients,21 dPD patients,and 20 MDD patients for high-throughput 16S rRNA sequencing analysis.The Snaith-Hamilton pleasure scale(SHAPS),ruminative responses scale(RRS),Connor-Davidson resilience scale(CD-RISC)and self-compassion scale short form(SCS-SF)were used for psychological assessments.Results The relative abundance of Megamonas was higher in the MDD group than in the dPD and PD groups,while Prevotella was lower in the MDD group than in the dPD and PD groups.The relative abundance of Escherichia-Shigella in PD was higher than that in the dPD and MDD groups,and the difference was significant(P<0.05).The score of the CD-RISC was positively correlated with the abundance of microbiota at Vibrio(r=0.598,P<0.001)and Shewanella(r=0.569,P<0.001),while the score of ruminative responses scale was positively correlated with the abundance of microbiota at Hydrogenophaga(r=0.625,P<0.001),Rhodococcus(r=0.510,P<0.001).Conclusion There are some differences in gut microbiota among patients with Parkinson disease,Parkinson disease with depression and major depression disorder.The specific microbiota such as Vibrio and Rhodococcus may be related to the psychological factors and depressive symptoms of dPD patients.

BACKGROUND: Approximately 40% of individuals with diabetes worldwide are at risk of developing diabetic kidney disease (DKD), which is not only the leading cause of kidney failure, but also significantly increases the risk of cardiovascular disease, causing significant societal health and financial burdens. This study aimed to describe the burden of DKD and explore its cross-country epidemiological status, predict development trends, and assess its risk factors and sociodemographic transitions. METHODS: Based on the Global Burden of Diseases (GBD) Study 2021, data on DKD due to type 1 diabetes (DKD-T1DM) and type 2 diabetes (DKD-T2DM) were analyzed by sex, age, year, and location. Numbers and age-standardized rates were used to compare the disease burden between DKD-T1DM and DKD-T2DM among locations. Decomposition analysis was used to assess the potential drivers. Locally weighted scatter plot smoothing and Frontier analysis were used to estimate sociodemographic transitions of DKD disability-adjusted life years (DALYs). RESULTS: The DALYs due to DKD increased markedly from 1990 to 2021, with a 74.0% (from 2,227,518 to 3,875,628) and 173.6% (from 4,122,919 to 11,278,935) increase for DKD-T1DM and DKD-T2DM, respectively. In 2030, the estimated DALYs for DKD-T1DM surpassed 4.4 million, with that of DKD-T2DM exceeding 14.6 million. Notably, middle-sociodemographic index (SDI) quintile was responsible for the most significant DALYs. Decomposition analysis revealed that population growth and aging were major drivers for the increased DKD DALYs in most regions. Interestingly, the most pronounced effect of positive DALYs change from 1990 to 2021 was presented in high-SDI quintile, while in low-SDI quintile, DALYs for DKD-T1DM and DKD-T2DM presented a decreasing trend over the past years. Frontiers analysis revealed that there was a negative association between SDI quintiles and age-standardized DALY rates (ASDRs) in DKD-T1DM and DKD-T2DM. Countries with middle-SDI shouldered disproportionately high DKD burden. Kidney dysfunction (nearly 100.0% for DKD-T1DM and DKD-T2DM), high fasting plasma glucose (70.8% for DKD-T1DM and 87.4% for DKD-T2DM), and non-optimal temperatures (low and high, 5.0% for DKD-T1DM and 5.1% for DKD-T2DM) were common risk factors for age-standardized DALYs in T1DM-DKD and T2DM-DKD. There were other specific risk factors for DKD-T2DM such as high body mass index (38.2%), high systolic blood pressure (10.2%), dietary risks (17.8%), low physical activity (6.2%), lead exposure (1.2%), and other environmental risks. CONCLUSIONS DKD markedly increased and varied significantly across regions, contributing to a substantial disease burden, especially in middle-SDI countries. The rise in DKD is primarily driven by population growth, aging, and key risk factors such as high fasting plasma glucose and kidney dysfunction, with projections suggesting continued escalation of the burden by 2030.
Humans ; Global Burden of Disease ; Risk Factors ; Male ; Female ; Disability-Adjusted Life Years ; Diabetic Nephropathies/epidemiology* ; Middle Aged ; Diabetes Mellitus, Type 2/epidemiology* ; Adult ; Diabetes Mellitus, Type 1/complications* ; Aged ; Adolescent ; Young Adult ; Quality-Adjusted Life Years

Metabolic dysfunction-associated steatotic liver disease (MASLD) comprises a spectrum of liver injuries, including steatosis to steatohepatitis (MASH), liver fibrosis, cirrhosis, and relevant complications. The liver mainly comprises hepatocytes, liver sinusoidal endothelial cells (LSECs), Kupffer cells (KCs), immune cells (T cells, B cells), and hepatic stellate cells (HSCs). Crosstalk among these different liver cells, endogenous aberrant glycolipid metabolism, and altered gut dysbiosis are involved in the pathophysiology of MASLD. This review systematically examines advances in understanding the molecular pathogenesis of MASLD, with a focus on emerging therapeutic targets and translational clinical trials. We first delineate the crucial regulatory mechanisms involving diverse liver cells and the gut-liver axis in MASLD development. These cell-specific pathogenic insights offer valuable perspectives for advancing precision medicine approaches in MASLD treatment. Furthermore, we evaluate potential therapeutic targets and summarize clinical trials currently underway. By comprehensively updating the MASLD pathophysiology and identifying promising strategies, this review aims to facilitate the development of novel pharmacotherapies for this increasingly prevalent condition.
Humans ; Fatty Liver/therapy* ; Animals ; Liver/pathology* ; Kupffer Cells/metabolism* ; Hepatocytes/metabolism* ; Hepatic Stellate Cells/metabolism*

Humanistic caring for patients in the operating room refers to providing the whole process of caring medical services for patients in the operating room. In order to standardize humanistic caring services for patients in the operating room of medical institutions, improve the comprehensive service level of the operating room, and enhance the surgical experience of patients, the Chinese Association for Life Care released the group standard " Humanistic Caring Management Standards for Patients in the Operating Room" in December 2023. This article interpreted the basic requirements for humanistic caring of patients in the operating room, the environment and facilities for humanistic caring, the procedures and measures for humanistic caring, and the quality management framework, aiming to assist administrators and clinical practitioners across various levels of medical institutions in accurately understanding and effectively implementing the standard, and to provide essential textual reference and practical guidance for promoting the application of the standard.

Medical therapy and surgical intervention are the two primary approaches for treating myocardial bridge.However,there remains controversy regarding the use of coronary artery bypass grafting(CABG)and myocardial bridge unroofing.Here,we report a case of myocardial infarction following CABG in a patient with a myocardial bridge.The patient was admitted to Lanzhou First Peopie's Hospital with persistent chest pain,chest tightness,and shortness of breath lasting 2 hours.Physical examination revealed no significant abnormalities.Electrocardiography(ECG)indicated extensive anterior wall myocardial infarction.Laboratory findings showed myoglobin levels of 140.1 ng/ml and troponin Ⅰ levels of 2.59 ng/ml,with no other significant abnormalities.The initial diagnosis was acute extensive anterior wall myocardial infarction.Emergency coronary angiography revealed a myocardial bridge in the mid-segment of the left anterior descending artery(LAD).Emergency CABG using the left internal mammary artery to the LAD was performed,leading to symptomatic improvement,and the patient was discharged in stable condition.However,the patient experienced a recurrent myocardial infarction seven years post-surgery and received secondary preventive medical therapy.The patient is currently under ongoing follow-up care.CABG is an effective treatment for myocardial bridge.However,based on the case reported in this study,we recommend careful evaluation of whether a patient may benefit from CABG.

Public hospitals have formed a relatively perfect working foundation in the introduction and training of young talents,but the evaluation system of young talents is not perfect.Based on the requirements of high-quality development,grasp the principle of party management of talents,combine the talents development situation in Jiading District Maternal and Child Health Care Hospital,takes the special training of young talents in administration as the starting point,comprehensively uses the literature method,interview method and Delphi method to establish the index database,uses the exploratory factor analysis meth-od to calculate the index weight,and constructs the evaluation model of young talents in hospital administrative management,so as to help hospitals better screen and evaluate talents and give full play to the value and role of talents as the first resource.