Esophageal cancer is a prevalent malignant tumor of the digestive tract in China, and radical surgery remains the cornerstone of its comprehensive treatment. However, multifactorial challenges such as postoperative gastrointestinal tract reconstruction, traumatic stress, and tumor-related metabolic disturbances render esophageal cancer patients highly susceptible to malnutrition. Perioperative nutritional support therapy plays a crucial role in enhancing surgical safety, improving clinical outcomes, and elevating patients' quality of life by regulating metabolic homeostasis, preserving organ function, and optimizing the immune microenvironment. This article reviews the mechanisms underlying malnutrition in esophageal cancer, methods for nutritional status assessment, and precision intervention pathways based on multi-omics evaluations. The aim is to strengthen clinicians' awareness of standardized perioperative nutritional management for esophageal cancer patients and promote its clinical implementation, thereby facilitating postoperative recovery and improving long-term quality of life.

To address the scarcity of annotated data for pediatric abdominal CT imaging and the insufficient generalization capability of existing models, we constructed a self-supervised pretraining architecture tailored for pediatric CT domain adaptation based on the visual foundation model DINOv3, and validated its performance in the task of pediatric abdominal multi-organ segmentation.

Residual inflammatory risk （RIR） is a key issue to be urgently addressed in the secondary prevention of atherosclerotic cardiovascular disease （ASCVD）. Targeted intervention of RIR has become a novel target for drug development and clinical management. A series of high-quality randomized controlled trials （RCTs）， including COLCOT， LoDoCo2 and CLEAR SYNERGY， provided high-level evidence and confirmed that low-dose colchicine （0.5 mg/d） significantly reduced the risk of cardiovascular events in ASCVD patients at stable stage or after the acute phase， while its efficacy varied in different clinical scenarios. International authoritative guidelines from the European Society of Cardiology and the American Heart Association/American College of Cardiology include low-dose colchicine in the recommendations for ASCVD secondary prevention. Two domestic guidelines released in 2024， namely the Guideline for the Diagnosis and Treatment of Non-ST-Segment Elevation Acute Coronary Syndrome （ 2024 ） and the Guideline for the Diagnosis and Management of Chronic Coronary Syndrome in China ， have also added relevant recommendations. Nevertheless， due to potential racial differences， safety concerns regarding drug-drug interactions， and the relative lack of clinical evidence in China， especially the absence of prospective RCTs using low-dose colchicine for secondary prevention of ASCVD patients， current clinical recommendations still mainly based on international evidence and guidelines， and should not be simply extrapolated.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective To investigate the value of serum lipoprotein-associated phospholipase A2(Lp-PLA2)for predicting high-risk coronary plaques in elderly males.Methods A retrospective study was conducted on 46 elderly males aged ≥60 years undergoing health check-ups and coro-nary computed tomography angiography in our hospital between May and July 2024.Their general clinical data were collected.Artificial intelligence software was used to analyze coronary calcium scores and plaque characteristics.The participants were divided into a high-risk plaque group(n=15)and a non-high-risk plaque group(n=31).The differences were compared between the two groups.Multivariate logistic regression analysis was used to identify the influencing factors for high-risk coronary plaques.ROC curve was plotted to determine the predictive value of serum Lp-PLA2 for high-risk plaques,and its AUC value was calculated.Results The high-risk plaque group had significantly larger proportions of smoking history and hyperlipidemia,and higher level of homocysteine and Lp-PLA2 than the non-high-risk plaque group(P＜0.05,P＜0.01).Multiva-riate logistic regression analysis indicated that Lp-PLA2 was an independent risk factor for high-risk coronary plaques(HR=1.030,95％CI:1.008-1.053,P＜0.05).ROC curve analysis revealed that the AUC value of Lp-PLA2 in predicting high-risk coronary plaques was 0.833(95％CI:0.694-0.927,P＜0.01),with a sensitivity of 93.3％,a specificity of 71.0％,a positive predictive value of 62.5％,and a negative predictive value of 100％.Conclusion Serum Lp-PLA2 is of signif-icant value in predicting high-risk coronary plaques in elderly men.

Objective:To investigate the predictive value of measured cardiac power output(CPO)of echocardiography for the prognosis of elderly patients with acute heart failure(AHF)in the vulnerable period of heart failure.Methods:A total of 120 elderly patients with AHF who admitted to the Third Hospital Affiliated to Shanxi Medical University from January 2021 to January 2024 were selected,and they were divided into the major adverse cardiovascular events(MACE)group(18 cases)and the non-MACE group(102 cases)according to whether occurred MACE in the vulnerable period within 3 months after discharge.The baseline data of the two groups of patients were compared.Logistic regression was used to analyze the influencing factors of occurring MACE in the vulnerable period of patients,and the receiver operating characteristic(ROC)curve was used to analyze the predictive value of CPO for MACE in the vulnerable period of heart failure in elderly patients with AHF.Results:In the baseline data of patients,the total cholesterol,25-hydroxyvitamin D[25(OH)D],reserve CPO,resting CPO,and peak CPO in the MACE group were all lower than those in the non-MACE group,and the differences were statistically significant(t=5.987,2.236,2.921,2.390,4.569,P<0.05).The levels of brain natriuretic peptide(BNP)and N-terminal pro-brain natriuretic peptide(NT-proBNP)in the MACE group were higher than those in the non-MACE group,and the differences were statistically significant(t=22.074,23.368,P<0.05).The results of Logistic regression analysis showed that the total cholesterol,25(OH)D,reserve CPO,resting CPO,and peak CPO were all influencing factors for the occurrence of MACE during the vulnerable period of heart failure in patients(OR=0.064,0.942,0.015,0.035,0.041,P<0.05).ROC curve analysis showed that the efficacy of resting CPO and reserve CPO of the cardiac function indicators in predicting MACE of patients were slightly lower than that of peak CPO.The AUC,sensitivity and specificity of peak CPO in predicting MACE of patients were 0.752,92.2%and 55.6%,respectively.Conclusion:The lower peak CPO value of cardiac function indicator of echocardiography is independent risk factor for MACE during the vulnerable period of heart failure in elderly patients with AHF.Measuring CPO can identify potential poor prognosis populations in advance.

Objective:To investigate the factors affecting the efficacy of 131I treatment for Graves′ disease (GD) and to construct a predictive model for the treatment outcomes of 131I therapy. Methods:Retrospective analysis of the treatment efficacy was performed on 2 190 patients (547 males, 1 643 females, age (42.9±12.4) years) with GD, who received initial 131I treatment in Tianjin Medical University General Hospital between October 2013 and May 2018. Univariate analysis ( χ2 test, et al) and logistic regression were performed to analyze the possible factors affecting the efficacy of 131I treatment. An efficacy prediction model for 131I treatment of GD was constructed, and decision curve analysis (DCA) was used to evaluate the clinical utility of the prediction model. Results:The overall effectiveness rate of 131I treatment for GD patients was 99.95%(2 189/2 190), with a total cure rate of 83.74%(1 834/2 190), among which 94.11%(1 726/1 834) were cured after a single treatment. Pre-treatment thyroid mass was identified as an independent risk factor affecting the efficacy of initial 131I treatment (odds ratio ( OR)=0.983(95% CI: 0.977-0.989), P<0.001). The clinical cure rate was higher in patients who received an adequate dose of 131I compared with that in patients who didn′t receive an adequate dose (79.97%(1 537/1 922) vs 70.52%(189/268); χ2=12.57, P<0.001), but it did not increase the incidence of hypothyroidism within one year. A predictive model was constructed, and it was found that thyroid mass and disease duration had a relatively high impact on the clinical cure rate. The concordance index (C-index) of the predictive model was 0.623(95% CI: 0.593-0.654). DCA indicated that the predictive model offered substantial net benefits across a wide range of probability thresholds. Conclusions:131I treatment is effective in most patients with GD. The predictive model for efficacy of initial 131I treatment developed in this study can assist in evaluating treatment outcomes and help clinicians select the most suitable 131I treatment dose, enhancing clinical decision-making.

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.

By establishing a complete data organizational structure,technical architecture,quality control framework,and concept framework,hospitals can effectively regulate data management,data security,and quality monitoring,achieving full-cycle monitoring of data management.Breaking down the resource barriers of data systems,improving the efficiency of data usage and circulation,and promoting the increase in data value.It drives the hospital's scientific research innovation,medical insurance cost control,data value monetization,and the improvement of high-quality capabilities.Through the establishment of a sustainable digital culture and operational philosophy,it integrates data with hospital assets,continuously enhancing the value realization of hospital data in operations,management,diagnosis and treatment,and scientific research.

Objective:To evaluate the effect of an anesthesia intensive care unit (AICU)-based Enhanced Recovery After Surgery (ERAS)-multidisciplinary team (MDT) model on prognosis in patients following minimally invasive cardiac surgery.Methods:This was a retrospective cohort study. Medical records were reviewed for patients who received standardized ERAS-MDT model and underwent minimally invasive cardiac surgery and were admitted to an intensive care unit (ICU) at the First Affiliated Hospital of Xi′an Jiaotong University between March and December 2023. The patients admitted to the AICU postoperatively were included in AICU group, while the patients admitted to the cardiac surgical intensive care unit (CSICU) were included in CSICU group. Clinical data from both groups were collected and compared, including the baseline patient characteristics (age, gender, body mass index, comorbidities, severity of preoperative pulmonary hypertension, preoperative cardiac function status [ejection fraction, New York Heart Association functional class]), intraoperative conditions (types of surgical procedures, cardiopulmonary bypass time, operation time), postoperative recovery (duration of postoperative endotracheal intubation in ICU, total duration of treatment with ventilators, postoperative treatment duration in ICU, postoperative length of hospital stay, total length of hospital stay), postoperative adverse events (in-ICU bedside resuscitation, postoperative bedside resuscitation on ward, readmission to ICU from ward, re-operation [bedside thoracotomy, return to the operating room], postoperative pulmonary infection, postoperative treatment using continuous renal replacement therapy, postoperative cerebral infarction, in-hospital death), and medical costs (total hospitalization costs, out-of-pocket expenses, nursing costs, non-surgical treatment costs).Results:Compared with CSICU group, the rate of early postoperative extubation was significantly increased, the duration of intubation and stay in ICU was shortened, the postoperative and total length of hospital stay was shortened, the incidence of postoperative pulmonary infection was decreased, and the total hospitalization costs, out-of-pocket expenses, nursing care costs, and non-surgical treatment costs were reduced in AICU group ( P<0.05). Conclusions:Compared with the CSICU-based ERAS-MDT model, the AICU-based ERAS-MDT model can accelerate postoperative recovery and patient turnover, improve outcomes, and reduce healthcare costs more effectively in patients following minimally invasive cardiac surgery.