BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

Objective To explore the influence of the medical and health management model based on artificial intelligence (AI) on type 2 diabetes mellitus (T2DM) combined with masked hypertension (MH). Methods A total of 342 patients with T2DM admitted to the hospital from May 2021 to August 2024 were selected as research subjects, and the incidence rate of MH was counted. All patients were classified into the reference group (routine management) and the study group (AI+medical health management) according to the random number table method, with 171 cases in each group. The self-management, glycolipid metabolism and ambulatory blood pressure were compared between both groups before and after intervention. Results Among the 342 patients with T2DM, MH occurred in 34 cases, with an incidence rate of 9.94% (34/342). The self-management ability in the two groups was improved after 6 months and 12 months of intervention, and the self-management ability was higher in the study group (P<0.05). After 6 months and 12 months of intervention, the glucolipid metabolism indexes in both groups were optimized, and the improvements in the study group were greater (P<0.05). The daytime average systolic blood pressure and diastolic blood pressure, 24 h average systolic blood pressure and diastolic blood pressure were decreased in both groups after 6 months and 12 months of intervention, and the study group showed lower indexes (P<0.05). Conclusion T2DM are prone to MH. AI medical and health chronic disease management can enhance patients' self-management ability, help improve glucose and lipid metabolism, lower blood pressure, and help reduce the risk of MH.

OBJECTIVE To establish the UPLC fingerprint and the method for multi-component content determination in Jingangteng capsules， and to evaluate its quality by combining chemical pattern recognition analysis. METHODS An UPLC method was established. Separation was performed on a Zorbax SB-C 18 Rapid Resolution HD column， with acetonitrile-0.1% formic acid as the mobile phase for gradient elution.Using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicines （2012 edition）， UPLC fi ngerprints were established for 10 batches of Jingangteng capsules， and similarity was evaluated. SPSS 22.0 and SIMCA 14.1 software were used to perform hierarchial-cluster analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）， respectively. The same UPLC method was employed to determine the contents of chlorogenic acid， 3，5-dihydroxy-2-methylbenzoic acid-3- O -glucoside （M1）， caffeic acid， astilbin， oxyresveratrol， quercitrin and resveratrol in the 10 batches of samples. RESULTS A total of 17 common peaks were identified in UPLC fingerprints of the 10 batches of samples， of which 7 were identified as chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol. The similarities of 10 batches of samples ranged from 0.820 to 0.985. The results of hierarchial-cluster analysis showed that 10 batches of samples were grouped into four categories： S1-S4 formed one group， S5 and S6 formed another， S7， S8 and S10 formed a third， and S9 formed a fourth， consistent with the OPLS-DA results； the variable importance projection values for peaks 7， 10， 2， 16 （resveratrol）， 13 （oxyresveratrol）， 11， 6 （caffeic acid）， 5 （M1） and 15 （quercitrin） were ＞1. Quantitative analysis results showed that the contents of chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol were 1.650 8-4.213 7， 0.636 2-2.161 7， 0.031 0-0.086 5， 0.239 1-1.069 3， 0.211 9-1.104 0， 0.488 8-2.399 2， and 0.164 0-0.699 8 mg/g， respectively. CONCLUSIONS UPLC fingerprint and content determination methods established in this study are simple to operate， accurate， reliable and reproducible； when combined with chemical pattern recognition analysis， they can be used to evaluate the quality of Jingangteng capsules. Nine components， such as resveratrol， oxyresveratrol， caffeic acid， M1 and quercitrin， may serve as markers of quality variation.

Organ transplantation is an effective alternative treatment for patients with end-stage organ failure. However, the shortage of donor organs has limited the widespread application of clinical transplantation. In recent years, breakthroughs in CRISPR-Cas9 gene editing technology have overcome the barrier of hyperacute rejection in xenotransplantation, offering a potential solution to the organ shortage crisis. Rejection remains a critical factor affecting graft survival. Antigen-presenting cells play a vital role in the initiation and progression of rejection and immune regulation in xenotransplantation. Therefore, in-depth investigation into the role of antigen-presenting cells in xenotransplantation is of great significance. This article summarizes the roles and therapeutic strategies of professional antigen-presenting cells, including macrophages, dendritic cells and B cells in xenotransplantation, aiming to provide insights for future research on immune regulation mechanisms in this field.

Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

ObjectiveTo investigate the clinical application value of thromboelastographic parameters in assessing coagulation function by analyzing the thromboelastographic features of patients with primary liver cancer （PLC）， and to provide a basis for coagulation management and prognostic evaluation in liver cancer patients. MethodsA retrospective analysis was performed for 1 253 PLC patients who were admitted to The First Affiliated Hospital of Xi’an Jiaotong University from May 2015 to December 2022. According to the presence or absence of cirrhosis， the patients were divided into non-cirrhosis group with 262 patients and cirrhosis group with 991 patients， and according to the presence or absence of HBV infection， they were divided into HBV infection group with 1 055 patients and non-HBV infection group with 198 patients. The patients were stratified based on the severity of liver cirrhosis （Child-Pugh class and MELD score） and liver reserve function （indocyanine green retention rate at 15 minutes ［ICGR15］）， and thromboelastography was used to measure thromboelastographic parameters （reaction time ［R］， coagulation formation time ［K］， α-angle， maximum thrombosis amplitude ［MA］， and coagulation composite index ［CI］） and conventional coagulation markers. The t-test was used for comparison of normally distributed continuous data between two groups； a one-way analysis of variance was used for comparison between multiple groups， and the least significant difference t-test was used for further comparison between two groups. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the Kruskal-Wallis H test was used for comparison between multiple groups， and the Bonferroni correction method was used for further comparison between two groups. The chi-square test was used for comparison of categorical data between grouips， and the Spearman test was used for correlation analysis. ResultsAmong the 991 patients in the cirrhosis group， 826 had Child-Pugh class A （5 — 6 points）， and 165 had Child-Pugh class B （7 — 9 points）； 812 had an MELD score of <10， and 179 had an MELD score of ≥10； 679 had an ICGR15 of <10%， and 294 had an ICGR15 of ≥10%. Compared with the patients with Child-Pugh class A， the patients with Child-Pugh class B had a significantly longer K time and significant reductions in α-angle， MA， and CI （all P <0.001）； compared with the MELD score <10 group， the MELD score ≥10 group had a significantly longer K time and significant reductions in α-angle， MA， and CI （all P<0.001）； compared with the ICGR15 <10% group， the ICGR15 ≥10% group had a significantly longer K time and a significant reduction in MA （both P <0.001）. Among the 1 253 patients， MA was strongly positively correlated with fibrinogen and platelet count （r=0.675 and 0.667， both P<0.001）； The MA had a weak correlation with Child-Pugh score， MELD score， and ICGR15 （r=-0.112， -0.250， and -0.117， all P<0.001）， while the K time，α-angle and CI were weakly correlated with the MELD score （r=0.222， -0.184， and -0.183， all P<0.001），R time was negatively correlated with ICGR15 （r=-0.080， P=0.005）. The HBV infection group had significantly higher MA and CI than the non-HBV infection group （P<0.05）. ConclusionThromboelastography can sensitively identify the hypocoagulable state associated with the progression of liver cirrhosis and the hypercoagulable tendency in HBV-related liver cancer， which provides an important reference for individualized anticoagulant therapy in clinical practice.

The thyroid gland is the largest endocrine organ in the human body， and its dysfunction can cause varying degrees of liver injury， leading to liver failure in severe cases. Patients with hyperthyroidism have a relatively high incidence rate of liver dysfunction， manifesting as hepatocellular injury or cholestatic liver injury， while hypothyroidism is closely associated with metabolic dysfunction-associated fatty liver disease. Autoimmune thyroid diseases， including Hashimoto’s thyroiditis and subacute thyroiditis， are commonly comorbid with autoimmune liver disease. In addition， medications such as antithyroid drugs， amiodarone， and immune checkpoint inhibitors can cause severe liver injury through direct toxicity or immune-mediated mechanisms. Although significant progress has been achieved in related diagnosis and treatment techniques in recent years， there are still many challenges in pathogenesis， individualized treatment strategies， early warning， and prognostic evaluation. This article systematically reviews the research advances in liver injury associated with thyroid dysfunction and proposes the directions for future research， in order to provide guidance for clinical diagnosis and treatment.

To systematically analyzed the reporting status of core elements in publicly available clinical practice guideline(hereafter referred to as "guideline") protocols published domestically and internationally over the past decade, identified existing problems, and provided evidence to inform the standardized writing and publication of future guideline protocols.

OBJECTIVE To upgrade the drug traceability code management system for a pediatric hospital under the “payment by code” background， aiming to comprehensively enhance traceability integrity， efficiency， and compliance. METHODS Taking Xiamen Children’s Hospital as the implementation setting， a before-and-after control design was adopted to construct an intelligent drug traceability code management system through systematic upgrades involving the technology platform， core mechanisms， and coordination with medical insurance. Key interventions included： upgrading a traceability code management platform and designing a dynamic code pool； innovating differentiated traceability mechanisms for routine， split-dose， and special drugs； establishing a tiered early-warning and emergency response system； and constructing a data coordination and quality control system. The drug traceability code upload rate served as the primary outcome. Process indicators such as the root causes distribution of failed uploads and the duration of medication returns， and a comprehensive outcome （the number of insurance-flagged abnormal prescriptions） were also analyzed. The data between the baseline period （April 2025） and the observation period （June-August 2025） were compared and evaluated. RESULTS After the upgrade， the overall upload rate of drug traceability codes increased from 9.21% （baseline） to 99.86% （August 2025）. The upload rate of traceability codes in previously unmanaged areas， such as the inpatient pharmacy and pharmacy intravenous admixture services， soared from 0 to nearly 100%. The proportion of non-uploads due to system issues fell from 66.44% （June 2025） to 2.62% （August Additionally， the number of insurance-flagged） abnormal prescriptions dropped sharply from 2 275.00 in the first “payment by code” policy month （July 2025） to 212.00 by the end of the observation period （August 2025）， a 90.70% decrease. CONCLUSIONS The developed management system effectively addresses complex scenario challenges such as high-frequency drug splitting. It significantly enhances traceability code upload performance and ensures a high degree of compliance with medical insurance data requirements. These outcomes contribute to proactive risk mitigation against insurance claim denials and demonstrate a concurrent optimization of pharmacy operations.