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.

Background:Nutritional risk is highly prevalent among gastric cancer patients,yet accurate screening tools remain lacking.Aims:To construct and validate a nutritional risk prediction model for gastric cancer inpatients.Methods:From August 2023 to July 2024,a total of 295 gastric cancer inpatients admitted to the First Hospital of Qinhuangdao were enrolled,and divided into the model group(n=206)and validation group(n=89)at a ratio of 7∶3.Nutritional screening was performed in the model group using the nutritional risk screening 2002(NRS 2002)score.Univariate analysis and multivariate Logistic regression analysis were employed to identify the independent risk factors for nutritional risk,and a prediction model was constructed.The Hosmer-Lemeshow goodness-of-fit test was used to evaluate the consistency between the model constructed and NRS 2002 score.The predictive performance was assessed using ROC curve and validated in the independent cohort.Risk stratification was performed based on the cut-off value derived from the ROC curve,and the nutritional risk in different subgroups of the model group and validation group was assessed.Results:Multivariate Logistic regression analysis indicated that age≥68 years,body mass index(BMI)≤22 kg/m2,anorexia,dysphagia and anemia were the independent risk factors for nutritional risk in gastric cancer patients in the model group(all P<0.05).The prediction model had good consistency with the NRS 2002 score(P=0.567).ROC curve showed that the area under the curve(AUC)of the prediction model for predicting nutritional risk were 0.840(95%CI:0.785-0.895,P<0.001)for the model group and 0.895(95%CI:0.831-0.958,P<0.001)for the validation group when the cut-off value was set at 9.5 points.The proportion of patients with nutritional risk in high-risk subgroup was significantly higher than that in low-risk subgroup in both model group and validation group(P<0.001).Conclusions:The prediction model based on age,BMI,anorexia,dysphagia and anemia can effectively identify nutritional risk in gastric cancer inpatients and may serve as a clinical reference tool.

Objective:To explore the potential categories and influencing factors of medication compliance in patients with cardiometabolic multimorbidity, and provide a reference for formulating targeted intervention measures.Methods:A cross-sectional study design was adopted. From March to October 2024, the patients with cardiometabolic multimorbidity in the First Hospital Affiliated with Hunan Normal University (Hunan Provincial People′s Hospital) were selected by convenience sampling method as research objects. Data were collected using a general information questionnaire, Medication Adherence Rating Scale (MARS), Perceived Social Support Scale (PSSS), and Medication Literacy Questionnaire. The latent class analysis was used to explore the characteristics and classifications of medication compliance in cardiometabolic multimorbidity, and unordered multivariate Logistic regression was used to analyze the influencing factors of different latent classes.Results:A total of 421 subjects were included, consisting of 291 males and 130 females, aged (64.28±9.74) years old. The overall medication adherence score was 6.00 (5.00, 8.00) points, which could be divided into four categories: overall good adherence group (24.47%, 103/421), subjective perception-poor adherence group (15.91%, 67/421), forgetfulness-poor adherence group (37.53%, 158/421), and overall poor adherence group (22.09%, 93/421). The results showed that when taking the overall good adherence group as a reference, the inability to obtain pharmaceutical information from social media, medication literacy scores, social support scores were the influencing factors for the subjective perception-poor adherence group ( OR=4.210, 0.516, 0.733, all P<0.05). Occupational characteristics (employees in public institutions or government-affiliated institutions), age, social support scores were the influencing factors for the forgetfulness-poor adherence group( OR=0.173, 1.155, 0.781, all P<0.05). Occupational characteristics (employees in public institutions or government-affiliated institutions), failure to receive medication guidance from medical staff, medication literacy scores and social support scores were the influencing factors for the overall poor adherence group( OR values were 0.136-5.275, all P<0.05). When taking the overall poor adherence group as a reference, failure to receive medication guidance from medical staff and medication literacy scores were the influencing factors for the subjective perception-poor adherence group ( OR=0.310, 1.752, both P<0.05). Failure to receive medication guidance from medical staff, age, medication literacy scores and social support scores were the influencing factors for the forgetfulness-poor adherence group ( OR values were 0.315-2.554, all P<0.05). Conclusions:There is significant heterogeneity in medication adherence among patients with cardiometabolic multimorbidity. Healthcare professionals should consider individual characteristics in clinical practice and provide targeted, precise interventions to improve adherence in different patient categories.

Objective To explore the imaging manifestations of Rosai-Dorfman disease(RDD)in children.Methods A total of 12 children with RDD confirmed by pathology were retrospectively enrolled,including 8 cases underwent non-contrast CT(NCCT)+contrast enhanced CT(CECT),2 cases underwent NCCT+CECT+non-contrast MR(NCMR)+contrast enhanced MR(CEMR),1 case underwent NCCT+NCMR and CEMR,while 1 case underwent NCCT and X-ray examinations.Imaging manifestations of RDD in children were observed.Results Among 12 cases,intranodal type RDD was found in 7 case,extranodal type RDD in 3 cases,and mixed type(with both lymph nodes and extranodal sites affected)RDD were noticed in 2 cases.In 7 cases of intranodal type RDD,NCCT and CECT showed multiple lymph node enlargements in both sides of the neck,with uniform isodensity on NCCT and mild-moderate progressive enhancement in 5 cases,while with low-density necrotic area and ring-shaped enhancement in 2 cases.Among 3 cases of extranodal RDD,the lesion in 1 case involved nasal cavity and posterior group of ethmoid sinuses on CT and MRI,which developed circular soft tissue mass centered on nasal septum with moderate heterogeneous enhancement,also compressed the adjacent bone with destruction.In another case of extranodal RDD,CT showed that the lesion involved left ilium and bilateral parietal bones,with bone destruction accompanied by obvious periosteal reaction and soft tissue mass,which was mildly enhanced.In the rest 1 case of extranodal RDD,CT and X-ray film showed that the lesion involved the upper segment of right femur and left parietal bone,with osteolytic destruction accompanied by layered periosteal reaction.The lesions in both 2 cases of mixed type RDD involved brain(1 case involved left parieto-occipital lobe,1 case involved bilateral temporal lobes,left frontal lobe and bilateral occipital lobes),presented as isodensity on CT and equal or slightly low signal intensity on T 1WI,equal-high mixed signal intensity on T2WI,some shaped like brain gyral with mild edema of surrounding tissue,and nodular or mass-like significant enhancement.RDD involvements of bilateral lung,mediastinum and hilar lymph nodes were also observed in the above 2 cases,chest CT showed multiple nodular or small patchy uniform high-density shadows in bilateral lungs,as well as enlarged mediastinum and hilar lymph nodes.Conclusion Imaging manifestations of pediatric RDD had certain specificity,being helpful to diagnosis.

Artificial intelligence(AI)has emerged as a cutting-edge technology leading the future and is a key engine for China's development.In the innovation and research of medical devices,AI has provided critical support in the areas of intelligent diagnostic assistance,intelligent therapeutic assis-tance,intelligent monitoring,life support,et al.Ma-chine learning-enabled device software functions(ML-DSFs)have become an essential component of many medical devices.Recently,the United States Food and Drug Administration(FDA)released a draft guidance titled"Marketing Submission Rec-ommendations for a Predetermined Change Con-trol Plan for Artificial Intelligence/Machine Learn-ing(AI/ML)-Enabled Device Software Functions(Draft)."that aimed to provide a forward-looking approach to foster the development of ML medical devices.By supporting iterative updates through modifications,this approach ensures the continu-ous safety and effectiveness of the devices.This guidance represents the latest in regulatory direc-tion and is especially beneficial for enhancing the quality and efficiency of clinical trials for AI prod-ucts.Therefore,we plan to provide a detailed intro-duction and interpretation of the guidance,with the aim of learning from international advanced regulatory concepts and experiences to promote the development of ML-DSFs with more profound international influence.

AIM To investigate the clinical effects of Yifei Tongluo Decoction combined with azithromycin on patients with childern severe Mycoplasma pneumoniae pneumonia due to Toxic Heat Blocking Lung.METHODS One hundred and fifty-six patients were randomly assigned into control group(78 cases)for 7-day administration of azithromycin,and observation group(78 cases)for 7-day administration of both Yifei Tongluo Decoction and azithromycin.The changes in clinical effects,disappearance time of local symptoms,mycoplasmas,pulmonary imaging score,Toxic Heat Blocking Lung score,pulmonary function indices(PEF,VPTEF,MMF,TPTEF),inflammatory factors(sB7-H3,Cgp-39,sICAM-1,CCL5),immune function indices(RBC-C3bR,RBC-ICR,CD3+,CD4+)and safety indices were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05),along with shorter disappearance time of local symptoms(P＜0.05).After the treatment,the two groups displayed decreased mycoplasmas,pulmonary imaging score,Toxic Heat Blocking Lung score,inflammatory factors,RBC-ICR(P＜0.05),and increased pulmonary function indices,RBC-C3bR,CD3+,CD4+(P＜0.05),especially for the observation group(P＜0.05).No obvious difference in incidence of adverse reactions was found between the two groups(P＞0.05).CONCLUSION For the patients with childern severe Mycoplasma pneumoniae pneumonia due to Toxic Heat Blocking Lung,Yifei Tongluo Decoction combined with azithromycin can safely and effectively alleviate clinical symptoms,improve pulmonary functions,and reduce body inflammatory responses.

Background:Nutritional risk is highly prevalent among gastric cancer patients,yet accurate screening tools remain lacking.Aims:To construct and validate a nutritional risk prediction model for gastric cancer inpatients.Methods:From August 2023 to July 2024,a total of 295 gastric cancer inpatients admitted to the First Hospital of Qinhuangdao were enrolled,and divided into the model group(n=206)and validation group(n=89)at a ratio of 7∶3.Nutritional screening was performed in the model group using the nutritional risk screening 2002(NRS 2002)score.Univariate analysis and multivariate Logistic regression analysis were employed to identify the independent risk factors for nutritional risk,and a prediction model was constructed.The Hosmer-Lemeshow goodness-of-fit test was used to evaluate the consistency between the model constructed and NRS 2002 score.The predictive performance was assessed using ROC curve and validated in the independent cohort.Risk stratification was performed based on the cut-off value derived from the ROC curve,and the nutritional risk in different subgroups of the model group and validation group was assessed.Results:Multivariate Logistic regression analysis indicated that age≥68 years,body mass index(BMI)≤22 kg/m2,anorexia,dysphagia and anemia were the independent risk factors for nutritional risk in gastric cancer patients in the model group(all P<0.05).The prediction model had good consistency with the NRS 2002 score(P=0.567).ROC curve showed that the area under the curve(AUC)of the prediction model for predicting nutritional risk were 0.840(95%CI:0.785-0.895,P<0.001)for the model group and 0.895(95%CI:0.831-0.958,P<0.001)for the validation group when the cut-off value was set at 9.5 points.The proportion of patients with nutritional risk in high-risk subgroup was significantly higher than that in low-risk subgroup in both model group and validation group(P<0.001).Conclusions:The prediction model based on age,BMI,anorexia,dysphagia and anemia can effectively identify nutritional risk in gastric cancer inpatients and may serve as a clinical reference tool.

Objective:To explore the potential categories and influencing factors of medication compliance in patients with cardiometabolic multimorbidity, and provide a reference for formulating targeted intervention measures.Methods:A cross-sectional study design was adopted. From March to October 2024, the patients with cardiometabolic multimorbidity in the First Hospital Affiliated with Hunan Normal University (Hunan Provincial People′s Hospital) were selected by convenience sampling method as research objects. Data were collected using a general information questionnaire, Medication Adherence Rating Scale (MARS), Perceived Social Support Scale (PSSS), and Medication Literacy Questionnaire. The latent class analysis was used to explore the characteristics and classifications of medication compliance in cardiometabolic multimorbidity, and unordered multivariate Logistic regression was used to analyze the influencing factors of different latent classes.Results:A total of 421 subjects were included, consisting of 291 males and 130 females, aged (64.28±9.74) years old. The overall medication adherence score was 6.00 (5.00, 8.00) points, which could be divided into four categories: overall good adherence group (24.47%, 103/421), subjective perception-poor adherence group (15.91%, 67/421), forgetfulness-poor adherence group (37.53%, 158/421), and overall poor adherence group (22.09%, 93/421). The results showed that when taking the overall good adherence group as a reference, the inability to obtain pharmaceutical information from social media, medication literacy scores, social support scores were the influencing factors for the subjective perception-poor adherence group ( OR=4.210, 0.516, 0.733, all P<0.05). Occupational characteristics (employees in public institutions or government-affiliated institutions), age, social support scores were the influencing factors for the forgetfulness-poor adherence group( OR=0.173, 1.155, 0.781, all P<0.05). Occupational characteristics (employees in public institutions or government-affiliated institutions), failure to receive medication guidance from medical staff, medication literacy scores and social support scores were the influencing factors for the overall poor adherence group( OR values were 0.136-5.275, all P<0.05). When taking the overall poor adherence group as a reference, failure to receive medication guidance from medical staff and medication literacy scores were the influencing factors for the subjective perception-poor adherence group ( OR=0.310, 1.752, both P<0.05). Failure to receive medication guidance from medical staff, age, medication literacy scores and social support scores were the influencing factors for the forgetfulness-poor adherence group ( OR values were 0.315-2.554, all P<0.05). Conclusions:There is significant heterogeneity in medication adherence among patients with cardiometabolic multimorbidity. Healthcare professionals should consider individual characteristics in clinical practice and provide targeted, precise interventions to improve adherence in different patient categories.

OBJECTIVE To study the clinical efficacy of Professor Li Bingmao's Tongfu Xiere Quyu Shuli Prescription in the treatment of patients with functional dyspepsia(FD)of spleen and stomach damp-heat and qi stagnation and blood stasis type.METH-ODS A total of 206 patients with functional dyspepsia of spleen and stomach damp-heat and qi stagnation and blood stasis type diag-nosed by Hengshui People's Hospital were included in the study and randomly divided into a study group and a control group with 103 cases in each group.During the treatment,3 cases dropped out in each group.The control group adopted the conventional Western medicine treatment plan for functional dyspepsia(mosapride+rabeprazole),and the study group took Tongfu Xiere Quyu Shuli Pre-scription on the basis of the treatment of the control group.The treatment course of both groups was 4 weeks.The traditional Chinese medicine(TCM)syndrome scores,psychological status[self-rating anxiety scale(SAS),self-rating depression scale(SDS),and quality of life[Nepean dyspepsia life quality index(NDLQI)of the two groups of patients before and after treatment were observed and the clinical efficacy was evaluated;serum motilin(MTL),ghrelin,gastrin(GAS),corticotropin-releasing hormone(CRH)and pep-sinogen(PG Ⅰ,PG Ⅱ)were measured by enzyme-linked immunosorbent assay;changes in gastric motility indexes were analyzed by electrogastrogram analyzer;changes in intestinal flora were detected by instillation method.The occurrence of adverse reactions in the two groups of patients was monitored during treatment.RESULTS After treatment,the TCM syndrome scores of the two groups were significantly reduced(P<0.05,P<0.01),and the score in the study group was lower than that in the control group(P<0.01).The total effective rate of the study group was significantly higher than that in the control group(P<0.01).After treatment,the expression levels of MTL,Ghrelin,GAS,PG Ⅰ and PG Ⅱ in the two groups increased,and CRH decreased,and the improvement degree of the study group was better than that of the control group(P<0.01).After treatment,the main frequency and slow wave percentage of the electrogastrogram increased in the two groups,and the study group was better than that of the control group(P<0.01).After treat-ment,the number of bifidobacteria and lactobacilli in the two groups increased,and the number in the study group was greater than that in the control group,while the number of enterobacteria,enterococci and yeast decreased,and the number in the study group was less than that in the control group(P<0.01).There was no significant difference in adverse reactions between the two groups(P>0.05).CONCLUSION Tongfu Xiere Quyu Shuli Prescription is effective in the treatment of FD patients with spleen and stomach damp-heat syndrome,and can improve FD clinical symptoms,quality of life,anxiety and depression symptoms,regulate gastrointesti-nal hormone expression levels,gastric motility and intestinal flora expression,and does not increase adverse reactions,and is safe and reliable.

Objective To propose a high-precision deep learning-based image assessment method of osteosarcoma chemotherapy efficacy for clinical treatment,as existing methos have low accuracy of osteosarcoma assessment.Methods The low incidence of osteosarcoma led to the small scale of its imaging data and the problem of imbalance in data categories.This study combined deep learning with clinical medical information,combined the bone sarcoma generation module of BoneGAN and the scale lesion information capture module,and proposed OMLA-Net,a deep learning assessment network for chemotherapy effect of bone sarcoma based on multi-scale lesion attention network,which achieved computer-aided bone tumor assessment with integrated data augmentation and focused lesion information through pre-training and generalized loss training.Results In this study,40 cases of osteosarcoma MRI data were used as the basis for the comparison test on the generated dataset,and the OMLA-Net assessment outperformed the SOTA method Conv-LSTM-GAN in terms of the assessment effects such as accuracy and F1 scores,and the difference was statistically significant(Bootstrap statistical method P＜0.05);the subsequent K-fold cross-validation ablation experiments further demonstrated the effectiveness of each module proposed by OMLA-Net.Conclusion OMLA-Net can effectively perform the impact assessment of chemotherapy effect on osteosarcoma,which provides a new idea for subsequent clinical application.