Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

ObjectiveTo investigate the epidemiological characteristics of human parainfluenza virus (HPIV) in Pudong New Area, Shanghai, and to provide a basis for the prevention and control of HPIV infections in this area. MethodsA total of 8 180 cases with acute respiratory infection (ARI)/influenza-like illness (ILI) attending the fever outpatient clinics, pediatric outpatient clinics, respiratory outpatient clinics, pediatric wards, emergency departments, respiratory wards, and intensive care units (ICUs) and other monitoring departments in 9 sentinel hospitals in Pudong New Area from 2017 to 2022 were selected as the research subjects, and their nasopharyngeal/ throat swabs were collected. Polymerase chain reaction (PCR) method was performed for testing the respiratory virus such as influenza virus, human adenovirus, human parainfluenza virus, respiratory syncytial virus (RSV), human enterovirus, rhinovirus, et al. HPIV serotypes were analyzed, and the detection rates of HPIV were compared between different times, seasons, and population groups. ResultsThe overall HPIV detection rate of ARI/ILI cases in Pudong New Area was 3.73% (305/8 180) in 2017‒2022, with HPIV-3 being the predominant serotype. The detection rate of HPIV decreased significantly in 2017‒2022, peaking at 7.66% (99/1 293) in 2017 and falling to 0.80% (13/1 617) in 2021. Statistically significant differences were observed in HPIV detection rates across different years (χ²_trend=80.037, P_trend<0.001). The detection rate was higher in 2017‒2019 than that in 2020‒2022 (χ²_trend=38.990, P_trend<0.001). HPIV exhibited seasonal patterns in 2017‒2019, with higher detection rates in summer and autumn and lower in spring and winter, whereas no seasonal patterns were observed in 2020‒2022. Children aged <6 years had the highest detection rate (7.07%, 139/1 967), followed by adults aged ≥60 years (4.78%, 85/1 779). Statistically significant differences were observed in the detection rates of HPIV among different age groups (χ²=111.210, P<0.001). Symptoms of HPIV infection were predominantly cough, fever, and runny nose in pre-school children, fever, cough, and sore throat in school-age children, and adults, and cough, expectoration, and fever in the elderly. ConclusionThe HPIV detection rate in Pudong New Area was low in 2017‒2022. The seasonal pattern of HPIV circulation in Pudong New Area disappeared in 2020‒2022 due to the influence of infectious disease epidemics. Young children and the elderly should be prioritized in HPIV prevention and control efforts.

Objective To describe and analyze the epidemiological characteristics of scrub typhus in Huai'an, Jiangsu Province from 2006 to 2024 and explore the long-term incidence trend and distribution of high-risk areas, and to formulate targeted prevention and control strategies. Methods The scrub typhus case report data of Huai'an from 2006 to 2024 in the Chinese Disease Prevention and Control Information System were extracted for descriptive analysis. Results A total of 898 cases of scrub typhus were reported in Huai'an, with an average annual incidence rate of 0.96 per 100 000 from 2006 to 2024. There was a turning point in the incidence trend of scrub typhus in 2011. From 2006 to 2011, the annual percentage change (APC) was 47.09% (95% CI: 7.53 - 859.39), and the upward trend was statistically significant (P < 0.05). From 2012 to 2024, the APC was -2.12% (95% CI: -29.09 - 3.75), and the downward trend was not statistically significant. October and November were the high-incidence months, and the total concentration from 2006 to 2024 was 0.93, indicating that scrub typhus had strict seasonality. The circular distribution method estimated that the peak period of the epidemic was from October 11th to November 25th, and the peak day of incidence was November 3rd. Jinhu County was a high-incidence area. The ratio of male to female cases was 1.03. The age group with the highest reported incidence was 40 to < 80 years old. The occupation with the highest proportion was farmers, accounting for 78.03%. Conclusion From 2006 to 2024, scrub typhus in Huai'an shows a peak every 3 - 4 years. Middle-aged and elderly farmers are the key population at risk, and Jinhu County is a key area. In the future, targeted health education should be carried out to effectively control the prevalence of scrub typhus.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

Tracheal intubation in emergency and complex scenarios is difficult for critical care medicine residents.Virtual reality(VR)technology has not been used in the training of tracheal intubation in critical care scenarios in China.This project team has developed an emergency tracheal intubation training system for the intensive care unit(ICU)based on virtual simulation technology,and has obtained the computer software copyright registration certificate from the National Copyright Administration(registration number:2024SR1139484).This system uses a case script of acute respiratory distress syndrome(ARDS)secondary to severe acute pancreatitis,sets the roles of patients,family members,nurses and residents,collects digital resources of ICU rescue scenes,computer-aided design(CAD)drawings,instrument models and equipment photos,models instruments and equipment,and uses PICO 4 Pro VR helmets to display the ICU environment in the virtual scene.The key points of skill assessment include tracheal intubation operation,the ability to interpret laboratory results,the ability to judge diseases and the ability to work in teams.The user center contains 3 submodules,namely,the score center,skill analysis and user management.There are 3 user roles in the system,namely,residents,teachers and administrators.The system can track and record the entire operation process,including video recording and playback,and score and comprehensively evaluate each step,thereby realizing an objective and quantitative training and assessment system.By simulating the three-dimensional clinical operation environment of the ICU,the entire process of real tracheal intubation is fully reproduced.Resident doctors are placed in the ICU rescue scene,focusing on training tracheal intubation skills,the ability of doctor-patient communication,on-the-spot response,and teamwork,which is expected to become an important type of standardized teaching in critical care medicine.

To analyze the prevalence, drug resistance and whole genome characteristics of Mycoplasma pneumoniae (MP) in respiratory throat swab samples of hospitalized children with pneumonia in Suzhou City from 2023 to 2024. Throat swab samples of hospitalized children aged 0-14 years old with pneumonia in Suzhou were collected from September 2023 to September 2024. Real-time fluorenscence quantitative PCR technology was used to detect MP nucleic acid. The results showed that the positive rate of MP in 3 235 samples was 22.44% (726/3 235), with a rate of 55.00% in week 47 of 2023. The positive rate of MP increased with age ( χ2=45.842, P<0.001). The study selected MP nucleic acid test positive samples from week 20 (5.13-5.19) to week 23 (6.3-6.9) of 2024 for isolation, culture and resistance phenotype detection. About 31 MP strains were successfully isolated and cultured, all of which were resistant to macrolides. The next-generation sequencing technology and nanopore sequencing technology were used for genome sequencing. All 31 strains carried the A2063G mutation, with the main prevalent genotype being the P1-1, and the main mlST type being the ST3. Despite the overall genomic similarity between strains being over 99%, there were significant differences between the P1-1 and P1-2 strains in the P1 gene region. In summary, from 2023 to 2024, the main MP type prevalent in Suzhou City is the P1-1 genotype. All isolated MP strains carry an A2063G resistance site mutation and are resistant to macrolides, requiring continuous monitoring and further research.

Objective:To establish a genomic nucleic acid mass spectrometry detection platform for allelic risk associated with Alzheimer's disease.Methods:Whole blood samples of 61 patients diagnosed as Alzheimer's disease in the Affiliated Brain Hospital of Guangzhou Medical University from December 28th, 2023 to 31st, March 2024 were collected and deoxynucleic acid (DNA) was extracted, including 22 males and 39 females, aged (67.36 ± 8.18) years old. After screening out 17 risk gene loci in Chinese population, multiplex polymerase chain reaction primers, single-base extension primers and Sanger sequencing primers were designed. Ten samples were used for primer optimization and debugging through Sanger sequencing and time-of-flight mass spectrometry to establish a detection system. The remaining samples were genotyped using a time-of-flight mass spectrometer and verified by Sanger sequencing for accuracy evaluation. Five samples were selected for gradient dilution and then subjected to time-of-flight mass spectrometry detection to evaluate the detection limit. Three clinical samples, one case of Escherichia coli and one case of Staphylococcus aureus genomic DNA samples were selected for cross-reaction research. The anti-interference ability of the detection system was evaluated against hemolysis, chylous substances and conventional anticoagulants in the samples. Two samples, one wild and one homozygous mutation sample with representative peak shapes, were selected to evaluate the anti-interference ability. Four samples containing the common genotypes of all gene loci in the system were selected and repeated 10 times to evaluate the precision.Results:The minimum intensity of single-base extension primers on mass spectrometry is greater than half of the maximum intensity. All 17 risk gene loci screened were successfully typed. The time-of-flight mass spectrometry detection results of 1,037 loci from 61 samples showed that the genotyping detection rate was 100%. The genotypes of the 20 DNA samples were completely consistent with the results of Sanger sequencing, with an accuracy rate of 100%. The mass spectrometry detection results of five samples after gradient dilution indicated that the low detection limit was 5 ng of DNA. The reaction system has a strong anti-interference ability against hemolysis of samples, chylous substances, conventional anticoagulants and DNA cross-contamination. Homologous allele interference and no cross-reaction between the bacterial genome and 17 gene loci do not affect the risk genome detection results. The results of 10 repeated mass spectrometry tests on 4 samples showed that the precision was 100%.Conclusion:The genomic detection system of Alzheimer's disease risk has been successfully established to provide an auxiliary mean for disease diagnosis and risk assessment.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective To investigate the efficacy of Castor branching stent in treating Stanford type B aortic dissection(TBAD)involving aortic arch.Methods The clinical data of 18 patients with Stanford TBAD,who were treated with Castor branching stent at the Suining Municipal Central Hospital of China from January 2020 to January 2022,were retrospectively analyzed.Results The main bracket and branch bracket of Castor branching stent were successfully released in all the 18 patients with a surgical success rate of 100％,and no internal leakage occurred during operation.During the perioperative period,there were neither aorta-related deaths nor serious complications such as stroke,upper limb ischemia,internal leakage,or stent displacement.The patients were followed up for(14.7±8.3)months,no aorta-related death,stroke,upper limb ischemia,internal leakage,or stent displacement was observed,the blood flow of the left subclavian artery(LSA)was unobstructed,but there was thrombosis formation within the false lumen of the covered stent segment.Conclusion The Castor branching stent has the advantages of reasonable release mode,accurate positioning,effective isolation of the first rupture of Stanford TBAD and reconstruction of LSA,with no serious short-term complications.However,further follow-up observation is needed before its long-term efficacy can be clarified.