With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

The surgical treatment of thoraco-abdominal aortic aneurysm (TAAA) requires a unique multidisciplinary approach. A thorough preoperative examination and evaluation are essential to determine the optimal timing for surgery and to optimize organ function as needed. During the perioperative period, excellent surgical skills and an appropriate strategy for extracorporeal circulation will be employed based on the extent of the aneurysm. Additionally, necessary measures will be taken to monitor and protect the functions of vital organs. Close monitoring and management in the postoperative stage, along with early detection of complications and effective treatment, are crucial for improving the prognosis of TAAA surgery. This article reviews the current research progress in the perioperative management of TAAA surgery.

Objective To explore the diagnosis and treatment strategies for elderly patients with ground-glass opacity (GGO). Methods The imaging features and postoperative pathological findings of the elderly patients with pulmonary GGO receiving surgery in our hospital from 2017 to 2019 were retrospectively analyzed. The patients were divided into an elderly patient group and a non-elderly patient group based on their age. Results Finally 575 patients were included in the study. There were 281 elderly patients, including 83 males and 198 females, with an average age of (67.0±5.3) years. There were 294 non-elderly patients, including 88 males and 206 females, with an average age of (49.1±7.3) years. Compared with the non-elderly patients, elderly GGO patients showed the following distinct clinical features: long observation time for lesions (P=0.001), high proportion of rough edges of GGO (P<0.001), significant pleural signs (P＜0.001) and bronchial signs (P＜0.001), and high proportion of type Ⅱ-Ⅳ GGO (P<0.001), lobectomy type (P=0.013), and invasive lesions reported in postoperative pathology (P<0.001). There was no statistical difference in the average hospital stay between the two groups (P=0.106). Multivariate logistic regression analysis showed that GGO diameter and GGO type were the main factors affecting the operation. Observation time, GGO diameter, GGO type and pleural signs were the main influencing factors for postoperative pathological infiltrative lesions. The cut-off value of GGO diameter in predicting infiltrating lesions was 10.5 mm in the elderly patients group. Conclusion The size and type of GGO are important factors in predicting invasive lesions and selecting surgical methods. Elderly patients with radiographic manifestations of type Ⅱ-Ⅳ GGO lesions with a diameter greater than 10.5 mm should be closely followed up.

Objective To compare the benefits and drawbacks of primary patch expansion versus pericardial tube right ventricular-pulmonary artery connection in patients diagnosed with pulmonary atresia with ventricular septal defect (PA/VSD). Methods A retrospective study was conducted on patients diagnosed with PA/VSD who underwent primary right ventricular-pulmonary artery connection surgery at our center between 2010 and 2020. Patients were categorized into two groups based on the type of right ventricular-pulmonary artery connection: a pericardial tube group and a patch expansion group. Clinical data and imaging findings were compared between the two groups. Results A total of 51 patients were included in the study, comprising 31 males and 20 females, with a median age of 12.57 (4.57, 49.67) months. The pericardial tube group included 19 patients with a median age of 17.17 (7.33, 49.67) months, while the patch expansion group consisted of 32 patients with a median age of 8.58 (3.57, 52.72) months. In both groups, the diameter of pulmonary artery, McGoon index, and Nakata index significantly increased after treatment (P<0.001). However, the pericardial tube group exhibited a longer extracorporeal circulation time (P<0.001). The reoperation rate was notably high, with 74.51% of patients requiring further surgical intervention, including 26 (81.25%) patients in the patch expansion group and 12 (63.16%) patients in the pericardial tube group. No statistical differences were observed in long-term cure rates or mortality between the two groups (P＞0.005). Conclusion In patients with PA/VSD, both patch expansion and pericardial tube right ventricular-pulmonary artery connection serve as effective initial palliative treatment strategies that promote pulmonary vessel development and provide a favorable foundation for subsequent radical operations. However, compared to the pericardial tube approach, the patch expansion technique is simpler to perform and preserves some intrinsic potential for pulmonary artery development, making it the preferred procedure.

This paper systematically summarizes the practical experience of the 2025 Dingri earthquake emergency medical rescue in Tibet. It analyzes the requirements for earthquake medical rescue under conditions of high-altitude hypoxia, low temperature, and low air pressure. The paper provides a detailed discussion on the strategic layout of earthquake medical rescue at the national level, local government level, and through social participation. It covers the construction of rescue organizational systems, technical systems, material support systems, and information systems. The importance of building rescue teams is emphasized. In high-altitude and cold conditions, rapid response, scientific decision-making, and multi-party collaboration are identified as key elements to enhance rescue efficiency. By optimizing rescue organizational structures, strengthening the development of new equipment, and promoting telemedicine technologies, the precision and effectiveness of medical rescue can be significantly improved, providing important references for future similar disaster rescues.

Objective To investigate the incidence, severity and longitudinal trajectories of symptoms at various time points in the perioperative period of lung cancer patients, and to provide scientific basis for clinical staff to implement predictive nursing and dynamic management of symptom clusters. Methods A prospective longitudinal investigation was conducted. The patients with lung cancer who underwent thoracoscopic lung surgery in four wards of the Department of Thoracic Surgery in our hospital were investigated by face-to-face and telephone follow-up before surgery, 1-2 days after surgery, on the day of discharge and 2 weeks after discharge. The investigation tool was the revised Chinese version of MD Anderson Symptom Inventory lung cancer specific module. Results A total of 192 patients with lung cancer were included in this study, including 59 males and 133 females, with an average age of (55.68±11.01) years. There were two symptom clusters (respiratory-gastrointestinal and emotional/psychological-disturbed sleep symptom clusters) before surgery, three symptom clusters (respiratory, gastrointestinal, and emotional/psychological-disturbed sleep symptom clusters) 1-2 days after surgery, three symptom clusters (pain-fatigue-emotional/psychological, respiratory, and gastrointestinal symptom clusters) on the day of discharge, and two symptom clusters (pain-fatigue-respiratory and respiratory symptom clusters) 2 weeks after discharge. The composition of symptoms was different in each time point during perioperative period. Conclusion There are four symptom clusters in patients with lung cancer during perioperative period, which are pain-fatigue-disturbed sleep symptoms, gastrointestinal symptoms, respiratory symptoms and emotional/psychological symptoms. The symptom clusters of lung cancer patients at different time points are relatively stable, but the symptoms within the symptom clusters show dynamic changes. Medical staff should attach great importance to and continuously monitor the dynamic changes of perioperative symptom groups of lung cancer patients, do relevant education and nursing in advance, and timely adjust the management plan according to the symptom group evaluation results.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Objective To explore the predictive value of systolic pulmonary artery pressure (SPAP) on autonomic nerve excitation in patients with valvular disease, so as to provide reference for the formulation of clinical intervention plans. Methods The clinical data of patients with valvular disease who received surgical treatment in the General Hospital of Northern Theater Command from August 28, 2020 to February 3, 2021 were prospectively collected. According to the standard deviation of normal-to-normal R-R intervals (SDNN) of the heart rate variability (HRV) of the long-range dynamic electrocardiogram (ECG) 7 days before the operation, the patients were divided into three groups: a sympathetic dominant (SE) group (SDNN≤50 ms), a balance group (50 ms