With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

[Objective] To explore the incidence and risk factors of blood transfusion undergoing total knee revision (TKR) using a nationwide database. [Methods] A retrospective data analysis was conducted based on the Nationwide Inpatient Sample (NIS), enrolling patients who underwent TKR from 2015 to 2019 with complete information. Patients under 18 years old and those using anticoagulants, antiplatelets, antithrombotic and non-steroidal were excluded. The patients were divided into two groups based on whether they received blood transfusion or not. The demographic characteristics, length of stay (LOS), total charge of hospitalization, hospital characteristics, hospital mortality, comorbidities and perioperative complications by Wilcoxon rank test for continuous data and chi-square test for categorical data. Logistic regression was performed to identify risk factors of blood transfusion undergoing TKR. [Results] The NIS database included 63 359 patients who underwent TKR. Among them, 5 271 patients received blood transfusion, with an incidence of blood transfusion of 7.8%. There was a decrease in the incidence over the years from 2015 to 2019, dropping from 10.2% to 6.5%. TKR patients requiring transfusions had experienced longer LOS, incurred higher total medical expenses, utilized Medicare more frequently, and had increased in-hospital mortality rates (all P<0.001). Independent risk factors for blood transfusion included female gender, iron-deficiency anemia, rheumatoid disease, collagen vascular disease, chronic blood loss anemia, congestive heart failure, coagulopathy, diabetes with chronic complications, lymphoma, fluid and electrolyte disorders, peripheral vascular disorders, renal failure, valvular disease and weight loss (malnutrition). In addition, risk factors for transfusion in TKR surgery included sepsis, acute myocardial infarction, deep vein thrombosis, gastrointestinal bleeding, heart failure, pneumonia, urinary tract infection, acute renal failure, postoperative delirium, wound infection, lower limb nerve injury, hemorrhage, seroma, hematoma, wound rupture and non healing. [Conclusion] Our findings highlight the importance of recognizing the risk factors of blood transfusion in TKR and establishing corresponding clinical pathways and intervention measures to reduce the occurrence of adverse events.

Objective To clarify the risk factors of diaphragmatic dysfunction (DD) after cardiac surgery with extracorporeal circulation. Methods A retrospective analysis was conducted on the data of patients who underwent cardiac surgery with extracorporeal circulation in the Department of Cardiovascular Surgery of Peking University People's Hospital from January 2023 to March 2024. Patients were divided into two groups according to the results of bedside diaphragm ultrasound: a DD group and a control group. The preoperative, intraoperative, and postoperative indicators of the patients were compared and analyzed, and independent risk factors for DD were screened using multivariate logistic regression analysis. Results A total of 281 patients were included, with 32 patients in the DD group, including 23 males and 9 females, with an average age of (64.0±13.5) years. There were 249 patients in the control group, including 189 males and 60 females, with an average age of (58.0±11.2) years. The body mass index of the DD group was lower than that of the control group [(18.4±1.5) kg/m2 vs. (21.9±1.8) kg/m2, P=0.004], and the prevalence of hypertension, chronic obstructive pulmonary disease, heart failure, and renal insufficiency was higher in the DD group (P<0.05). There was no statistical difference in intraoperative indicators (operation method, extracorporeal circulation time, aortic clamping time, and intraoperative nasopharyngeal temperature) between the two groups (P>0.05). In terms of postoperative aspects, the peak postoperative blood glucose in the DD group was significantly higher than that in the control group (P=0.001), and the proportion of patients requiring continuous renal replacement therapy was significantly higher than that in the control group (P=0.001). The postoperative reintubation rate, tracheotomy rate, mechanical ventilation time, and intensive care unit stay time in the DD group were higher or longer than those in the control group (P<0.05). Multivariate logistic regression analysis showed that low body mass index [OR=0.72, 95%CI (0.41, 0.88), P=0.011], preoperative dialysis [OR=2.51, 95%CI (1.89, 4.14), P=0.027], low left ventricular ejection fraction [OR=0.88, 95%CI (0.71, 0.93), P=0.046], and postoperative hyperglycemia [OR=3.27, 95%CI (2.58, 5.32), P=0.009] were independent risk factors for DD. Conclusion The incidence of DD is relatively high after cardiac surgery, and low body mass index, preoperative renal insufficiency requiring dialysis, low left ventricular ejection fraction, and postoperative hyperglycemia are risk factors for DD.

Objective: To explore the therapeutic mechanism of puerarin in treating rheumatoid arthritis (RA) rats based on the serine/tyrosine protein kinase B (AKT)-phosphorylated forkhead box protein O1 (FOXO1)-interleukin-9 (AKT-FOXO1-IL-9) signaling pathway. Methods : 36 rats were randomly divided into a blank group , a model group , a positive control group , and low , medium , and high dose groups of puerarin. Except for the blank group , the other groups were induced with type Ⅱ collagen to establish a RA rat model. After successful modeling , different doses of puerarin and methotrexate were given to treat the rats. The body mass and toe thickness of the rats were measured , and biochemical indicators of rat blood rheology were detected. X-ray was used to observe changes in rat joint morphology. Safranin green staining were used to observe the pathology of rat joint tissue. ELISA was used to detect the levels of IL-9 and rheumatoid factors in rat serum , and Western blot was used to detect changes in levels of AKT and FOXO1 . 36 rats were randomly divided into a blank group , a model group , a positive control group , and low , medium , and high dose groups of puerarin. Except for the blank group , the other groups were induced with type Ⅱ collagen to establish a RA rat model. After successful modeling , different doses of puerarin and methotrexate were given to treat the rats. The body mass and toe thickness of the rats were measured , and biochemical indicators of rat blood rheology were detected. X-ray was used to observe changes in rat joint morphology. Safranin green staining were used to observe the pathology of rat joint tissue. ELISA was used to detect the levels of IL-9 and rheumatoid factors in rat serum , and Western blot was used to detect changes in levels of AKT and FOXO1 . Results: Compared with the blank group , the model group had the lowest toe thickness , and X-ray images showed more obvious segmental stenosis and more severe marginal bone invasion ; scaly like changes appeared at the edges of joints stained with safranin green , accompanied by the exudation of inflammatory cells and increased proliferation and secretion of chondrocytes ; the expression levels of inflammatory factors IL-9 and rheumatoid factors were the highest , and the expression levels of AKT and FOXO1 proteins were the highest (P < 0. 05) . Compared with the model group , the toe thickness of rats treated with different doses of puerarin decreased ; X-ray images showed that the puerarin treatment group of rats showed improvement in plantar joint stenosis and marginal bone invasion ; the results of safranin green staining showed that after treatment with different doses of puerarin , the infiltration of inflammatory cells decreased , and the expression levels of inflammatory factor IL-9 , rheumatoid factors , AKT , and FOXO1 proteins decreased significantly ( P < 0. 05 ) , with the high-dose puerarin group showing the most significant difference. Compared with the high-dose puerarin group , the positive control group showed a significant decrease in the above results and statistical differences (P < 0. 05) . Conclusion Puerarin has a good therapeutic effect on rats with RA by inhibiting the AKT-FOXO1-IL-9 pathway. The high-dose puerarin group (60 mg/kg) has the best therapeutic effect and the results show a dose-response relationship.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

Objective:To explore the clinical efficacy of the splenic vessel-oriented anatomical plane priority strategy in Da Vinci robotic Kimura distal pancreatectomy.Methods:A retrospective analysis was conducted on 26 patients who underwent robotic-assisted distal pancreatectomy at Zhejiang Provincial People’s Hospital from January 2019 to September 2024. The cohort included 7 male and 19 female patients, aged (49.3±16.7) years. Surgical outcomes, including operative time, intraoperative blood loss, postoperative complications, and hospital stay, were analyzed, and surgical techniques were summarized.Results:All 26 patients successfully completed the surgery. Pathological diagnoses included 5 cases of intraductal papillary mucinous neoplasm, 5 serous cystadenomas, 1 pancreatic neuroendocrine tumor, 6 solid pseudopapillary neoplasms, 4 mucinous cystic neoplasms, and 5 neuroendocrine tumors. The maximum tumor diameter was (2.3±1.1) cm, and the operative time was (183.2±77.4) min. The spleen preservation rate was 100% (26/26). Intraoperative blood loss was 50.0 (17.5, 125) ml, and postoperative hospital stay was (10.1±3.7) d. No Clavien-Dindo grade III or higher complications occurred. The post-operative pancreatic fistula (POPF) rate was 53.8% (14/26), including 38.5% (10/26) biochemical leak and 15.3% (4/26) grade B POPF, with no grade C POPF.Conclusion:The splenic vessel-oriented anatomical plane priority strategy in robotic-assisted spleen-preserving distal pancreatectomy (Kimura technique) is safe and feasible, significantly improving the spleen preservation rate.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

BACKGROUND: The atherogenic index of plasma (AIP) has been shown to be positively correlated with cardiovascular disease in previous studies. However, it is unclear whether elderly people with long-term high AIP levels are more likely to develop coronary heart disease (CHD). Therefore, the aim of this study was to investigate the relationship between AIP trajectory and CHD incidence in elderly people. METHODS: 19,194 participants aged ≥ 60 years who had three AIP measurements between 2018 and 2020 were included in this study. AIP was defined as log₁₀ (triglyceride/high-density lipoprotein cholesterol). The group-based trajectory model was used to identify different trajectory patterns of AIP from 2018 to 2020. Cox proportional hazards models were used to estimate the hazard ratio (HR) with 95% CI of CHD events between different trajectory groups from 2020 to 2023. RESULTS: Three different trajectory patterns were identified through group-based trajectory model: the low-level group (n = 7410, mean AIP: -0.25 to -0.17), the medium-level group (n = 9981, mean AIP: 0.02-0.08), and the high-level group (n = 1803, mean AIP: 0.38-0.42). During a mean follow-up of 2.65 years, a total of 1391 participants developed CHD. After adjusting for potential confounders, compared with the participants in the low-level group, the HR with 95% CI of the medium-level group and the high-level group were estimated to be 1.24 (1.10-1.40) and 1.43 (1.19-1.73), respectively. These findings remained consistent in subgroup analyses and sensitivity analyses. CONCLUSIONS There was a significant correlation between persistent high AIP level and increased CHD risk in the elderly. This suggests that monitoring the long-term changes in AIP is helpful to identify individuals at high CHD risk in elderly people.