The Consolidated Standards of Reporting Trials (CONSORT) statement aims to enhance the quality of reporting for randomized controlled trial (RCT) by providing a minimum item checklist. It was first published in 1996, and updated in 2001 and 2010, respectively. The latest version was released in April 2025, continuously reflecting new evidence, methodological advancements, and user feedback. CONSORT 2025 includes 30 essential checklist items and a template for a participant flow diagram. The main changes to the checklist include the addition of 7 items, revision of 3 items, and deletion of 1 item, as well as the integration of multiple key extensions. This article provides a comprehensive interpretation of the statement, aiming to help clinical trial staff, journal editors, and reviewers fully understand the essence of CONSORT 2025, correctly apply it in writing RCT reports and evaluating RCT quality, and provide guidance for conducting high-level RCT research in China.

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

Objective:To investigate the risk factors for patients with hypertriglyceridemia-related acute pancreatitis (HTG-AP) developing into severe acute pancreatitis or experiencing organ failure.Methods:This retrospective cohort study collected clinical data from 2 429 patients diagnosed with acute pancreatitis from five hospitals in China between January 2019 and December 2023 using a pre-designed data collection form. The cohort included 1 516 males and 913 females,with an age of (50.2±16.5)years(range: 11 to 99 years). Among them,353 patients (16.1%) had HTG-AP,while 1 846 (83.9%) had non-HTG-AP. HTG-AP was defined as serum triglyceride levels>500 mg/dl with other etiologies excluded. Intergroup comparisons were performed using t-tests,Mann-Whitney U test or χ2 tests,respectively. Univariate and multivariate logistic regression analyses were conducted to assess risk factors for severe acute pancreatitis after adjusting for potential confounders,and a predictive model was developed and validated. Results:Compared with other etiologies,HTG-AP patients had a higher risk of progressing to SAP ( OR=1.415,95% CI: 0.866 to 2.312, P=0.017) and organ failure ( OR=1.256,95% CI: 1.015 to 1.554, P=0.036). Among HTG-AP patients,risk factors for SAP included body mass index ( OR=1.856,95% CI: 1.742 to 1.987, P=0.033),fasting blood glucose ( OR=1.128,95% CI: 1.036 to 1.229, P=0.006),white blood cell count( OR=1.162,95% CI: 1.055 to 1.281, P=0.002),and the presence of pleural effusion ( OR=13.151,95% CI: 4.330 to 19.946, P<0.01). A nomogram prediction model for SAP in HTG-AP was constructed based on these risk factors,demonstrating good discriminative ability with area under the curve values of 0.877 in the training set and 0.894 in the validation set,along with satisfactory calibration. Conclusions:HTG-AP patients are at higher risk of developing SAP and organ failure. The risk prediction model incorporating body mass index,fasting blood glucose,white blood cell count,and pleural effusion shows good predictive value for SAP.

Objective:To examine the current diagnostic and treatment practices, as well as surgical outcomes, for individuals over the age of 60 diagnosed with acute aortic arch dissection(ATAAD)at Tianjin University Chest Hospital.This analysis evaluates the safety and feasibility of performing open surgical procedures on elderly patients affected by aortic dissection.Methods:A retrospective analysis was conducted on 509 patients diagnosed with ATAAD who were registered in the Chest Pain Center data reporting platform(https: //datacs.chinacpc.org/)at Tianjin Chest Hospital, covering the period from June 2015 to December 2021.The patients were divided into two groups: the elderly group, consisting of individuals aged 60 years or older, and the non-elderly group, comprising those under 60 years of age.Their surgical conditions and short-term outcomes were subsequently examined and compared.Results:A total of 509 patients were included, 311 cases(61.1%)were identified within the non-elderly group, with a mean age of 45.78 ± 8.96 years(range: 21-59 years).In contrast, 198 cases(38.9%)belonged to the elderly group, with a mean age of 65.61 ± 4.13 years(range: 60-81 years).A total of 416 patients(81.7%)received surgical intervention.Among those who underwent surgery, the elderly group exhibited a significantly higher proportion of females(38.1% vs.20.6%, P<0.001), and these patients had smaller body surface areas and lower body mass index values.Furthermore, a greater number of elderly patients presented with comorbid conditions such as hypertension, coronary artery disease, chronic obstructive pulmonary disease, and stroke(all P<0.05).The 30-day all-cause mortality rate, incidence of cerebral infarction, and rate of continuous renal replacement therapy(CRRT)utilization were similar in both groups(20.9% vs.18.8%、15.1% vs.10.5%、19.4% vs.18.1%, all P>0.05).However, elderly patients experienced longer postoperative recovery durations, extended periods of ventilator dependency, and a higher incidence of new-onset atrial fibrillation following surgery(all P<0.05). Conclusions:The surgical rate for elderly patients with ATAAD is low, suggesting that there is significant potential for improvement in clinical diagnosis and treatment.Advanced age should not be viewed as a contraindication for surgery; rather, appropriate case selection and personalized treatment plans can enhance the success rate of surgical interventions.

Meat food is an important part of people's dietary supplements,but in recent years,meat adulteration cases are hidden and frequent,which seriously affects people's health and destroys the fairness of the market.Based on this,this paper analyses the development trend of meat adulteration and the current meat adulteration detection technology is summarized,combed in detail the use of the most widely used real-time fluorescence quantitative PCR technology application of the status quo and challenges to help real-time fluorescence quantitative PCR technology testing in meat adulteration evidence testing to the direction of more high detection efficiency and higher accuracy development.

Objective:To examine the current diagnostic and treatment practices, as well as surgical outcomes, for individuals over the age of 60 diagnosed with acute aortic arch dissection(ATAAD)at Tianjin University Chest Hospital.This analysis evaluates the safety and feasibility of performing open surgical procedures on elderly patients affected by aortic dissection.Methods:A retrospective analysis was conducted on 509 patients diagnosed with ATAAD who were registered in the Chest Pain Center data reporting platform(https: //datacs.chinacpc.org/)at Tianjin Chest Hospital, covering the period from June 2015 to December 2021.The patients were divided into two groups: the elderly group, consisting of individuals aged 60 years or older, and the non-elderly group, comprising those under 60 years of age.Their surgical conditions and short-term outcomes were subsequently examined and compared.Results:A total of 509 patients were included, 311 cases(61.1%)were identified within the non-elderly group, with a mean age of 45.78 ± 8.96 years(range: 21-59 years).In contrast, 198 cases(38.9%)belonged to the elderly group, with a mean age of 65.61 ± 4.13 years(range: 60-81 years).A total of 416 patients(81.7%)received surgical intervention.Among those who underwent surgery, the elderly group exhibited a significantly higher proportion of females(38.1% vs.20.6%, P<0.001), and these patients had smaller body surface areas and lower body mass index values.Furthermore, a greater number of elderly patients presented with comorbid conditions such as hypertension, coronary artery disease, chronic obstructive pulmonary disease, and stroke(all P<0.05).The 30-day all-cause mortality rate, incidence of cerebral infarction, and rate of continuous renal replacement therapy(CRRT)utilization were similar in both groups(20.9% vs.18.8%、15.1% vs.10.5%、19.4% vs.18.1%, all P>0.05).However, elderly patients experienced longer postoperative recovery durations, extended periods of ventilator dependency, and a higher incidence of new-onset atrial fibrillation following surgery(all P<0.05). Conclusions:The surgical rate for elderly patients with ATAAD is low, suggesting that there is significant potential for improvement in clinical diagnosis and treatment.Advanced age should not be viewed as a contraindication for surgery; rather, appropriate case selection and personalized treatment plans can enhance the success rate of surgical interventions.

Meat food is an important part of people's dietary supplements,but in recent years,meat adulteration cases are hidden and frequent,which seriously affects people's health and destroys the fairness of the market.Based on this,this paper analyses the development trend of meat adulteration and the current meat adulteration detection technology is summarized,combed in detail the use of the most widely used real-time fluorescence quantitative PCR technology application of the status quo and challenges to help real-time fluorescence quantitative PCR technology testing in meat adulteration evidence testing to the direction of more high detection efficiency and higher accuracy development.

Objective:To investigate the risk factors for patients with hypertriglyceridemia-related acute pancreatitis (HTG-AP) developing into severe acute pancreatitis or experiencing organ failure.Methods:This retrospective cohort study collected clinical data from 2 429 patients diagnosed with acute pancreatitis from five hospitals in China between January 2019 and December 2023 using a pre-designed data collection form. The cohort included 1 516 males and 913 females,with an age of (50.2±16.5)years(range: 11 to 99 years). Among them,353 patients (16.1%) had HTG-AP,while 1 846 (83.9%) had non-HTG-AP. HTG-AP was defined as serum triglyceride levels>500 mg/dl with other etiologies excluded. Intergroup comparisons were performed using t-tests,Mann-Whitney U test or χ2 tests,respectively. Univariate and multivariate logistic regression analyses were conducted to assess risk factors for severe acute pancreatitis after adjusting for potential confounders,and a predictive model was developed and validated. Results:Compared with other etiologies,HTG-AP patients had a higher risk of progressing to SAP ( OR=1.415,95% CI: 0.866 to 2.312, P=0.017) and organ failure ( OR=1.256,95% CI: 1.015 to 1.554, P=0.036). Among HTG-AP patients,risk factors for SAP included body mass index ( OR=1.856,95% CI: 1.742 to 1.987, P=0.033),fasting blood glucose ( OR=1.128,95% CI: 1.036 to 1.229, P=0.006),white blood cell count( OR=1.162,95% CI: 1.055 to 1.281, P=0.002),and the presence of pleural effusion ( OR=13.151,95% CI: 4.330 to 19.946, P<0.01). A nomogram prediction model for SAP in HTG-AP was constructed based on these risk factors,demonstrating good discriminative ability with area under the curve values of 0.877 in the training set and 0.894 in the validation set,along with satisfactory calibration. Conclusions:HTG-AP patients are at higher risk of developing SAP and organ failure. The risk prediction model incorporating body mass index,fasting blood glucose,white blood cell count,and pleural effusion shows good predictive value for SAP.

Objective To investigate the efficacy of low-dose inhaled nitric oxide (iNO) in the treatment of severe hypoxemia after Sun’s operation. Methods The clinical data of patients undergoing Sun’s operation for acute Type A aortic dissection in our hospital from January 2020 to June 2022 were retrospectively analyzed. Patients who received conventional treatment before November 2021 were enrolled as a control group. After November 2021, iNO was used in our hospital, and the patients who received iNO as an iNO group. The preoperative clinical baseline data, perioperative clinical data and oxygenation index were compared between the two groups. Results A total of 54 patients were included in the control group, including 45 males and 9 females, with an average age of 53.0±10.9 years. A total of 27 patients were included in the iNO group, including 21 males and 6 females, with an average age of 52.0±10.6 years. The preoperative body mass index of the two groups was greater than 25 kg/m2, white blood cell count, C-reactive protein were significantly higher than normal level, but there was no statistical difference between the groups (P＞0.05). There were no statistical differences in intraoperative data between the two groups (P＞0.05). The iNO group had significantly shorter duration of mechanical ventilation, postoperative ICU stay, and postoperative hospital stay than the control group (P<0.001). After 12 h of iNO treatment, hypoxic condition improved obviously, oxygenation indices in 12 h, 24 h, 36 h,48 h, 60 h and 72 h in the iNO group were significantly higher than those in the control group (P<0.05). Conclusion The treatment of severe hypoxemia after Sun’s surgery with low-dose of iNO is safe and effective, can significantly improve oxygenation function, and has significant advantages in shortening ventilator use time, postoperative ICU stay and postoperative hospital stay, but it is not significant in changing postoperative mortality.

Objective:Using different machine learning methods to construct and screen the best prediction model for predicting the risk of death within 30 days after surgery in patients with acute type A aortic dissection.Methods:Five hundred and twenty-one patients with acute type A aortic dissection who underwent surgery between 2015 and 2022 were included, after collecting their perioperative date and screening them, 329 patients were retained. two different groups of predictor variables were generated by using Lasso regression and principal component analysis, after that, logistic regression, support vector machine algorithm, random forest algorithm, gradient boosting algorithm, and super learning algorithm were used to develop prediction models for the risk of death within 30 days after surgery. Finally, we compare the models and select the best one. Results:The AUC values for all models rangrd from 0.791-0.959. The model using Lasso regression to determine the predictor variables and built by the super learning algorithm had the best prediction with an AUC value of 0.959. Conclusion:The super learning algorithm better than other algorithms in predicting death within 30 days after acute type A aortic dissection.