Objective: To analyze the results of national external quality assessment (EQA) for transfusion compatibility test from 2018 to 2023, with the aim of providing references for improving laboratory testing quality and ensuring the safety of clinical blood transfusion. Methods: Three EQA programs were conducted annually, each distributing 22 quality assessment samples. Participating transfusion laboratories were required to complete testing within specified deadlines and to submit results along with documentation of testing methodologies, reagents, and equipment used. National Center for Clinical Laboratories (NCCL) conducted statistical analysis of laboratory results, evaluated testing outcomes and related circumstances, and provided feedback to participating laboratories. EQA data from transfusion laboratories across China from 2018 to 2023 were collected and systematically analyzed. Results: From 2018 to 2023, the qualification rates for all five items (ABO forward typing, ABO reverse typing, Rh blood group typing, antibody screening, and cross-matching) were 67.59%, 77.11%, 77.38%, 72.78%, 79.96%, and 85.16%, respectively. The mean qualification rates for ABO forward typing, ABO reverse typing, RhD blood group typing, antibody screening, and cross-matching over the past six years were 96.25%±0.59%, 90.45%±4.52%, 96.05%±0.71%, 90.88%±2.86%, and 88.34%±3.48%, respectively. The qualification rates in 2019, 2020, 2022, and 2023 all showed a stable trend of "blood stations>tertiary hospitals>secondary hospitals". The mean qualification rate of laboratories in secondary hospitals from 2018 to 2023 was significantly lower than those of laboratories in tertiary hospitals and blood stations (P<0.05), while no significant difference was observed between laboratories in tertiary hospitals and blood stations (P>0.05). The micro column agglutination method was the most widely used in all five tests. In the four test items, namely ABO forward typing, ABO reverse typing, antibody screening, and cross-matching, there was a statistically significant difference in the qualification rate of micro column agglutination method compared to other methods (P<0.05). There was a statistical difference in the qualification rate between manual and automated detection using micro column agglutination method in the cross-matching tests (P<0.05), whereas no significant difference was noted for the other test items (P>0.05). Conclusion: From 2018 to 2023, the number of laboratories participating in EQA activities has been increasing year by year, and the qualification rate has shown an overall upward trend. The type of laboratory is a key factor affecting the qualification rate, and the testing capabilities of some laboratories still need to be improved. The micro column agglutination method is widely used in transfusion compatibility tests. The established EQA program effectively monitors quality issues in laboratories, drives continuous improvement, and ensures sustained enhancement of testing standards to safeguard clinical blood safety.

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 genetic mutation characteristics of patients with bilateral macronodular adrenocortical disease（BmacAD）and to analyze the clinical phenotypes and adrenal nodule transcriptomic profiles associated with different genotypes.Methods:This retrospective study analyzed the clinical data of 37 patients diagnosed with BmacAD by clinical and pathological assessment who underwent surgery at Peking Union Medical College Hospital from January 2001 to December 2024. Data included symptoms and signs related to hypercortisolism，24-hour urinary free cortisol，plasma adrenocorticotropic hormone（ACTH），and overnight low-dose dexamethasone suppression test results. Whole-exome sequencing（WES）was performed on frozen adrenal hyperplasia tissue samples from surgical specimens and matched frozen residual blood samples for all patients to screen for germline and somatic mutations. Sanger sequencing was used to validate some of the identified mutations. The relation between genetic mutations and clinical features was analyzed. Transcriptome sequencing of the hyperplastic tissues was conducted，and unsupervised clustering，differential gene expression analysis，and pathway enrichment analysis were used to compare the transcriptomic profiles of patients with different genotypes.Results:A total of 37 cases were included（23 males and 14 females），aged between 31?68 years old. Among the patients with available clinical data，most exhibited signs of hypercortisolism，including hypertension（100.0%，36/36），diabetes（50.0%，18/36），and centripetal obesity（55.9%，19/34），accompanied by relevant endocrine abnormalities such as elevated 24-hour urinary free cortisol（79.4%，27/34），suppressed ACTH（77.8%，28/36），and a positive overnight low-dose dexamethasone suppression test（45.2%，14/31）. WES and Sanger sequencing revealed that ARMC5 gene mutations were the most common. Among the 37 patients，33（89.2%）had ARMC5 germline mutations，and 31（83.8%）concurrently harbored ARMC5 somatic mutations，including 3 cases of loss of heterozygosity. Two patients without detectable ARMC5 mutations both carried a somatic p.S45P mutation in the CTNNB1 gene and neither had typical manifestations of hypercortisolism. Transcriptome sequencing results suggested that patients with ARMC5 mutations had an upregulation of pathways related to steroid secretion.Conclusions:The majority of BmacAD patients present with typical manifestations of hypercortisolism，while a minority exhibit only mild autonomous cortisol secretion without obvious symptoms. Biallelic inactivation of the ARMC5 gene is the primary genetic driver of this disease，leading to more severe hypercortisolism by upregulating steroid hormone secretion. CTNNB1 mutations may be involved in the pathogenesis of some patients without ARMC5 mutations.

Objective:To investigate the efficacy of unilateral adrenalectomy combined with contralateral partial adrenalectomy in patients with bilateral macronodular adrenal cortical disease（BmacAD）.Methods:Retrospective analysis was performed on the clinical data of 41 patients with bilateral macronodular adrenal disease（BmacAD）who underwent unilateral total adrenalectomy plus contralateral partial adrenalectomy at Peking Union Medical College Hospital，Chinese Academy of Medical Sciences，between January 1990 and December 2018. The cohort comprised 27 men（65.9%）and 14 women（34.1%），with a mean age of（48.5 ± 9.3）years. The median disease duration was 60（25，108）months . Twenty-six patients（63.4%）presented with clinical features of Cushing’s syndrome（CS），while 15 patients（36.6%）did not exhibit typical CS symptoms. Endocrine evaluation revealed a median 24-hour urinary free cortisol（24h-UFC）level of 429.1（255.3，799.2）μg/24h. Plasma adrenocorticotropic hormone（ACTH）was normal in 5 patients（12.2%）and suppressed in 36 patients（87.8%）. Computed tomography（CT）imaging demonstrated typical multinodular involvement of both adrenal glands in all patients. The mean volume of the left adrenal gland was（57.4 ± 31.8）ml，the mean volume of the right adrenal gland was（48.8 ± 18.0）ml，and the mean total volume was（106.2 ± 42.1）ml. The mean maximum nodule diameter was（2.4 ± 1.0）cm. All 41 patients underwent unilateral total adrenalectomy plus contralateral partial adrenalectomy. Postoperatively，patients were followed up every 3 to 6 months to monitor symptoms and hormonal changes. Residual adrenalectomy was performed if symptoms or hormone levels did not improve or recurred.Results:Of the 41 patients，2 underwent simultaneous unilateral total adrenalectomy plus contralateral partial adrenalectomy，while 39 underwent staged procedures. The median follow-up was 56 months（range 2 to 199 months）. During the follow-up period，82.9%（34/41）of patients achieved normalization of clinical symptoms and biochemical markers postoperatively. The median time to improvement of CS symptoms was 19 months. The median 24h-UFC level at 1 week postoperatively was 385.48（219.95，525.04）μg/24h，decreasing to 56.96（37.38，88.70）μg/24h at 3 months postoperatively. All 41 patients received routine glucocorticoid supplementation postoperatively，with gradual tapering until discontinuation. The median duration of hormone replacement was 29 months（3，72）months. Among the 34 patients who did not experience recurrence，30（88.2%）were eventually able to discontinue hormone replacement，with a median duration of supplementation of 24（3，36）months，while 4（11.8%）required long-term hormone replacement. The final outcome showed that 73.2%（30/41）of patients achieved control of CS symptoms with preservation of normal adrenal function following unilateral total adrenalectomy plus contralateral partial adrenalectomy. Seven patients（17.1%）required completion adrenalectomy for residual disease. There were no statistically significant differences（ P > 0.05）in preoperative clinical symptoms，hormone levels，adrenal gland volume，or maximum nodule diameter between patients who experienced recurrence after unilateral total adrenalectomy plus contralateral partial adrenalectomy and those who did not. Conclusions:Unilateral adrenalectomy with contralateral partial adrenalectomy represents a feasible treatment strategy for BmacAD，but requires careful patient selection. This approach may offer a balance between therapeutic efficacy and preservation of adrenal function，providing a novel perspective for clinical decision-making.

Objective:To screen the risk factors for non-complete procedural success of transvenous lead extraction(TLE),and to establish a prediction model based on the results and evaluate its predictive efficacy.Methods:A total of 1 029 patients who underwent TLE in Peking University People's Hospital from January 2014 to December 2020 were enrolled and divided into training set(n=720)and validation set(n=309)using the random number method.There were no statistically significant differences among the variables in the training set and the validation set.The training set was divided into the complete procedural success(CPS)group(n=664)and the non-CPS group(n=56).Univariate analysis was employed to screen the relevant indicators of non-CPS,followed by binary logistic regression analysis to identify the independent risk factors of non-CPS.Subsequently,a predictive model and nomogram were constructed.The receiver operating characteristic(ROC)curve analysis was applied to evaluate the ability of the model to distinguish non-CPS from TLE patients in the training set and validation set.The Hosmer-Lemeshow goodness-of-fit test was used to assess the consistency between the predicted risk and the actual risk of the model.Results:Univariate analysis showed that the relevant variables with P<0.1 including the age at the first implantation of the lead,the number of leads extracted,the oldest dwell time of lead extracted,the presence of abandoned leads,non-manual traction for lead extracted,the number of extracted leads>3,bilateral lead implantation,and the indications for TLE.The binary logistic regression analysis revealed that the presence of abandoned leads(OR=2.252,95%CI:1.111-4.564,P=0.024),the oldest dwell time of the extracted leads(OR=1.009,95%CI:1.005-1.012,P<0.001),and the number of extracted leads>3(OR=3.177,95%CI:1.306-7.733,P=0.011)were independent risk factors for non-CPS of TLE.ROC curve analysis revealed that the area under the ROC curve(AUC)of the training set was 0.80(95%CI:0.75-0.85,P<0.001).The AUC of the validation set was 0.81(95%CI:0.72-0.90,P<0.001).The Hosmer-Lemeshow goodness-of-fit test indicated that the P values of both the training set(P=0.089)and the validation set(P=0.136)were greater than 0.05.Conclusions:The presence of abandoned leads,the oldest dwell time of lead extracted,and the number of extracted leads>3 are independent risk factors for non-CPS in patients undergoing TLE.The nomogram model based on the above factors has satisfactory predictive ability.

Objective:To analyze the results of national external quality assessment (EQA) for transfusion compatibility test in 2023, and provide reference for quality management of clinical transfusion compatibility testing.Methods:The EQA of clinical transfusion compatibility testing by NCCL was performed 3 times in 2023 among included laboratories. The panel consisting of 22 samples was distributed to 4 186 laboratories across 31 provinces (Including 2 961 tertiary hospital laboratories, 1 085 secondary hospital laboratories, 23 primary hospital laboratories, 106 blood station laboratories and 11 independent clinical laboratories). Each panel contains 11 red blood cell and 11 plasma samples per 1.5 ml/tube. Each participant laboratory of the EQA program was required to carry out the detection and return results in expected time. Statistical analysis and evaluation on the reported results were conducted by NCCL from the aspects of regional distribution, laboratory grading, testing methodology, reagent and testing system usage.Results:The qualification rates of EQA for five items including ABO positive typing, ABO reverse typing, RhD blood type, antibody screening, and cross matching were 96.68%, 95.10%, 96.46%, 95.32%, and 91.04%, respectively. The EQA qualification rate of tertiary hospital laboratories was 87.77% (2 599/2 961), which was significantly higher than the 77.79% (844/1 085) of secondary hospital laboratories. There were significant differences in the qualification rate of participating laboratories among different regions. The utilization rates of micro column agglutination method in ABO positive typing, ABO reverse typing, RhD blood type, antibody screening, and cross matching were 80.81% (10 080/12 474), 75.06% (9 337/12 440), 81.38% (10 118/12 433), 89.59% (11 104/12 394) and 76.25% (9 495/12 453), respectively. The qualification rate of micro column agglutination method was significantly higher than that of saline slide method in ABO positive typing detection ( P<0.05). The qualification rate of micro column agglutination method was significantly higher than that of the polyamine method and anti-human globulin test tube method in antibody screening ( P<0.05). There were statistically significant differences in qualification rate of 7 reagents in ABO reverse typing, antibody screening and cross matching ( P<0.05). There was no statistically significant difference in the qualification rate between the two detection systems for other reagents, except for the ABO reverse typing where the qualification rate of reagent 1 in a single system was higher than that in a mixed system ( P<0.05). Conclusion:The testing capabilities of clinical laboratories in different regions and different type varied significantly in China. Micro column agglutination method was the most popular selection in transfusion compatibility testing. The regents used in these laboratories showed good performance. However, the detection efficiency of some reagents still need to be improved. EQA could be used to evaluate, monitor, and improve the quality of testing.

The armadillo repeat containing 5 (ARMC5) gene is part of a family of protein-coding genes that are rich in armadillo repeat sequences, are ubiquitously present in eukaryotes, and mediate interactions between proteins, playing roles in various cellular processes. Current research has demonstrated that reduced expression or absence of the ARMC5 gene in various tumor tissues can lead to uncontrolled cell proliferation, thereby inducing a range of diseases. The ARMC5 gene was initially extensively studied in the context of bilateral macronodular adrenocortical disease (BMAD), with harmful pathogenic variants in ARMC5 identified in approximately 50% of BMAD patients. With advancing research, scientists have discovered that ARMC5 pathogenic variants may also have potential effects on other diseases and could be associated with increased susceptibility to certain cancers. This review aims to present the latest research progress on how the ARMC5 gene plays its role in tumors. It outlines the basic structure of ARMC5 and the regions where it functions, as well as the diseases currently proven to be associated with ARMC5. Moreover, some evidence suggests its relation to embryonic development and the regulation of immune system activity. In conclusion, the ARMC5 gene is a crucial focal point in genetic and medical research. Understanding its function and regulation is of great importance for the development of new therapeutic strategies related to diseases associated with its pathogenic variants.
Humans ; Neoplasms/genetics* ; Armadillo Domain Proteins/genetics* ; Animals ; Genetic Predisposition to Disease ; Cytoskeletal Proteins/genetics* ; Tumor Suppressor Proteins/genetics*

Objective To analyze the risk factors for catheter-related thrombosis(CRT)in the upper arm infusion port(UAP)and to construct a machine-learning prediction model.Methods A total of 6028 patients,who received UAP implantation at Shanghai Renji Hospital of China from February 2014 to February 2023,were enrolled in this study.The patients were divided into training set(n=4 219)and validation set(n=1 809).Six machine-learning prediction models,including Least Absolute Shrinkage and Selection Operator(LASSO)regression,random forest,decision tree,neural network,XGBoost and logistic,were constructed,and the model having best performance was selected as the optimal model.SHapely Additive exPlanations(SHAP)analysis was used to explain the neural network model,and DALEXtra package was used to explain the continuous variables.Results The neural network model was chosen as the final model.The variables,in order of the degree of importance from high to low,included sex,the diameter of catheter,catheter tip confirmation method,the length of catheter,inpatient or outpatient status,history of central venous catheter implantation,the length of subcutaneous tunnel,age,body mass index(BMI),primary tip displacement,and left or right venous approach.The learning curve,i.e.the area under curve(AUC)of the receiver operating characteristic(ROC)curve,for the training set was＞0.6,and the Delong testing and Bootstrap Methods Test showed that the neural network model performed well(P＜0.05).The Kolmogorov-Smirnov plot(KS plot)value was 0.313 5,indicating that the model had the good ability of discrimination.The clinical impact curve(CIC)assessment revealed that the model had good clinical value.Conclusion The machine-learning prediction model of upper arm infusion port with CRT has been successfully constructed.For minimizing the risk of CRT,it is recommended to prioritize the use of 5 F diameter catheters,adopt left-sided venous approach and positioning the tip of the catheter based on anatomical measurements,besides,the catheter length should be not shorter than 36.56 cm,and the subcutaneous tunnel length should not be less than 5 cm.The basic features associated with higher CRT risk include age of 50-65 years,BMI being between 18.69 kg/m2 and 20.81 kg/m2 or between 23.68 kg/m2 and 23.94 kg/m2 and male.

Objective To explore the clinical value of three-dimensional(3D)fracture mapping in improving the consistency of Arbeitsgemeinschaft für Osteosynthesefragen(AO)/the Orthopaedic Trauma Association(OTA)classification and optimizing preoperative surgical planning for Pilon fractures.Methods This single-center retrospective cohort study included 60 Pilon fracture patients admitted to the Trauma Emergency Center of the Third Hospital of Hebei Medical University between January 2022 and December 2024.All patients underwent preoperative computed tomography(CT)scans.Image standardization and expert manual segmentation/annotation of fracture lines and fragments were performed with 3D Slicer software.3D fracture lines extracted from gold-standard models were registered to a unified standard tibial model.A 3D probability heatmap was constructed by counting spatial fracture frequency,with high-incidence zones analyzed via spatial clustering algorithms.Three orthopedic surgeons independently completed AO/OTA classification and preoperative planning with the assistance of conventional CT only and CT with 3D fracture mapping.Accuracy,time consumption,inter-observer consistency(Cohen's κ),planning time,plan modification frequency,and subjective scores were evaluated.Results The 3D fracture heatmap revealed that fracture lines predominantly concentrated in the anterolateral and posteromedial regions of the distal tibia,with an average of(4.2±1.1)hotspots,a coverage rate of(78.3±5.6)%,and(3.5±1.0)clustering areas.With 3D fracture mapping assistance,classification accuracy was improved to(88.0±5.0)%compared to(75.0±8.0)%with conventional CT(P=0.001);classification time reduced to(10.4±2.5)min from(15.2±3.1)min(P<0.001);and Cohen's κ increased from 0.68±0.05 to 0.82±0.03(P=0.002).For preoperative planning,the average planning time was(15.8±3.2)min in the 3D mapping-assisted group,which was significantly shorter than that of conventional CT group(22.5±4.3)min(P<0.001);the number of plan modifications was(1.5±0.7)times,lower than that of conventional CT group(3.2±1.1)times(P<0.001),and the subjective score was 8.9±0.9,higher than that of conventional CT group(6.8±1.2)(P<0.001).Conclusion The 3D fracture mapping accurately characterizes spatial distribution patterns of Pilon fractures,significantly improves classification accuracy,inter-observer consistency,and preoperative planning efficiency,and thus holds substantial clinical value.

Purpose To explore the value of the clinical radiomics nomogram based on ultrasound in evaluating the degree of fibrosis in chronic kidney disease(CKD).Materials and Methods This retrospective study included 350 patients with CKD in Nanchong Central Hospital from January 2014 to July 2022 who underwent renal biopsy.The patients were categorized by the tubule atrophy with interstitial fibrosis(TA/IF)and divided into a training cohort(n=245)and test cohort(n=105).The patient demographics were evaluated to establish a clinical prediction model.The XGBoost machine learning model was constructed by extracting the radiomics features from the ultrasound images.The clinical radiomics nomogram prediction model was constructed by combining the radiomics score(Rad score)and important clinical features.The diagnostic performance of the three models was evaluated using receiver operating characteristic curve analysis.Results Among the 350 patients with CKD,226 had TA/IF 0 and 124 had TA/IF 1.Based on the clinical characteristics and Rad score,the clinical radiomics nomogram prediction model had the highest area under the curve in the training and testing cohorts,with the area under the curve of 0.938(95%CI 0.909-0.969)and 0.933(95%CI 0.891-0.980),respectively.Conclusion The ultrasound-based radiomics prediction model has potential value for the noninvasive diagnosis of TA/IF in CKD.Nomogram prediction models based on renal Rad scores and clinic may help clinicians to manage patients.