OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

ObjectiveTo explore the value of a multimodal MRI-based radiomics nomogram for differentiating human epidermal growth factor receptor-2 （HER-2） negative breast cancer molecular subtypes.MethodsA retrospective analysis was conducted on 190 patients with HER-2 negative breast cancer who underwent multimodal MRI examination， and the patients were divided into two molecular subtype groups： a HER-2 low expression group （n=108） and a HER-2 zero expression group （n=82）. The cases were randomly stratified and sampled at a ratio of 7∶3 and divided into a training set of 133 cases and a testing set of 57 cases. The clinical and radiological features of the patients were collected， the radiomics features based on T2-weighted imaging （T2WI）， diffusion-weighted imaging （DWI）， and dynamic contrast-enhanced （DCE）-MRI were extracted， and the clinical-radiological model， unimodal radiomics model， multimodal radiomics model， and combined model were constructed respectively. Then the nomogram combined multimodal radiomics signature （radsocre） with clinical-radiological features was used to construct a visualized predictive model， and the area under the curve （AUC） was used to compare the effectiveness of different models in distinguishing HER-2 low expression and zero expression subtypes.ResultsA significant difference in radscore was demonstrated between the HER-2 low and HER-2 zero expression groups in both the training （P<0.000 1） and testing sets （P<0.01）. The AUC of the multimodal radiomics model in the training set and the testing set were 0.914 and 0.836， respectively， which was superior to any unimodal radiomics model. The nomogram demonstrated great diagnostic efficacy （AUC=0.930 in training set； AUC=0.865 in testing set）.ConclusionA multimodal MRI-based nomogram incorporating radsocre and clinical-radiological features can accurately distinguish the subtypes of HER-2 negative breast cancer.

Intelligent prescription recommendation has become an important research direction in traditional Chinese medicine (TCM), offering new opportunities to support clinical decision-making and promote the modernization of TCM practice. With the rapid development of artificial intelligence (AI), a variety of computational approaches have been proposed to learn prescription patterns from clinical data and generate personalized treatment recommendations. However, despite increasing research activity, systematic and comprehensive reviews of AI-driven methods for TCM prescription recommendation remain limited. In this study, we present a comprehensive review of computational approaches for herbal prescription recommendation (HPR) in TCM. Existing methods are systematically categorized into several major paradigms, including traditional machine learning methods, topic model methods, sequential generative methods, deep learning and graph-based methods, and large language model–based frameworks. In addition to summarizing methodological developments, we also review commonly used public datasets and evaluation metrics in this field. Furthermore, representative models with publicly available implementations are experimentally evaluated on multiple benchmark datasets to provide a comparative analysis of their performance on the HPR task. Finally, we discuss the key challenges that hinder the practical deployment of intelligent prescription recommendation systems, including data heterogeneity, limited interpretability, and insufficient integration of TCM domain knowledge. Future research directions are outlined to facilitate the development of more reliable, interpretable, and clinically applicable AI-assisted HPR systems for TCM.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

This article introduces the clinical experience of Professor WANG Jihong in treatment of post-stroke hypermyotonia with Lai's tongyuan therapy (therapy for removing obstruction and consolidating vital essence). Regarding the pathogenesis of this disease, Professor WANG Jihong emphasizes a "trinity" approach, "the mind disturbed, qi and blood unbalanced, and yuan (vital essence) not consolidated". In treatment, "the unblocking, conducting and nourishing are taken as the fundamental" to "prevent from over-dredging, balancing yin and yang, and avoiding over-replenishing". In clinical practice, the combined measure is adopted with acupuncture, tuina and herbal medicine. In acupuncture, the acupoints are selected according to the front-back combination of the points of the conception vessel and the governor vessel (basic prescription: Yintang [GV24⁺], Baihui [GV20] and Niesanzhen; prescription for promoting the governor vessel: Dazhui (GV14), Jinsuo [GV8], Xinshu [BL15], Pishu [BL20] and etc.; and the prescription for consolidating the vital essence: Danzhong (CV17), Zhongwan [CV12], Tianshu [ST25], Qihai [CV6]) and etc., as well as those on the four limbs for "opening, closing and pivoting of yin and yang" (on the upper limbs of the affected side: Jiquan [HT1], Jianyu [LI15], Quchi [LI11], Quze [PC3] and etc.; on the lower limbs of the affected side: Huantiao [GB30], Liangqiu [ST34], Xuehai [SP10], Yanglingquan [GB34]) and etc. The above points co-act on regulating the conception vessel and the governor vessel, and balancing yin and yang. Tuina is delivered on the governor vessel, the bladder meridian of foot-taiyang and wind points on the area between the head and nape, so as to promote the governor vessel, benefit the orifices, strengthen the spine and relax tendons. Herbal medicine works on nourishing the liver to soften tendons, nourishing blood to remove wind, regulating qi to replenish the spleen, consolidating the root to cultivate the vital essence, activating blood circulation to unblock meridians, and removing stasis to resolve phlegm. Tongyuan therapy provides a certain instruction in treatment of post-stroke hypermyotonia.
Humans ; Acupuncture Therapy ; Acupuncture Points ; Stroke/complications* ; Male ; Female ; Middle Aged ; Aged ; Drugs, Chinese Herbal ; Adult

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 compare the effectiveness of early versus delayed closed reduction and percutaneous Kirschner wire fixation in the treatment of pediatric supracondylar humerus fractures. METHODS: A retrospective analysis was conducted on 468 children with supracondylar humerus fractures, who were admitted between January 2020 and December 2023 and met the inclusion criteria. Among them, 187 children were treated during 12 hours after injury (early operation group) and 281 were treated after 12 hours (delayed operation group). There was no significant difference between the two groups ( P>0.05) in the gender, age, injury mechanism, fracture side and type, while there was significant difference in interval from injury to operation ( P<0.05). The operative outcomes, including the operation time, intraoperative blood loss, the length of hospital stay, fracture healing time, elbow function assessed by Flynn criteria at 3 months after operation, and complications, were compared. RESULTS: Compared to the delayed operation group, the early operation group demonstrated significantly shorter operation time and less intraoperative blood loss ( P<0.05). There was no significant difference in the length of hospital stay between the two groups ( P>0.05). All children were followed up 3-12 months. The follow-up time was (6.7±2.9) months in the early operation group and (6.9±2.8) months in the delayed operation group, showing no significant difference between the two groups ( P>0.05). There was no significant difference in the fracture healing time between the two groups ( P>0.05). At 3 months after operation, the early operation group exhibited superior Flynn elbow functional outcomes to the delayed operation group ( P<0.05). In the early operation group, there was 1 case of fracture non-union and 3 cases of cubital varus deformity after operation. In the delayed operation group, there was 1 case of nerve injury, 7 cases of fracture non-union, and 12 cases of cubital varus deformity after operation. There was significant difference in the incidence of complications between the two groups ( P<0.05). One case of the early operation group and 10 cases of the delayed operation group underwent secondary operation, showing no significant difference in the incidence of secondary operation between the two groups ( P>0.05). CONCLUSION For pediatric supracondylar humerus fractures, early closed reduction and percutaneous Kirschner wire fixation can reduce operation time, minimize intraoperative blood loss and postoperative complications, and improve the functional recovery compared to delayed operation.
Humans ; Humeral Fractures/surgery* ; Bone Wires ; Retrospective Studies ; Male ; Female ; Child ; Fracture Fixation, Internal/instrumentation* ; Child, Preschool ; Treatment Outcome ; Operative Time ; Fracture Healing ; Length of Stay ; Closed Fracture Reduction/methods* ; Blood Loss, Surgical ; Time Factors ; Time-to-Treatment ; Postoperative Complications/epidemiology*

In recent years, with the development of big data application technology, the real-world data and the corresponding generated real-world evidence have attracted the attention of healthcare regulatory authorities around the world. Regulators recognize that real-world research with specific purposes using real-world data can provide important evidence for regulatory decisions. A total of 90 instances of publicly released on the application of real-world evidence to support regulatory decisions of U. S. Food and Drug Administration are explored, and the positioning and value of real-world evidence in U. S. Food and Drug Administration regulatory decisions are summarized and analyzed, providing references for the use of real-world data and real-world evidence to promote medical devices whole cycle regulation in China.
United States ; United States Food and Drug Administration ; Equipment and Supplies ; Device Approval ; China

Objective To investigate the independent risk factors affecting the prognosis of chronic active antibody-mediated rejection (caAMR) after kidney transplantation. Methods A retrospective analysis was conducted on 61 patients who underwent renal biopsy and were diagnosed with caAMR. The patients were divided into caAMR group (n=41) and caAMR+TCMR group (n=20) based on the presence or absence of concurrent acute T cell-mediated rejection (TCMR). The patients were followed up for 3 years. The value of 24-hour urinary protein and estimated glomerular filtration rate (eGFR) at the time of biopsy in predicting graft loss was assessed using receiver operating characteristic (ROC) curves. The independent risk factors affecting caAMR prognosis were analyzed using the LASSO-Cox regression model. The correlation between grouping, outcomes, and Banff scores was compared using Spearman rank correlation matrix analysis. Kaplan-Meier analysis was used to evaluate the renal allograft survival rates of each subgroup. Results The 3-year renal allograft survival rates for the caAMR group and the caAMR+TCMR group were 83% and 79%, respectively. The area under the ROC curve (AUC) for predicting 3-year renal allograft loss was 0.83 ［95% confidence interval (CI) 0.70-0.97］ for eGFR and 0.78 (95% CI 0.61-0.96) for 24-hour urinary protein at the time of biopsy. LASSO-Cox regression analysis and Kaplan-Meier analysis showed that eGFR≤25.23 mL/(min·1.73 m²) and the presence of donor-specific antibody (DSA) against human leukocyte antigen (HLA) class I might be independent risk factors affecting renal allograft prognosis, with hazard ratios of 7.67 (95% CI 2.18-27.02) and 5.13 (95% CI 1.33-19.80), respectively. A strong correlation was found between the Banff chronic lesion indicators of renal interstitial fibrosis and tubular atrophy (P<0.05). Conclusions The presence of HLA class I DSA and eGFR≤25.23 mL/(min·1.73 m²) at the time of biopsy may be independent risk factors affecting the prognosis of caAMR.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.