Objective: To evaluate the effect of community comprehensive management model intervention among patients with dyslipidemia, so as to provide the reference for optimizing community management strategies and improving the target achievement rate for blood lipids among this population. Methods: From May to June 2023, a multi-stage stratified random sampling method was employed to select patients with dyslipidemia from primary healthcare institutions in Jiaxing City, Zhejiang Province. Eligible participants were randomly assigned to either a control group or an intervention group. The control group received routine management, while the intervention group was subjected to a community comprehensive management model in addition to the routine care. Both groups were followed up for 24 months. Data on demographic characteristics, lifestyle behaviors, physical examination indices, and blood biochemical indicators were collected at baseline and after the intervention through questionnaires, physical examinations, and laboratory tests. Changes in obesity rate, central obesity rate, target achievement rates for blood lipids, blood pressure, and blood glucose, as well as lifestyle modifications, were analyzed. Differences between the two groups before and after the intervention were assessed using generalized estimating equations (GEE). Results: The control group consisted of 560 patients, including 303 females (54.11%) and 430 individuals aged ≥65 years (76.79%). The intervention group also included 560 patients, with 300 females (53.57%) and 431 individuals aged ≥65 years (76.96%). Before the intervention, no statistically significant differences were observed between the two groups in terms of gender, age, educational level, history of chronic diseases, and atherosclerotic cardiovascular disease risk stratification (all P>0.05). After 24 months of intervention, interaction effects between group and time were observed for obesity rate, central obesity rate, target achievement rate for blood lipids, target achievement rate for blood glucose, composite target achievement rate, physical activity rate, and medication adherence (all P<0.05). Specifically, the intervention group demonstrated lower rates of obesity and central obesity, and higher target achievement rate of blood lipids, target achievement rate of blood glucose, composite target achievement rate, physical activity rate, and medication adherence compared to the control group. Conclusion The community comprehensive management model contributed to improvements in multiple metabolic parameters (including body weight, waist circumference, blood lipids, and blood glucose) among patients with dyslipidemia, and was associated with increased physical activity rate and medication adherence.

Background: Diabetic macrovascular and microvascular complications often coexist and may share similar risk factors and pathological pathways. We aimed to investigate whether 10-year atherosclerotic cardiovascular disease (ASCVD) risk, which is commonly assessed in diabetes management, can predict incident diabetic nephropathy (DN) and retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM). Methods: This prospective cohort study enrolled 2,891 patients with clinically diagnosed T2DM who were free of ASCVD, nephropathy, or retinopathy at baseline in the Guangzhou (2017–2022) and Shaoguan (2019–2021) Diabetic Eye Study in southern China. The 10-year ASCVD risk was calculated by the Prediction for ASCVD Risk in China (China-PAR) equations. Multivariable- adjusted Cox proportional hazard models were developed to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive capability. Results: During follow-up, a total of 171 cases of DN and 532 cases of DR were documented. Each 1% increment in 10-year ASCVD risk was associated with increased risk of DN (pooled HR, 1.122; 95% CI, 1.094 to 1.150) but not DR (pooled HR, 0.996; 95% CI, 0.979 to 1.013). The model demonstrated acceptable performance in predicting new-onset DN (pooled AUC, 0.670; 95% CI, 0.628 to 0.715). These results were consistent across cohorts and subgroups, with the association appearing to be more pronounced in women. Conclusion Ten-year ASCVD risk predicts incident DN but not DR in our study population with T2DM. Regular monitoring of ASCVD risk in routine diabetes practice may add to the ability to enhance population-based prevention for both macrovascular and microvascular diseases, particularly among women.

Background: Diabetic macrovascular and microvascular complications often coexist and may share similar risk factors and pathological pathways. We aimed to investigate whether 10-year atherosclerotic cardiovascular disease (ASCVD) risk, which is commonly assessed in diabetes management, can predict incident diabetic nephropathy (DN) and retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM). Methods: This prospective cohort study enrolled 2,891 patients with clinically diagnosed T2DM who were free of ASCVD, nephropathy, or retinopathy at baseline in the Guangzhou (2017–2022) and Shaoguan (2019–2021) Diabetic Eye Study in southern China. The 10-year ASCVD risk was calculated by the Prediction for ASCVD Risk in China (China-PAR) equations. Multivariable- adjusted Cox proportional hazard models were developed to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive capability. Results: During follow-up, a total of 171 cases of DN and 532 cases of DR were documented. Each 1% increment in 10-year ASCVD risk was associated with increased risk of DN (pooled HR, 1.122; 95% CI, 1.094 to 1.150) but not DR (pooled HR, 0.996; 95% CI, 0.979 to 1.013). The model demonstrated acceptable performance in predicting new-onset DN (pooled AUC, 0.670; 95% CI, 0.628 to 0.715). These results were consistent across cohorts and subgroups, with the association appearing to be more pronounced in women. Conclusion Ten-year ASCVD risk predicts incident DN but not DR in our study population with T2DM. Regular monitoring of ASCVD risk in routine diabetes practice may add to the ability to enhance population-based prevention for both macrovascular and microvascular diseases, particularly among women.

Background: Diabetic macrovascular and microvascular complications often coexist and may share similar risk factors and pathological pathways. We aimed to investigate whether 10-year atherosclerotic cardiovascular disease (ASCVD) risk, which is commonly assessed in diabetes management, can predict incident diabetic nephropathy (DN) and retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM). Methods: This prospective cohort study enrolled 2,891 patients with clinically diagnosed T2DM who were free of ASCVD, nephropathy, or retinopathy at baseline in the Guangzhou (2017–2022) and Shaoguan (2019–2021) Diabetic Eye Study in southern China. The 10-year ASCVD risk was calculated by the Prediction for ASCVD Risk in China (China-PAR) equations. Multivariable- adjusted Cox proportional hazard models were developed to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive capability. Results: During follow-up, a total of 171 cases of DN and 532 cases of DR were documented. Each 1% increment in 10-year ASCVD risk was associated with increased risk of DN (pooled HR, 1.122; 95% CI, 1.094 to 1.150) but not DR (pooled HR, 0.996; 95% CI, 0.979 to 1.013). The model demonstrated acceptable performance in predicting new-onset DN (pooled AUC, 0.670; 95% CI, 0.628 to 0.715). These results were consistent across cohorts and subgroups, with the association appearing to be more pronounced in women. Conclusion Ten-year ASCVD risk predicts incident DN but not DR in our study population with T2DM. Regular monitoring of ASCVD risk in routine diabetes practice may add to the ability to enhance population-based prevention for both macrovascular and microvascular diseases, particularly among women.

Background: Diabetic macrovascular and microvascular complications often coexist and may share similar risk factors and pathological pathways. We aimed to investigate whether 10-year atherosclerotic cardiovascular disease (ASCVD) risk, which is commonly assessed in diabetes management, can predict incident diabetic nephropathy (DN) and retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM). Methods: This prospective cohort study enrolled 2,891 patients with clinically diagnosed T2DM who were free of ASCVD, nephropathy, or retinopathy at baseline in the Guangzhou (2017–2022) and Shaoguan (2019–2021) Diabetic Eye Study in southern China. The 10-year ASCVD risk was calculated by the Prediction for ASCVD Risk in China (China-PAR) equations. Multivariable- adjusted Cox proportional hazard models were developed to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive capability. Results: During follow-up, a total of 171 cases of DN and 532 cases of DR were documented. Each 1% increment in 10-year ASCVD risk was associated with increased risk of DN (pooled HR, 1.122; 95% CI, 1.094 to 1.150) but not DR (pooled HR, 0.996; 95% CI, 0.979 to 1.013). The model demonstrated acceptable performance in predicting new-onset DN (pooled AUC, 0.670; 95% CI, 0.628 to 0.715). These results were consistent across cohorts and subgroups, with the association appearing to be more pronounced in women. Conclusion Ten-year ASCVD risk predicts incident DN but not DR in our study population with T2DM. Regular monitoring of ASCVD risk in routine diabetes practice may add to the ability to enhance population-based prevention for both macrovascular and microvascular diseases, particularly among women.

Objective To analyze the proportion and clinicopathological characteristics of HER2-positive breast cancer patients with BRCA1/2 pathogenic variants, and their response to neoadjuvant anti-HER2 targeted therapy. Methods The clinicopathological data of 531 breast cancer patients with germline BRCA1/2 pathogenic variants (201 with BRCA1 variants and 330 with BRCA2 variants) were analyzed. Results Among the 201 BRCA1 and 330 BRCA2 variants, 17 (8.5%) and 42 (12.7%) HER2-positive breast cancer cases were identified, respectively, accounting for 11.1% of all BRCA1/2-mutated breast cancers. Compared with BRCA1/2-mutated HR-positive/HER2-negative patients, HER2-positive patients did not present any significant differences in clinicopathological features; however, compared with triple-negative breast cancer patients, HER2-positive patients had a later onset age and lower tumor grade. Among the 17 patients who received neoadjuvant anti-HER2 targeted therapy, 10 cases achieved pCR (58.8%), whereas 7 cases did not (41.2%). Conclusion HER2-positive breast cancer accounts for more than 10% of BRCA1/2-mutated patients. Approximately 40% of these patients fail to achieve pCR after neoadjuvant targeted therapy. This phenomenon highlights the possibility of combining anti-HER2 targeted agents with poly (adenosine diphosphate-ribose) polymerase inhibitors.

Objective: To investigate the current status and influencing factors of overweight and obesity among adults in Jiaxing City, Zhejiang Province, so as to provide a basis for developing targeted weight management measures. Methods: In 2024, a multistage stratified random cluster sampling method was employed to recruit permanent residents aged ≥18 years from Jiaxing City for questionnaire surveys. Data on basic information, lifestyle behaviors, and history of chronic diseases were collected. Height and body weight were measured, and overweight and obesity were determined based on body mass index (BMI). The influencing factors of overweight and obesity among adults were analyzed by a multivariable logistic regression model. Results: Totally 10 509 questionnaires were allocated, and 9 802 valid questionnaires were recovered, with an effective recovery rate of 93.27%. Among the respondents, 4 808 (49.05%) were males and 4 994 (50.95%) were females, with a mean age of (51.27±17.26) years. A total of 4 884 overweight and obesity individuals were identified, with a detection rate of 49.83%. Multivariable logistic regression analysis showed that gender (male, OR=1.719, 95%CI: 1.578-1.873), age (≥60 years, OR=0.802, 95%CI: 0.652-0.986), educational level (bachelor and above, OR=0.640, 95%CI: 0.518-0.791), marital status (being married/cohabiting, OR=1.224, 95%CI: 1.009-1.486), adequate nut intake (OR=0.910, 95%CI: 0.832-0.995), hypertension (OR=2.462, 95%CI: 2.219-2.732), and dyslipidemia (OR=1.629, 95%CI: 1.444-1.837) were statistically associated with overweight and obesity among adults. Conclusion The detected rate of overweight and obesity among adults in Jiaxing City was relatively high, and was mainly associated with gender, age, education level, marital status, nut intake, hypertension, and dyslipidemia.

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 explore the application of targeted mRNA sequencing in fusion gene diagnosis of hematologic diseases. METHODS: Bone marrow or peripheral blood samples of 105 patients with abnormally elevated eosinophil proportions and 291 acute leukemia patients from January 2015 to June 2023 in the First Affiliated Hospital of Soochow University were analyzed and gene structural variants were detected by targeted mRNA sequencing. RESULTS: Among 105 patients with abnormally elevated eosinophil proportions, 6 cases were detected with gene structural variants, among which fusion gene testing results in 5 cases could serve as diagnostic indicators for myeloid neoplasms with eosinophilia. In addition, a IL3∷ETV6 fusion gene was detected in one patient with chronic eosinophilic leukemia, not otherwise specified. Among 119 patients with acute myeloid leukemia (AML), 38 cases were detected structural variants by targeted mRNA sequencing, accounting for 31.9%, which was significantly higher than 20.2% (24/119) detected by multiple quantitative PCR (P < 0.05). We also found one patient with AML had both NUP98∷PRRX2 and KCTD5∷JAK2 fusion genes. A total of 104 patients were detected structural variants by targeted mRNA sequencing in 172 cases with acute B-lymphoblastic leukemia who were tested negative by multiple quantitative PCR, with a detection rate of 60.5% (102/172). CONCLUSION Targeted mRNA sequencing can effectively detect fusion gene and has potential clinical application value in diagnosis and classificatation in hematologic diseases.
Humans ; Hematologic Diseases/diagnosis* ; RNA, Messenger/genetics* ; Oncogene Proteins, Fusion/genetics* ; Sequence Analysis, RNA ; Leukemia, Myeloid, Acute/diagnosis*