Objective To analyze the characteristics of viral hepatitis mortality and life loss among residents in Pudong New Area from 2003 to 2023, and to provide a basis for related prevention and control work. Methods Viral hepatitis mortality data were obtained from the Pudong New Area mortality monitoring system. The crude mortality rate (CMR), standardized mortality rate (SMR), potential years of life lost (PYLL), average years of life lost (AYLL), and standardized potential years of life lost (SPYLL) were calculated to analyze viral hepatitis deaths. The average annual change (AAPC) and annual percentage change (APC) of the mortality rate were calculated by Joinpoint regression analysis to analyze the trend of mortality. Results The CMR and SMR of viral hepatitis among residents in Pudong New Area from 2003 to 2023 were 3.89/100000 and 1.98/100000, respectively. Both CMR and SMR of viral hepatitis showed a decreasing trend over time (CMR:APC=-5.476, t=-13.581, P<0.001; SMR:APC=- 7.624, t= -21.253, P<0.001). The CMR for males was 4.75/100000 and the SMR for males was 2.65/100000; the CMR for females was 3.04/100000 and the SMR for females was 1.32/100000, with a higher mortality rate for males than for females（Z_CME=12.094，P<0.001; Z_SMR=-14.718，P<0.001). Deaths were concentrated in the age groups of 45-64 years old and 65 years old and above, accounting for 91.62% of the total deaths. The PYLL of deaths due to viral hepatitis among residents in Pudong New Area from 2003 to 2023 was 26912 person-years, with a PYLLR of 0.45% and an AYLL of 8.88 years per person. Conclusion The mortality rate of viral hepatitis among the residents of Pudong New Area in 2003-2023 shows a decreasing trend over time. The mortality rate of males is higher than that of females, and the deaths of middle-aged and elderly people account for a large proportion of the total deaths. Chronic hepatitis B is the main cause of death.

ObjectiveThis paper aims to investigate the traditional Chinese medicine syndrome types in patients with chronic hepatitis B （CHB） complicated by metabolic dysfunction-associated fatty liver disease （MAFLD） and explore the correlations between these syndrome types and clinical indicators， as well as ocular manifestation characteristics， thereby providing a reference for syndrome differentiation and treatment strategies in traditional Chinese medicine. MethodsGeneral data， information from the four diagnostic methods of traditional Chinese medicine， clinical indicators， and ocular manifestation data were collected from 506 patients with CHB complicated by MAFLD enrolled at the Public Health Clinical Center of Chengdu between June 2024 and December 2024. Cluster analysis， principal component analysis， and complex network models were employed to identify the distribution patterns of traditional Chinese medicine syndromes. Correlations between different syndrome types and clinical indicators， as well as ocular manifestation characteristics， were further analyzed. ResultsThe predominant syndromes identified in patients with CHB complicated by MAFLD were dampness and heat accumulation （51.58%）， liver depression with spleen deficiency （31.62%）， blood stasis obstructing collaterals （8.89%）， and Qi-Yin deficiency （7.91%）. No statistically significant differences were found among the four syndrome types in routine blood tests and liver function indicators. However， patients with the dampness and heat accumulation type exhibited significantly higher levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， liver stiffness measurement （LSM）， controlled attenuation parameter （CAP）， and alpha-fetoprotein （AFP）， along with lower levels of high-density lipoprotein cholesterol （HDL-C）， compared with those with other syndrome types. Regarding ocular manifestations， the incidence of moon halo signs was significantly higher in patients with the blood stasis obstructing collaterals type than in those with other syndrome types. Additionally， the incidence in scleral zone 3 （corresponding to the large intestine） was higher in patients with the damp and heat accumulation type. ConclusionDampness and heat accumulation is the core syndrome type in patients with CHB complicated by MAFLD， commonly accompanied by spleen deficiency， liver depression， blood stasis， and Yin deficiency. A complex syndrome pattern characterized by a predominance of dampness and heat， along with a mixture of deficiency and excess， is formed. Different traditional Chinese medicine syndrome types are associated with distinct clinical indicators and ocular manifestation characteristics. Among them， patients with the dampness and heat accumulation type exhibit more pronounced metabolic disturbances and liver injury， whereas those with the blood stasis type show a higher incidence of moon halo signs. Abnormalities in scleral zone 3 are also more prevalent in patients with dampness and heat type.

The digitization of traditional Chinese medicine (TCM) has generated vast amounts of data. However, these data are characterized by significant heterogeneity and complex semantic structures, posing substantial challenges for systematic integration and intelligent analysis, and limiting its potential for modern clinical and computational research. To address the challenges posed by the high heterogeneity and complex structure in TCM data, we designed and developed the TCM Data Hub platform, which is powered by the YiYuan large language models (LLMs). This platform aims to enhance intelligent data processing capabilities and unlock the potential for clinical application of TCM data through systematic integration and efficient utilization, thereby bridging the gap between traditional knowledge and modern computational research. This study first analyzed the heterogeneity and complexity of TCM information with respect to data types, structures, and semantics. A standardized data framework was constructed to enhance data integration and interoperability. Based on the TCM Intelligent Computing Platform of the China Academy of Chinese Medical Sciences, we trained the YiYuan LLMs to acquire domain-specific semantic understanding of TCM, thereby improving the platform’s comprehension of specialized terminology and knowledge systems. Leveraging the natural language processing capabilities of the LLMs, we developed a human-in-the-loop data processing system to enable efficient extraction, cleansing, and structured organization of TCM data. In addition, utilizing Vue and Java technologies, we developed multiple LLM-powered intelligent agents and systems, including a human-in-the-loop data processing system, as well as automated prescription mining and network pharmacology analysis agents. Task-specific agents tailored to TCM data processing were developed to enhance the model’s effectiveness in clinical knowledge discovery. System functionality and platform infrastructure were implemented using Java and Vue technologies.The TCM Data Hub platform has completed system construction and core functionality implementation. It supported integrated management and efficient access to 8 key types of TCM data: prescriptions, materia medica, ingredients, targets, diseases (Western medicine), diseases (TCM), syndromes, and therapeutic methods. The human-in-the-loop data processing system achieved an accuracy of 95.34% in structuring TCM data and supported annotation for data requiring manual labeling. The intelligent agent-driven big-data analytics module enabled 1-click, end-to-end workflows for TCM prescription mining, herb-syndrome association analysis, network pharmacology, and molecular biology research, completing a full data mining task in approximately 30 minutes. Users can interact with and manipulate data through a visual front-end interface. The system demonstrated stable performance, strong scalability, and a user-friendly experience. Empowered by the YiYuan LLMs, the TCM Data Hub platform significantly improves the accessibility, usability, and intelligence of TCM data. It effectively bridges traditional TCM knowledge with modern intelligent technologies, providing robust data support and intelligent tools for TCM research and clinical applications.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To elucidate the application scope and delineate the criteria of dobutamine stress echocardiography (DSE) in assessing surgical risk associated with valvular heart diseases in patients presenting with reduced left ventricular ejection fraction (LVEF). Methods This retrospective analysis encompassed data from patients with reduced LVEF (LVEF<40%) who underwent DSE prior to valvular heart surgery at the Valvular Surgery Center of Beijing Anzhen Hospital between May 2016 and September 2024. Patients were stratified based on the terminal dose of dobutamine into two cohorts: a limited dose group [receiving a maximum dobutamine dose of <5 µg/(kg·min) due to concomitant conditions such as suspected atrial thrombus, aortic dilation, or previous myocardial infarction] and a non-limited dose group (where dosage was adjusted to either achieve the maximum positive standard or the maximal dose tolerable by the patient). Within the non-limited dose group, patients were further classified into positive and negative response groups. The positive response post DSE was defined based on the following criteria: LVEF≥55% (the maximum positive standard), LVEF<55% but with a 5% improvement (the minimum positive standard) from resting situation, aortic maximum velocity (AVmax)≥400 cm/s, or mean pressure gradient (meanPG)≥40 mm Hg, latter two applicable only to patients with aortic stenosis. Clinical indicators were compared in the three groups. Results A total of 99 patients were enrolled, aged 35 to 87 years, with an average age of (61.7±10.1) years. The number of males was significantly higher than that of females (3:1). There were 61 (61.6%) patients undergoing aortic valve surgery, 25 (25.3%) undergoing mitral valve surgery, and 13 (13.1%) undergoing combined aortic and mitral valve surgery. Nineteen (19.2%) patients experienced adverse symptoms such as palpitations, head and face numbness, dizziness, chest tightness post DSE. Additionally, new-onset or aggravated ventricular premature ventricular contractions were in 40 (40.4%) patients. All above symptoms and signs resolved minutes after cessation of the test. No severe adverse events necessitating oxygen therapy or emergency intervention occurred. Among the 93 patients in the non-limited dose group, 86 were classified in the positive response group and 7 in the negative response group. The left ventricular end diastolic diameter, left ventricular end systolic diameter, and LVEF in the positive group all showed significant improvement compared to preoperative values, and were also significantly better than those in the negative group (P<0.05). All 7 patients with negative DSE results underwent interventional surgery, which was significantly different from the positive group (36 patients, 41.9%). In the limited dose group (n=6), 4 patients with a positive result or a positive trend on DSE underwent median sternotomy, 2 received interventional treatment due to a negative response. No significant differences in mortality were observed among the groups (P>0.05). Conclusion Dobutamine stress echocardiography significantly contributes to risk stratification in surgical interventions for patients with valvular heart disease complicated by reduced LVEF. It aids in determining optimal timing and methods for surgery. With comprehensive patient evaluation and controlled dobutamine dosing, the application of DSE can be safely expanded.

Background The crude mortality rate of sudden death has shown a steady upward trend. Pudong New Area, Shanghai, is a highly urbanized and densely populated district that is substantially affected by the urban heat island effect and has experienced frequent extreme temperature events in recent years. However, evidence on the association between ambient temperatures and sudden death among local residents remains limited. Objective To examine the association between daily mean temperature and sudden death in Pudong New Area, and to provide evidence for reducing temperature-related risks of sudden death. Methods Data on sudden death, meteorological factors (daily average temperature, daily average relative humidity, and daily average air pressure), and air pollutants [inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂)] in Pudong New Area from 2016 to 2021 were collected. A distributed lag non-linear model was used to examine the associations of daily mean temperature with total sudden death and sudden death due to cardiovascular and cerebrovascular diseases, including lagged and cumulative effects (lag0, 0-3, 0-7, 0-14, and 0-21 d). Stratified analyses were performed by sex, age, and education level to identify vulnerable populations. The temperature attributable burden of sudden death was assessed by calculating attributable number (AN) and attribute fraction (AF). Results A total of 19458 sudden deaths were reported in Pudong New Area from 2016 to 2021, of which 11082 (56.95%) were due to cardiovascular and cerebrovascular diseases. Both low (P₅, 4.6 ℃) and high (P₉₅, 30.2 ℃) temperatures were associated with increased risks of sudden death. The cumulative risks associated with low temperature peaked at lag 0-21 d for both total sudden death and sudden death due to cardiovascular and cerebrovascular diseases. In contrast, the cumulative risks associated with high temperature peaked at lag 0-7 d for total sudden death and at lag 0-3 d for sudden death due to cardiovascular and cerebrovascular diseases. Stratified analyses showed that females, individuals aged ≥65 years, and those with primary school education or below were more sensitive to low temperature; whereas females, individuals aged <65 years, and those with secondary school education or above were more sensitive to high temperature. Using 21.5 ℃ as the minimum mortality temperature, the AN of total sudden deaths attributable to non-optimal temperature was 3791 (95%CI: 1853, 5587), with an AF of 20.41% (95%CI: 9.47%, 28.94%); the AN attributable to low temperature was 3358 (95%CI: 1087, 5062), with an AF of 17.26% (95%CI: 5.89%, 26.01%), whereas the AN attributable to high temperature was 225 (95%CI: −274, 655), with an AF of 2.03% (95%CI: −2.53%, 5.78%). For sudden deaths due to cardiovascular and cerebrovascular diseases, the AN attributable to non-optimal temperature was 2721 (95%CI: 1747, 5575), with an AF of 24.55% (95%CI: 9.59%, 28.65%); the AN attributable to low temperature was 2496 (95%CI: 988, 3562), with an AF of 22.53% (95%CI: 8.97%, 32.41%), whereas the AN attributable to high temperature was 614 (95%CI: −15, 1176), with an AF of 3.15% (95%CI: −0.08%, 6.02%). Conclusions Both low (P₅, 4.6 ℃) and high (P₉₅, 30.2 ℃) temperatures are associated with increased risks of sudden death in Pudong New Area, Shanghai. High temperature shows a relative short-term effect, whereas low temperature shows a stronger cumulative effect. Females, people ≥65 years, and individuals with primary school educational attainment or below are more vulnerable to low temperature, while females, people <65 years, and those with secondary school educational attainment or above are more vulnerable to high temperature. The attributable burden of low temperature is greater than that of high temperature. Targeted health protection measures should be strengthened for vulnerable populations during extreme temperature events.

ObjectiveTo construct a machine learning model combining two-dimensional shear wave elastography （2D-SWE） and serological markers， and to investigate its clinical value in differentiating primary biliary cholangitis （PBC） from overlap syndrome （OS）. MethodsA total of 199 patients with pathologically confirmed PBC or OS in Nantong Third People’s Hospital from January 2021 to December 2025 were retrospectively enrolled， with 125 patients in the PBC group and 74 in the OS group. The patients were randomly divided into a training set with 139 patients and a test set with 60 patients at a ratio of 7∶3. Related data were collected， including serological markers， conventional two-dimensional ultrasound parameters， and 2D-SWE parameters （including velocity of shear wave ［VS］ and liver fibrosis index ［LFI］）. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. The univariate and multivariate Logistic regression analyses were used to identify independent predictive factors， which were then incorporated into six machine learning models， and 5-fold cross-validation was used for optimization of parameters. The indicators including the area under the receiver operating characteristic curve （AUC） were compared in the test set to determine the best model， and the SHapley additive exPlanations （SHAP） analysis was used for model interpretation. ResultsFemale patients accounted for 87.8% in the OS group and 79.2% in the PBC group. Compared with the PBC group， the OS group had significantly higher age， VS， LFI， splenic area， aspartate aminotransferase， total bilirubin， prothrombin time， immunoglobulin G （IgG）， and immunoglobulin M （Z=-2.883， -6.524， -4.000， -3.061， -2.194， -2.372， -4.079， -6.964， and -2.709， all P<0.05） and a significantly lower platelet count （Z=4.098， P<0.001）， and there were also significant differences between the two groups in the proportion of patients with positive anti-nuclear antibody， fibrosis stage， and inflammation grade （χ²=3.458， 63.198， and 101.038， all P<0.05）. Variables without multicollinearity were included in the regression analysis， and the multivariate Logistic regression analysis showed that VS （odds ratio ［OR］=4.503， 95% confidence interval ［CI］： 1.698 — 11.943， P=0.003）， LFI （OR=1.813， 95%CI： 1.050 — 3.132， P=0.033）， and IgG （OR=1.121， 95%CI： 1.026 — 1.226， P=0.012） were independent predictive factors for differentiating PBC from OS. Six machine learning models were constructed based on these variables， among which the logistic regression model showed the best predictive performance in the test set， with an AUC of 0.881 （95%CI： 0.788 — 0.974）， a sensitivity of 0.731， and a specificity of 0.794. The SHAP analysis showed that IgG contributed the most to model prediction. ConclusionThe noninvasive multimodal machine learning model combining 2D-SWE parameters （VS， LFI） and serum IgG can effectively differentiate PBC from OS， providing a reference for clinical decision-making regarding the need for liver biopsy.

Objective To investigate the expression of leukocyte cell-derived chemotaxin 2(LECT2)and complement C3 in the serum of patients with autoimmune hepatitis(AIH),and their correlation with liver function grading and prognosis.Methods A total of 109 AIH patients admitted to our hospital from January 2022 to February 2024 were included as the observation group.According to the disease activity upon admission,they were grouped into the active group(59 cases)and the remission group(50 cases).According to the Child-Pugh grading,they were assigned into the grade A group(47 cases),the grade B group(40 cases),and the grade C group(22 cases).According to the prognosis,they were assigned into a poor prognosis group(35 cases)and a good prognosis group(74 cases),with 110 healthy volunteers who underwent physical checkup in our hospital as the control group.Enzyme linked immunosorbent assay(ELISA)was applied to measure serum LECT2 level.Immunoturbidimetry was applied to detect serum complement C3 level.The correlation between LECT2,complement C3 and clinical indexes was analyzed by Pearson correlation analysis.Spearman correlation analysis was applied to analyze the relationship between serum LECT2,complement C3,and Child-Pugh grading.Receiver operating characteristic(ROC)curves were established to evaluate the predictive value of LECT2 and complement C3 levels for poor prognosis in AIH patients.Results The serum level of LECT2 in the observation group was higher than that in the control group,and the level of complement C3 was lower than that in the control group(P＜0.05).The expression level of ELECT2 in the grade C group was prominently higher than that in the grade B group and grade A group,while the expression level of complement C3 was prominently lower than that in the grade B group and grade A group(P＜0.05).The level of serum LECT2 in poor prognosis group was higher than that in good prognosis group,and the level of serum complement C3 was lower than that in good prognosis group(P＜0.05).Pearson correlation analysis showed that LECT2 was positively correlated with IgG,IL-6,TNF-α and Th17/Treg,and negatively correlated with TGF-β,while complement C3 was negatively correlated(all P＜0.05);Spearman correlation analysis showed that LECT2 level was positively correlated with Child-Pugh grading,while complement C3 level was negatively correlated with Child-Pugh grading(rs=0.803,-0.875,both P＜0.05).ROC curve reveled that the AUC of serum LECT2 and complement C3 levels in predicting poor prognosis of AIH patients was 0.802 and 0.805,respectively,the AUC of their combined detection was 0.905,which was higher than that of single indicator detection(P＜0.05).Conclusion Serum LECT2 level is elevated and complement C3 level is reduced in AIH patients,and they are correlated with liver function grading and disease severity.The combined detection of the two can serve as serological indicators for evaluating liver function and predicting prognosis.