Objective: This prospective study evaluated the feasibility of chemical exchange saturation transfer (CEST) MRI for assessing disease activity in thyroid-associated ophthalmopathy (TAO). Materials and Methods: A total of 88 patients with active TAO, 76 with inactive TAO, and 30 healthy controls were enrolled. CEST MRI-derived magnetization transfer ratio (MTR) and MTR asymmetry (MTRasym) at 1 ppm, 2 ppm, and 3.5 ppm were calculated. Clinical data, MTR, and MTRasym values for the extraocular muscles (one representative muscle per eye, yielding two measurements per participant) were compared among the groups. Spearman’s correlation was used to examine associations between imaging parameters and the clinical activity score (CAS) in patients with TAO. Logistic regression analysis was used to identify independent associations between imaging parameters and disease activity in patients with TAO (active vs. inactive). Receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic performance for discriminating active from inactive TAO. Results: Patients with active TAO showed lower MTR values (P < 0.001) and higher MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) (all P < 0.001) compared with those with inactive TAO. MTR was negatively correlated with CAS (r = -0.402; P < 0.001), while MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) were positively correlated with CAS (r = 0.369, 0.350, and 0.349, respectively;all P < 0.001). MTR and MTRasym (1 ppm) were independently associated with TAO activity. The areas under the ROC curve (AUCs) for MTR and MTRasym (1 ppm) in discriminating active from inactive TAO were 0.772 and 0.730, respectively. Combining MTR with MTRasym (1 ppm) significantly improved diagnostic performance compared with either parameter alone, achieving an AUC of 0.805 (P = 0.029 and 0.001). Conclusion MTR and MTRasym (1 ppm) were independently associated with TAO activity. Their combination further enhanced diagnostic performance in distinguishing active from inactive TAO, suggesting their potential as quantitative imaging biomarkers to guide treatment in patients with TAO.

Objective This study aims to apply the moving average method of time series analysis to forecast outpatient and emergency department visits at our hospital for 2024.Additionally,we will validate the trend prediction model against actual visit data from January to April 2024,assessing the accuracy of the time series fitting.The insights generated will serve as a sci-entific foundation for the hospital to allocate resources effectively,formulate work plans,and meet annual objectives.Methods We collected data on outpatient and emergency visits from 2020 to 2023(n=16 periods)and employed the four moving average method for time series decomposition.We calculated the adjusted seasonal index values and developed a linear trend prediction model(Y=7 3847+568.08t)that incorporates seasonal factors.We then computed the predicted monthly outpatient emergency visits for 2024 and compared these forecasts with actual values from the first four months of 2024 to test the model's reliability.Results The predicted visits for the first four months of 2024 were 84 396,80 633,88 244,and 84 158 respectively.The rela-tive errors compared to actual figures ranged from 1.13％to 8.81％,with an average relative error of 4.22％.The seasonal indi-ces revealed that the third quarter represents the peak period(104.26％),while the second quarter is the low point(95.91％).Conclusion The moving average seasonal index method effectively captures the seasonal variations in outpatient and emergency department visits,offering high prediction accuracy.This methodology can assist hospitals in dynamically adjusting their schedu-ling and optimizing resource allocation.

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

Objective To investigate the current status of hypertension in the old adults living in urban city and rural areas in Qinghai Plateau and analyze the related influencing factors in order to provide data and evidence for targeted formulation of preventive and control measures for the pop-ulation.Methods Cluster-random sampling was used to subject 1372 elderly people(aged ≥60 years)from 8 urban areas and 25 natural villages in Xining City,Qinghai Province.Questionnaires were used to collect their demographic data,body mass index(BMI),history of chronic diseases,and lipid-related indicators.According to complicated with hypertension or not,they were divided into a hypertension group(615 cases)and a non-hypertension group(757 cases).SPSS 26.0 soft-ware was employed to perform statistical analyses with descriptive analysis and multivarlate un-conditional logistic regression analysis.Results Among the 1372 elderly persons,615 participants had hypertension,and the overall prevalence was 44.8％,and that in urban area and rural area was 50.1％and 38.5％,respectively,with significant difference(P＜0.01).Statistical differences were observed between those with and without hypertension in terms of age,BMI,and proportions of coronary heart disease(CHD),diabetes and stroke(P＜0.05,P＜0.01).In the urban populations,there were obvious differences in marital status,BMI,and proportions of CHD and diabetes be-tween those with and without hypertension(P＜0.01).For the rural populations,notable differ-ences were observed in age and proportions of CHD and diabetes between those with and without hypertension(P＜0.05,P＜0.01).Multivariate unconditional logistic regression analysis revealed that urban areas,obesity,CHD and diabetes were risk factors for hypertension in the elderly living in the urban and rural areas(OR=1.622,95％CI:1.299-2.026,P=0.000;OR=0.564,95％CI:0.315-1.006,P=0.042;OR=0.604,95％CI:0.417-0.874,P=0.008;OR=0.472,95％CI:0.328-0.678,P=0.000;OR=0.474,95％CI:0.334-0.673,P=0.000).Obesity,CHD and diabetes were risk factors for hypertension in those in the urban areas(OR=0.553,95％CI:0.317-0.963,P=0.036;OR=0.506,95％CI:0.320-0.800,P=0.004;OR=0.458,95％CI:0.303-0.692,P=0.000),and CHD and diabetes were risk factors in those in the rural areas(OR=0.382,95％CI:0.219-0.666,P=0.001;OR=0.452,95％CI:0.253-0.807,P=0.007).Conclusion There is sig-nificant difference in the prevalence of hypertension between the elderly living in the urban city and rural areas in Qinghai Plateau.The old adults with overweight,obesity,and complication of CHD and diabetes are prone to developing hypertension.

Objective This study aims to apply the moving average method of time series analysis to forecast outpatient and emergency department visits at our hospital for 2024.Additionally,we will validate the trend prediction model against actual visit data from January to April 2024,assessing the accuracy of the time series fitting.The insights generated will serve as a sci-entific foundation for the hospital to allocate resources effectively,formulate work plans,and meet annual objectives.Methods We collected data on outpatient and emergency visits from 2020 to 2023(n=16 periods)and employed the four moving average method for time series decomposition.We calculated the adjusted seasonal index values and developed a linear trend prediction model(Y=7 3847+568.08t)that incorporates seasonal factors.We then computed the predicted monthly outpatient emergency visits for 2024 and compared these forecasts with actual values from the first four months of 2024 to test the model's reliability.Results The predicted visits for the first four months of 2024 were 84 396,80 633,88 244,and 84 158 respectively.The rela-tive errors compared to actual figures ranged from 1.13％to 8.81％,with an average relative error of 4.22％.The seasonal indi-ces revealed that the third quarter represents the peak period(104.26％),while the second quarter is the low point(95.91％).Conclusion The moving average seasonal index method effectively captures the seasonal variations in outpatient and emergency department visits,offering high prediction accuracy.This methodology can assist hospitals in dynamically adjusting their schedu-ling and optimizing resource allocation.

With the popularization of computer software technology and the development of hospital informatization,virtu-alization technology-as a key technology supporting IT infrastructure-has seen continuously expanding market demand and ap-plication scenarios.In recent years,domestic virtualization manufacturers have increased investment in independent innovation,achieving breakthroughs in virtualization software and related technologies,along with iterative product updates.This has enabled them to catch up with and surpass foreign virtualization technologies,providing more personalized virtualization products for Chi-nese enterprises.Hospitals operate multiple systems such as HIS databases,Electronic Medical Record Systems(EMRS),Pic-ture Archiving and Communication Systems(PACS),and Laboratory Information Systems(LIS).Migrating these systems from a purely physical machine environment to a virtualization platform,and using CNware virtualization products to manage existing physical resources in the data center,enables the sharing and integration of computing resources such as server resources,storage resources,and memory resources.This improves hardware utilization and software operation efficiency,achieves significant appli-cation results,and continuously enhances the quality of medical informatization services.

With the popularization of computer software technology and the development of hospital informatization,virtu-alization technology-as a key technology supporting IT infrastructure-has seen continuously expanding market demand and ap-plication scenarios.In recent years,domestic virtualization manufacturers have increased investment in independent innovation,achieving breakthroughs in virtualization software and related technologies,along with iterative product updates.This has enabled them to catch up with and surpass foreign virtualization technologies,providing more personalized virtualization products for Chi-nese enterprises.Hospitals operate multiple systems such as HIS databases,Electronic Medical Record Systems(EMRS),Pic-ture Archiving and Communication Systems(PACS),and Laboratory Information Systems(LIS).Migrating these systems from a purely physical machine environment to a virtualization platform,and using CNware virtualization products to manage existing physical resources in the data center,enables the sharing and integration of computing resources such as server resources,storage resources,and memory resources.This improves hardware utilization and software operation efficiency,achieves significant appli-cation results,and continuously enhances the quality of medical informatization services.

Objective To investigate the current status of hypertension in the old adults living in urban city and rural areas in Qinghai Plateau and analyze the related influencing factors in order to provide data and evidence for targeted formulation of preventive and control measures for the pop-ulation.Methods Cluster-random sampling was used to subject 1372 elderly people(aged ≥60 years)from 8 urban areas and 25 natural villages in Xining City,Qinghai Province.Questionnaires were used to collect their demographic data,body mass index(BMI),history of chronic diseases,and lipid-related indicators.According to complicated with hypertension or not,they were divided into a hypertension group(615 cases)and a non-hypertension group(757 cases).SPSS 26.0 soft-ware was employed to perform statistical analyses with descriptive analysis and multivarlate un-conditional logistic regression analysis.Results Among the 1372 elderly persons,615 participants had hypertension,and the overall prevalence was 44.8％,and that in urban area and rural area was 50.1％and 38.5％,respectively,with significant difference(P＜0.01).Statistical differences were observed between those with and without hypertension in terms of age,BMI,and proportions of coronary heart disease(CHD),diabetes and stroke(P＜0.05,P＜0.01).In the urban populations,there were obvious differences in marital status,BMI,and proportions of CHD and diabetes be-tween those with and without hypertension(P＜0.01).For the rural populations,notable differ-ences were observed in age and proportions of CHD and diabetes between those with and without hypertension(P＜0.05,P＜0.01).Multivariate unconditional logistic regression analysis revealed that urban areas,obesity,CHD and diabetes were risk factors for hypertension in the elderly living in the urban and rural areas(OR=1.622,95％CI:1.299-2.026,P=0.000;OR=0.564,95％CI:0.315-1.006,P=0.042;OR=0.604,95％CI:0.417-0.874,P=0.008;OR=0.472,95％CI:0.328-0.678,P=0.000;OR=0.474,95％CI:0.334-0.673,P=0.000).Obesity,CHD and diabetes were risk factors for hypertension in those in the urban areas(OR=0.553,95％CI:0.317-0.963,P=0.036;OR=0.506,95％CI:0.320-0.800,P=0.004;OR=0.458,95％CI:0.303-0.692,P=0.000),and CHD and diabetes were risk factors in those in the rural areas(OR=0.382,95％CI:0.219-0.666,P=0.001;OR=0.452,95％CI:0.253-0.807,P=0.007).Conclusion There is sig-nificant difference in the prevalence of hypertension between the elderly living in the urban city and rural areas in Qinghai Plateau.The old adults with overweight,obesity,and complication of CHD and diabetes are prone to developing hypertension.

Objective: To prospectively compare single-shot (SS) echo-planar imaging (EPI) and field-of-view optimized and constrained undistorted single-shot multiplexed sensitivity-encoding (FOCUS MUSE) for diffusion-weighted imaging (DWI) in evaluating thyroid-associated ophthalmopathy (TAO). Materials and Methods: SS EPI and FOCUS MUSE DWIs were obtained from 39 patients with TAO (18 male; mean ± standard deviation: 48.3 ± 13.3 years) and 26 healthy controls (9 male; mean ± standard deviation: 43.0 ± 18.5 years). Two radiologists scored the visual image quality using a 4-point Likert scale. The image quality score, signal-to-noise ratio (SNR), contrast-tonoise ratio (CNR), and apparent diffusion coefficient (ADC) of extraocular muscles (EOMs) were compared between the two DWIs. Differences in the ADC of EOMs were also evaluated. The performance of discriminating active from inactive TAO was assessed using receiver operating characteristic curves. The correlation between ADC and clinical activity score (CAS) was analyzed using Spearman correlation. Results: Compared with SS EPI DWI, FOCUS MUSE DWI demonstrated significantly higher image quality scores (P < 0.001), a higher SNR and CNR on the lateral rectus muscle (LRM) and medial rectus muscle (MRM) (P < 0.05), and a non-significant difference in the ADC of the LRM and MRM. Active TAO showed higher ADC than inactive TAO and healthy controls with both SS EPI and FOCUS MUSE DWIs (P < 0.001). Inactive TAO and healthy controls did not show a significant ADC difference with both DWIs. Compared with SS EPI DWI, FOCUS MUSE DWI demonstrated better discrimination of active from inactive TAO (AUC:0.925 vs. 0.779; P = 0.007). The ADC was significantly correlated with CAS in SS EPI DWI (r = 0.391, P < 0.001) and FOCUS MUSE DWI (r = 0.645, P < 0.001). Conclusion FOCUS MUSE DWI provides better images for evaluating EOMs and better performance in diagnosing active TAO than SS EPI DWI. The application of FOCUS MUSE will facilitate the DWI evaluation of TAO.

Objective:This study discusses the job preferences of Center for Disease Control and Prevention(CDC)staffs at the prefectural-level,and provides a basis for the development of an effective incentive mechanism.Method:This study used a combination of stratified sampling and purposive sampling to research online 455 staffs from six prefectural-level CDCs in Shandong Province,analyzed the data using a mixed logit model and latent class model,and calculated willingness to pay and relative importance.Result:In the mixed logit model,income,benefit level,establishment,workload,recognition and respect from the public,personal career development opportunities,and training opportunities all had significant influences(P<0.05)on the job selection preferences of the CDC staffs,with hygiene factors such as establishment(β =2.636)and income(β =0.083)having a greater degree of influence than motivation factors.The latent class model shows that relatively young CDC staffs with lower monthly incomes value income more;older CDC staffs with higher monthly incomes value establishment more.Conclusion:Prefectural-level CDC staffs prefer jobs with establishment,higher incomes,very good benefit levels,recognition and respected from the public,lower workloads,many opportunities for personal career advancement and abundant training opportunities.It is recommended that the total number of establishments be rationally controlled and dynamically adjusted to balance the differences between working conditions within and outside the establishment and that the financial input to CDC be increased and the pay performance system be improved;that attention be paid to both hygiene factors and motivation factors,and that a variety of measures work together to incentivize CDC staffs development;and that differentiated incentives be adopted for different categories of CDC staffs.