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: 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 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 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 investigate the early clinical characteristics of elderly patients with severe burns and the risk factors on prognosis.Methods:This study was a retrospective case series study. Clinical data of 124 elderly patients with severe burns who met the inclusion criteria and were admitted to the 12 hospitals from January 2015 to December 2020 were collected, including 4 patients from the Fourth People's Hospital of Dalian, 5 patients from Fujian Medical University Union Hospital, 22 patients from Guangzhou Red Cross Hospital of Jinan University, 5 patients from Heilongjiang Provincial Hospital, 27 patients from the First Affiliated Hospital of Naval Medical University, 9 patients from the First Affiliated Hospital of Nanchang University, 10 patients from Affiliated Hospital of Nantong University, 9 patients from Tongren Hospital of Wuhan University & Wuhan Third Hospital, 12 patients from the 924 th Hospital of PLA, 6 patients from Zhangjiagang First People's Hospital, 4 patients from Taizhou Hospital of Zhejiang Province, and 11 patients from Zhengzhou First People's Hospital. The patients' overall clinical characteristics, such as gender, age, body mass index, total burn area, full-thickness burn area, inhalation injury, causative factors, whether combined with underlying medical diseases, and admission time after injury were recorded. According to the survival outcome within 28 days after injury, the patients were divided into survival group (89 cases) and death group (35 cases). The following data of patients were compared between the two groups, including the basic data and injuries (the same as the overall clinical characteristics ahead); the coagulation indexes within the first 24 hours of injury such as prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen degradation product (FDP), international normalized ratio (INR), and fibrinogen; the blood routine indexes within the first 24 hours of injury such as white blood cell count, platelet count, neutrophil-to-lymphocyte ratio, monocyte count, red blood cell count, hemoglobin, and hematocrit; the organ function indexes within the first 24 hours of injury such as direct bilirubin, total bilirubin, urea, serum creatinine, aspartate aminotransferase, alanine aminotransferase, total protein, albumin, globulin, blood glucose, triglyceride, total cholesterol, alkaline phosphatase, creatine kinase, electrolyte indexes (potassium, sodium, chlorine, calcium, magnesium, and phosphorus in blood), uric acid, myoglobin, and brain natriuretic peptide; the infection and blood gas indexes within the first 24 hours of injury such as procalcitonin, C-reactive protein, pH value, oxygenation index, base excess, and lactate; treatment such as whether conducted with mechanical ventilation, whether conducted with continuous renal replacement therapy, whether conducted with anticoagulation therapy, whether applied with vasoactive drugs, and fluid resuscitation. The analysis was conducted to screen the independent risk factors for the mortality within 28 days after injury in elderly patients with severe burns. Results:Among 124 patients, there were 82 males and 42 females, aged 60-97 years, with body mass index of 23.44 (21.09, 25.95) kg/m 2, total burn area of 54.00% (42.00%, 75.00%) total body surface area (TBSA), and full-thickness burn area of 25.00% (10.00%, 40.00%) TBSA. The patients were mainly combined with moderate to severe inhalation injury and caused by flame burns. There were 43 cases with underlying medical diseases. The majority of patients were admitted to the hospital within 8 hours after injury. There were statistically significant differences between patients in the 2 groups in terms of age, total burn area, full-thickness burn area, and inhalation injury, and PT, APTT, D-dimer, FDP, INR, white blood cell count, platelet count, urea, serum creatinine, blood glucose, blood sodium, uric acid, myoglobin, and urine volume within the first 24 hours of injury (with Z values of 2.37, 5.49, 5.26, 5.97, 2.18, 1.95, 2.68, 2.68, 2.51, 2.82, 2.14, 3.40, 5.31, 3.41, 2.35, 3.81, 2.16, and -3.82, respectively, P<0.05); there were statistically significant differences between two groups of patients in whether conducted with mechanical ventilation and whether applied with vasoactive drugs (with χ2 values of 9.44 and 28.50, respectively, P<0.05). Age, total burn area, full-thickness burn area, serum creatinine within the first 24 hours of injury, and APTT within the first 24 hours of injury were the independent risk factors for the mortality within 28 days after injury in elderly patients with severe burns (with odds ratios of 1.17, 1.10, 1.10, 1.09, and 1.27, 95% confidence intervals of 1.03-1.40, 1.04-1.21, 1.05-1.19, 1.05-1.17, and 1.07-1.69, respectively, P<0.05). Conclusions:The elderly patients with severe burns had the injuries mainly from flame burns, often accompanied by moderate to severe inhalation injury and enhanced inflammatory response, elevated blood glucose levels, activated fibrinolysis, and impaired organ function in the early stage, which are associated with their prognosis. Age, total burn area, full-thickness burn area, and serum creatinine and APTT within the first 24 hours of injury are the independent risk factors for death within 28 days after injury in this population.

ObjectiveExisting artificial vision devices can be divided into two types: implanted devices and extracorporeal devices, both of which have some disadvantages. The former requires surgical implantation, which may lead to irreversible trauma, while the latter has some defects such as relatively simple instructions, limited application scenarios and relying too much on the judgment of artificial intelligence (AI) to provide enough security. Here we propose a system that has voice interaction and can convert surrounding environment information into tactile commands on head and neck. Compared with existing extracorporeal devices, our device can provide a larger capacity of information and has advantages such as lower cost, lower risk, suitable for a variety of life and work scenarios. MethodsWith the latest remote wireless communication and chip technologies, microelectronic devices, cameras and sensors worn by the user, as well as the huge database and computing power in the cloud, the backend staff can get a full insight into the scenario, environmental parameters and status of the user remotely (for example, across the city) in real time. In the meanwhile, by comparing the cloud database and in-memory database and with the help of AI-assisted recognition and manual analysis, they can quickly develop the most reasonable action plan and send instructions to the user. In addition, the backend staff can provide humanistic care and emotional sustenance through voice dialogs. ResultsThis study originally proposes the concept of “remote virtual companion” and demonstrates the related hardware and software as well as test results. The system can not only achieve basic guide functions, for example, helping a person with visual impairment to shop in supermarkets, find seats at cafes, walk on the streets, construct complex puzzles, and play cards, but also can meet the demand for fast-paced daily tasks such as cycling. ConclusionExperimental results show that this “remote virtual companion” is applicable for various scenarios and demands. It can help blind people with their travels, shopping and entertainment, or accompany the elderlies with their trips, wilderness explorations, and travels.