Injury monitoring is an important approach for injury control and is an important part of comprehensive disease monitoring. With the development of medical digitalization, an intelligent injury monitoring system has been created in Yinzhou District, Ningbo City, Zhejiang Province using artificial intelligence techniques based on Ningbo Municipal Health Information Platform and has been applied across the district since 2019. The manual card-reporting mode has been transformed to intelligent card-reporting mode in this system, which achieves functions of epidemiological analyses of the monitoring data, early warning of high-incidence injuries, classified management of injury and quality control of report cards. Nearly 300 thousand cards have been automatically reported since the system was online available since November 2022, and the epidemiological characteristics of injury were preliminarily understood, which provide data supports to early earning and interventions of injury. The intelligent injury monitoring system greatly improves the injury monitoring efficiency and card-reporting quality, and saves a large number of manpower and material resources, which provides a powerful technical support to widespread injury monitoring.

AIM: To compare the results calculated by population pharmacokinetic analysis tools Phoenix NLME, Monolix, R nlmixr package and CPhaMAS cloud platform with the gold standard sofeware NONMEM. METHODS: Fifty sparse sampling data sets based on a one-compartment model and fifty dense sampling data sets based on a two-compartment model were simulated, and the above five analysis tools were used to calculate the population typical value, individual variability and individual pharmacokinetic parameters. RESULTS: The population typical value and individual variability calculated by CPhaMAS and Phoenix NLME had the highest matching degree with NONMEM, followed by nlmixr. Monolix had the lowest matching degree, but Monolix and nlmixr might be more robust. The correspondence between clearance and distribution volume was better than the absorption rate constant. Except the absorption rate constant calculated by Monolix and intercompartmental clearance calculated by nlmixr, the correlation coefficients of individual pharmacokinetic parameters calculated by all analytical tools were greater than 0.99. CONCLUSION: The results calculated by the above four population pharmacokinetic analysis tools are highly correlated with that of NONMEM.

Lung cancer is one of the malignant tumors with the highest incidence and mortality rate worldwide and has a poor prognosis. With the popularization of thin layer CT, more and more early lung cancers are being detected. In recent years, thoracoscopic technology and robotic surgery technology have been innovated, and multiple adjuvant therapies such as chemotherapy, targeted therapy and immunotherapy have progressed rapidly, providing lung cancer patients with multiple treatment options. However, the prognosis of lung cancer patients has not been significantly improved, which is related to the overall poor prognosis of lung cancer patients on the one hand, and the urgent need to find effective predictive markers for patients' prognosis, to accurately screen patients, and to carry out targeted treatment in order to improve patients' prognosis on the other hand. In this paper, we review the progress of tertiary lymphoid structures (TLSs) in lung cancer and discuss the prognostic predictive value of TLSs in lung cancer and their feasibility as biomarkers for adjuvant therapy.

Objective:To create AAPM TG 119 test plans for intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) in order to evaluate the accuracy of the United Imaging Healthcare′s URT treatment planning system (URT-TPS). The plans were delivered to the phantom using the United Imaging Healthcare′s URT-Linac 506C.Methods:The overall accuracy of IMRT and VMAT planning, measurement, and analysis were evaluated for four test geometries provided by American Association of Physicists in Medicine (AAPM) Task Group Report 119(TG-119) on multi-target, prostate, head and neck and C-shape (easy). The dose distributions were measured in the coronal plane. The point measurements were measured by a Farmer type ion chamber and fluence measurements were completed with film and Delta4 phantom, respectively. Measured planar dose distributions were analyzed using gamma index with criteria 3%/3 mm.Results:For IMRT and VMAT plans, the planning results matched the TG-119 planning results. Measured point doses of IMRT and VMAT were within 2.62% and 3.90% of the planned doses, respectively. Measured film dosimetry gamma values of IMRT and VMAT were> 97.50% and> 93.27%, respectively.Conclusion:Based on these analyses which were performed in line with the TG119 recommendations, it is evident that the URT treatment planning system and URT-Linac 506C have commissioned IMRT and VMAT techniques with adequate accuracy.

Objective:To investigate the risk factors for chronic subdural hematoma(CSDH)recurrence and reoperation strategies in elderly patients.Methods:From October 2012 to December 2018, 56 patients aged 85 years and over with CSDHs undergoing surgery in our hospital were enrolled.After surgery, 12 patients had hematoma recurrence, of whom 11 received reoperation.The strategies of reoperation and the risk factors of recurrence were analyzed.Results:The average age was similar between patients with and without recurrence( t=0.308, P=0.759). However, the rates of recurrence between patients with mixed and with homogeneous density were significantly different(53.3% vs 12.8%, χ2=6.54, P=0.011), and there was also a significant difference in recurrent rate between patients with a small maximum thickness(1.0 cm to 2.5 cm)and those with a large maximum thickness(≥2.5 cm)before operation(12.5% vs 50.0%, χ2=4.753, P=0.029). Patients with a maximum thickness≥1.0 cm after surgery was associated with a comparable risk of hematoma recurrence compared with those with a thickness<1.0 cm(31.0% vs 12.0%, χ2=1.823, P=0.177). Most patients(10/11)achieved a good prognosis after reoperation. Conclusion:Reoperation can improve the quality of life in elderly patients with CSDH recurrence and without obvious contraindications.

OBJECTIVE: To analyze the dynamic changes of chest CT images of patients with corona virus disease-19 (COVID-19). METHODS: Fifty-two cases of COVID-19 were admitted in the First Affiliated Hospital of Zhejiang University School of Medicine. The consecutive chest CT scans were followed up for all patients with an average of 4 scans performed per patient during the hospitalization. The shortest interval between each scan was 2 days and the longest was 7 days. The shape, number and distribution of lung shadows, as well as the characteristics of the lesions on the CT images were reviewed. RESULTS: The obvious shadows infiltrating the lungs were shown on CT images in 50 cases, for other 2 cases there was no abnormal changes in the lungs during the first CT examination. Ground-glass opacities (GGO) were found in 48 cases (92.3%), and 19 cases (36.5%) had patchy consolidation and sub-consolidation, which were accompanied with air bronchi sign in 17 cases (32.7%). Forty one cases (78.8%) showed a thickened leaflet interval, 4 cases (7.6%) had a small number of fibrous stripes. During hospitalization, GGO lesions in COVID-19 patients gradually became rare, the fibrous strip shadows increased and it became the most common imaging manifestation. The lesions rapidly progressed in 39 cases (75.0%) within 6-9 days after admission. On days 10-14 of admission, the lesions distinctly resolved in 40 cases (76.9%). CONCLUSIONS The chest CT images of patients with COVID-19 have certain characteristics with dynamic changes, which are of value for monitoring disease progress and clinical treatment.

OBJECTIVE: To investigate the CT findings of patients with different clinical types of coronavirus disease 2019 (COVID-19). METHODS: A total of 67 patients diagnosed as COVID-19 by nucleic acid testing were collected and divided into 4 groups according to the clinical stages based on . The CT imaging characteristics were analyzed among patients with different clinical types. RESULTS: Among 67 patients, 3(4.5%) were mild, 35 (52.2%) were moderate, 22 (32.8%) were severe, and 7(10.4%) were critical ill. No significant abnormality in chest CT imaging in mild patients. The 35 cases of moderate type included 3 (8.6%) single lesions, the 22 cases of severe cases included 1 (4.5%) single lesion and the rest cases were with multiple lesions. CT images of moderate patients were mainly manifested by solid plaque shadow and halo sign (18/35, 51.4%); while fibrous strip shadow with ground glass shadow was more frequent in severe cases (7/22, 31.8%). Consolidation shadow as the main lesion was observed in 7 cases, and all of them were severe or critical ill patients. CONCLUSIONS CT images of patients with different clinical types of COVID-19 have characteristic manifestations, and solid shadow may predict severe and critical illness.
Betacoronavirus ; isolation & purification ; Coronavirus Infections ; classification ; diagnostic imaging ; Humans ; Lung ; diagnostic imaging ; Pandemics ; classification ; Pneumonia, Viral ; classification ; diagnostic imaging ; Tomography, X-Ray Computed

OBJECTIVE: To analyze the dynamic changes of chest CT images of patients with coronavirus disease 2019 (COVID-19). METHODS: Fifty-two cases of COVID-19 were admitted in the First Affiliated Hospital of Zhejiang University School of Medicine. The consecutive chest CT scans were followed up for all patients with an average of 4 scans performed per patient during the hospitalization. The shortest interval between each scan was 2 days and the longest was 7 days. The shape, number and distribution of lung shadows, as well as the characteristics of the lesions on the CT images were reviewed. RESULTS: The obvious shadows infiltrating the lungs were shown on CT images in 50 cases, for other 2 cases there was no abnormal changes in the lungs during the first CT examination. Ground-glass opacities (GGO) were found in 48 cases (92.3%), and 19 cases (36.5%) had patchy consolidation and sub-consolidation, which were accompanied with air bronchi sign in 17 cases (32.7%). Forty one cases (78.8%) showed a thickened leaflet interval, 4 cases (7.6%) had a small number of fibrous stripes. During hospitalization, GGO lesions in COVID-19 patients gradually became rare,the fibrous strip shadows increased and it became the most common imaging manifestation. The lesions rapidly progressed in 39 cases (75.0%) within 6-9 days after admission. On days 10-14 of admission, the lesions distinctly resolved in 40 cases (76.9%). CONCLUSIONS The chest CT images of patients with COVID-19 have certain characteristics with dynamic changes, which are of value for monitoring disease progress and clinical treatment.
Betacoronavirus ; isolation & purification ; China ; Coronavirus Infections ; diagnostic imaging ; pathology ; Disease Progression ; Humans ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; pathology ; Tomography, X-Ray Computed

OBJECTIVE: To analyze the CT findings of patients with different clinical types of coronavirus disease 2019 (COVID-19). METHODS: A total of 67 patients diagnosed as COVID-19 by nucleic acid testing were included and divided into 4 groups according to the clinical staging based on . The CT imaging characteristics were analyzed among patients with different clinical types. RESULTS: Among 67 patients, 3 (4.5%) were mild cases, 35 (52.2%) were ordinary cases, 22 (32.8%) were severe cases, and 7 (10.4%) were critically ill. There were no abnormal CT findings in mild cases. In 35 ordinary cases, there were single lesions in 3 cases (8.6%) and multiple lesions in 33 cases (91.4%), while in severe case 1 case had single lesion (4.5%) and 21 had multiple lesions (95.5%). CT images of ordinary patients were mainly manifested as solid plaque shadow and halo sign (18/35, 51.4%); while fibrous strip shadow with ground glass shadow was more frequent in severe cases (7/22, 31.8%). Consolidation shadow as the main lesion was observed in 7 cases, and all of them were severe or critical ill patients. CONCLUSIONS CT images in patients with different clinical types of COVID-19 have characteristic manifestations, and solid shadow may predict severe and critical illness.
Betacoronavirus ; Clinical Laboratory Techniques ; Coronavirus Infections ; diagnosis ; diagnostic imaging ; Humans ; Lung ; diagnostic imaging ; pathology ; Pneumonia, Viral ; diagnostic imaging ; pathology ; Severity of Illness Index ; Tomography, X-Ray Computed ; methods

OBJECTIVETo investigate the prevalence and risk factors of diabetic nephropathy in Ningbo Yinzhou district.

METHODSNephropathy screening was conducted among patients with type 2 diabetes mellitus (T2DM) registered in Ningbo Yinzhou district. Demographic information, clinical examination information, diabetes complications and behavioral risk factors of enrolled patients were collected. Logistic regression model was used to identify possible risk factors for the occurrence of diabetic nephropathy.

RESULTSAmong 10 604 T2DM patients included in this study, there were 3744 cases of diabetic nephropathy(35.31%). Univariate analysis showed that gender, age, education level, diabetes duration, glycemic control, hypertension, stroke, smoking and waist circumference were associated with diabetic nephropathy (<0.05 or <0.01). Multivariate logistic regression analysis showed that male, elders, long diabetes duration, hypertension and smoking were independent risk factors of diabetic nephropathy (<0.05 or <0.01).

CONCLUSIONSsDiabetic nephropathy is of high prevalence in T2DM patients. Male patients, elders, and those with long diabetes duration, hypertension and smoking habits are more likely to have diabetic nephropathy.

China ; Diabetes Mellitus, Type 2 ; Diabetic Nephropathies ; Humans ; Hypertension ; Logistic Models ; Male ; Prevalence ; Risk Factors ; Surveys and Questionnaires