Objective:To present an evaluation indicator system for access to cancer screening services.Methods:The evaluation indicator pool was constructed through a scoping review. The theoretical framework was constructed based on the multi-source indicators, and the qualitative expert consultation method was employed to form the initial version of the three-level evaluation indicator system. Delphi expert consultation method was conducted in two rounds to evaluate the relevance, importance, and availability of the proposed evaluation indicator system. The expert positive coefficient, authority coefficient, coordination degree of expert opinions, and concentration of expert opinions were subjected to analysis. Subsequently, the three-level evaluation indicator system for access to cancer screening services was adjusted and determined based on the boundary value method and the open opinions of experts. Finally, the combination weight method was employed to determine the weight.Results:The initial version of the indicator system comprised 3 primary (first-level) indicators, 11 secondary (second-level) indicators, and 46 tertiary (third-level) indicators. Delphi expert consultation was conducted for the initial version, and 17 experts ultimately completed it, exhibiting a positive coefficient of 100% and an authority coefficient of 0.87. In comparison to the initial round of consultation, Kendall's W coefficient ranges (0.15-0.43, all P<0.05) of relevance, importance, and availability scores for each tertiary indicator in the second round exhibited an improvement. The analysis of the importance dimension indicates that expert opinions are also more concentrated, as evidenced by an increase of 8.5% and 7.0% in the proportion of the tertiary indicators with an arithmetic mean above 8 and a full mark ratio above 0.5, respectively. The final evaluation indicator system comprises three primary indicators, with the weights of structure evaluation, process evaluation, and outcome evaluation being 0.338, 0.378, and 0.285, respectively. It also comprises 11 secondary indicators and 45 tertiary indicators. Conclusions:The evaluation indicator system developed in this article can be an effective evaluation tool for quantitative comparison of access to cancer screening services across different populations, cancer types, and before and after intervention. Furthermore, it is recommended that the system undergo continuous optimization concerning its application.

To analyze all-cause mortality among hepatitis C cases aged ≥18 years in Yuxi City from 2005 to 2023 and explore the interactions of factors influencing survival time. Baseline and follow-up data for hepatitis C cases reported during this period were extracted from the Chinese National Notifiable Disease Reporting System. Survival time and related factors were assessed using the Cox proportional hazards model. Kaplan-Meier cumulative mortality risk curves were generated for treated and untreated hepatitis C cases, and interactions among subgroups of various influencing factors were examined. A total of 5 110 hepatitis C cases aged ≥18 years were reported from 2005 to 2023, encompassing 35 349.25 person-years of observation with the follow-up time duration M ( Q1, Q3) was 6.17 (2.33, 11.08) person-years. There were 763 all-cause deaths, corresponding to a mortality density of 2.16 per 100 person-years. Survival analysis showed a statistically significant difference in cumulative mortality between the treated and untreated groups (Log-rank χ2=122.033, P<0.001), with a lower risk of death observed among treated patients. Additive model analysis showed that there was a synergistic interaction between treatment status and age group, with relative excess of interaction, attributable proportions of interaction, and synergy index of 6.16 (95 %CI: 2.70-9.61), 1.83 (95 %CI: 1.46-2.30), and 0.42 (95 %CI: 0.31-0.53), respectively; and between treatment status and gender. There was a synergistic interaction between treatment status and sex, with relative excess of interaction, attributable proportions of interaction, and synergy index of 2.63 (95 %CI: 1.14-4.13), 1.56 (95 %CI: 1.19-2.06), and 0.32 (95 %CI: 0.17-0.46), respectively. The cause of death composition were 38.53% (249 cases) attributed to hepatitis C-related causes.The leading non-hepatitis C-related causes of death were cardiovascular and cerebrovascular diseases, pulmonary diseases, malignancies, drug overdose, and injuries. In conclusion, hepatitis C cases ≥18 years of age in Yuxi City had a lower cumulative mortality rate when treated than when untreated. Treatment status interacted with age and gender on patient survival, respectively. Changes in patients with concomitant cardiovascular diseases, pulmonary diseases and malignancies should be focused.

This study retrospectively reviewed the clinical data of 9 recipients with post-transplant lymphoproliferative disorder (PTLD) after liver transplantation admitted to the Organ Transplantation Center of the Affiliated Hospital of Qingdao University from January 2020 to June 2024, and summarized their clinical manifestations, pathological features, treatment regimens, and prognostic conditions, so as to provide a reference for clinical diagnosis and treatment.

Objective:To present an evaluation indicator system for access to cancer screening services.Methods:The evaluation indicator pool was constructed through a scoping review. The theoretical framework was constructed based on the multi-source indicators, and the qualitative expert consultation method was employed to form the initial version of the three-level evaluation indicator system. Delphi expert consultation method was conducted in two rounds to evaluate the relevance, importance, and availability of the proposed evaluation indicator system. The expert positive coefficient, authority coefficient, coordination degree of expert opinions, and concentration of expert opinions were subjected to analysis. Subsequently, the three-level evaluation indicator system for access to cancer screening services was adjusted and determined based on the boundary value method and the open opinions of experts. Finally, the combination weight method was employed to determine the weight.Results:The initial version of the indicator system comprised 3 primary (first-level) indicators, 11 secondary (second-level) indicators, and 46 tertiary (third-level) indicators. Delphi expert consultation was conducted for the initial version, and 17 experts ultimately completed it, exhibiting a positive coefficient of 100% and an authority coefficient of 0.87. In comparison to the initial round of consultation, Kendall's W coefficient ranges (0.15-0.43, all P<0.05) of relevance, importance, and availability scores for each tertiary indicator in the second round exhibited an improvement. The analysis of the importance dimension indicates that expert opinions are also more concentrated, as evidenced by an increase of 8.5% and 7.0% in the proportion of the tertiary indicators with an arithmetic mean above 8 and a full mark ratio above 0.5, respectively. The final evaluation indicator system comprises three primary indicators, with the weights of structure evaluation, process evaluation, and outcome evaluation being 0.338, 0.378, and 0.285, respectively. It also comprises 11 secondary indicators and 45 tertiary indicators. Conclusions:The evaluation indicator system developed in this article can be an effective evaluation tool for quantitative comparison of access to cancer screening services across different populations, cancer types, and before and after intervention. Furthermore, it is recommended that the system undergo continuous optimization concerning its application.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

To analyze all-cause mortality among hepatitis C cases aged ≥18 years in Yuxi City from 2005 to 2023 and explore the interactions of factors influencing survival time. Baseline and follow-up data for hepatitis C cases reported during this period were extracted from the Chinese National Notifiable Disease Reporting System. Survival time and related factors were assessed using the Cox proportional hazards model. Kaplan-Meier cumulative mortality risk curves were generated for treated and untreated hepatitis C cases, and interactions among subgroups of various influencing factors were examined. A total of 5 110 hepatitis C cases aged ≥18 years were reported from 2005 to 2023, encompassing 35 349.25 person-years of observation with the follow-up time duration M ( Q1, Q3) was 6.17 (2.33, 11.08) person-years. There were 763 all-cause deaths, corresponding to a mortality density of 2.16 per 100 person-years. Survival analysis showed a statistically significant difference in cumulative mortality between the treated and untreated groups (Log-rank χ2=122.033, P<0.001), with a lower risk of death observed among treated patients. Additive model analysis showed that there was a synergistic interaction between treatment status and age group, with relative excess of interaction, attributable proportions of interaction, and synergy index of 6.16 (95 %CI: 2.70-9.61), 1.83 (95 %CI: 1.46-2.30), and 0.42 (95 %CI: 0.31-0.53), respectively; and between treatment status and gender. There was a synergistic interaction between treatment status and sex, with relative excess of interaction, attributable proportions of interaction, and synergy index of 2.63 (95 %CI: 1.14-4.13), 1.56 (95 %CI: 1.19-2.06), and 0.32 (95 %CI: 0.17-0.46), respectively. The cause of death composition were 38.53% (249 cases) attributed to hepatitis C-related causes.The leading non-hepatitis C-related causes of death were cardiovascular and cerebrovascular diseases, pulmonary diseases, malignancies, drug overdose, and injuries. In conclusion, hepatitis C cases ≥18 years of age in Yuxi City had a lower cumulative mortality rate when treated than when untreated. Treatment status interacted with age and gender on patient survival, respectively. Changes in patients with concomitant cardiovascular diseases, pulmonary diseases and malignancies should be focused.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

ObjectiveTo explore the establishment of performance assessment indicators for the classification and grading of public health staff in district-level Centers for Disease Control and Prevention (CDCs), and to provide a basis for such evaluations. MethodsThrough literature review and group interviews, performance evaluation indicators were developed based on competency evaluation. Experts were invited to evaluate the weight of performance evaluation indicators for public health staff from different categories, with the average value used to represent the weight of each indicator. ResultsTwenty-nine experts from universities in Shanghai, municipal CDCs, and district CDCs participated, yielding an expert authority coefficient of 0.86. The performance evaluation indicators for department managers were categorized into three levels, with 4 indicators at the primary level, 16 indicators at the secondary level, and 42 indicators at the tertiary level, while those for general staff included 4 primary indicators, 15 secondary indicators, and 36 tertiary indicators. Significant differences were observed in the weight coefficients of the primary indicators (internal operations, professional work, and learning and growth) between department managers and general staff. The top three secondary indicators for department managers were department management, monitoring and prevention, and level of expertise. For mid-level and senior staff, the top three secondary indicators were monitoring and prevention, level of expertise, and research work. The top three secondary indicators for junior staff were monitoring and prevention, professional expertise, and professional attitude. No significant statistical differences were found among tertiary indicators. ConclusionThe developed performance evaluation indicators are reliable. Staff at different levels and classifications should be evaluated using different performance evaluation standards to accurately reflect individual performance and contributions.

Objective: To investigate the objective characteristics of tongue manifestation in different stages of damp-heat syndrome in diabetic kidney disease (DKD). Methods: A cross-sectional study enrolled 134 patients with DKD G3-5 stages who met the diagnostic criteria for damp-heat syndrome in DKD. The patients were treated at Dongzhimen Hospital, Beijing University of Chinese Medicine, from May 2023 to January 2024. The patients were divided into three groups: DKD G3, DKD G4, and DKD G5 stage, with 53, 33, and 48 patients in each group, respectively. Clinical general data (gender, age, and body mass index) and damp-heat syndrome scores were collected from the patients. The YZAI-02 traditional Chinese medicine (TCM) AI Tongue Image Acquisition Device was used to capture tongue images from these patients. The accompanying AI Open Platform for TCM Tongue Diagnosis of the device was used to analyze and extract tongue manifestation features, including objective data on tongue color, tongue quality, coating color, and coating texture. Clinical data and objective tongue manifestation characteristics were compared among patients with DKD G3-5 based on their DKD damp-heat syndrome status. Results: No statistically significant difference in gender or body mass index was observed among the three patient groups. The DKD G3 stage group had the highest age (P<0.05). The DKD G3 stage group had a lower score for symptoms of poor appetite and anorexia(P<0.05) than the DKD G5 group. No statistically significant difference was observed in damp-heat syndrome scores among the three groups. Compared with the DKD G5 stage group, the DKD G3 stage group showed a decreased proportion of pale color at the tip and edges of the tongue (P<0.05). The DKD G4 stage group exhibited an increased proportion of crimson at the root of the tongue, a decreased proportion of thick white tongue coating at the root, a decreased proportion of pale color at the tip and edges of the tongue, an increased hue value (indicating color tone) of the tongue color in the middle, an increased brightness value (indicating color lightness) of the tongue coating color in the middle, and an increased thickness of the tongue coating (P<0.05). No statistically significant difference was observed in other tongue color proportions, color chroma values, body characteristics, coating color proportions, coating color chroma values, and coating texture characteristics among the three groups. Conclusion Tongue features differ in different stages of DKD damp-heat syndrome in multiple dimensions, enabling the inference that during the DKD G5 stage, the degree of qi and blood deficiency in the kidneys, heart, lungs, liver, gallbladder, spleen, and stomach is prominent. Dampness is more likely to accumulate in the lower jiao, particularly in the kidneys, whereas heat evil in the spleen and stomach is the most severe. These insights provide novel ideas for the clinical treatment of DKD.

Objective To investigate the clinical value of serum hsa_circRNA_0002980 and hsa_circRNA_104348 expression in the diagnosis and prognosis evaluation of liver cancer patients.Methods From April 2020 to April 2022,a total of 105 liver cancer patients and 105 liver cirrhosis patients admitted in the hospital were selected as the liver cancer group and cirrhosis group,and another 105 healthy volunteers who underwent physical examinations in the hospital were selected as the control group.Real-time fluorescence quantitative PCR(qPCR)was applied to detect the expression of serum hsa_circRNA_0002980 and hsa_circRNA_104348.Receiver operating characteristic(ROC)curve was applied to evaluate the diagnostic value and prognostic val-ue of serum hsa_circRNA_0002980 and hsa_circRNA_104348 expression in liver cancer.Multivariate COX re-gression was performed to analyze the influencing factors of prognosis in liver cancer.Results The expression levels of serum hsa_circRNA_0002980 in the liver cancer group,liver cirrhosis group,and control group in-creased sequentially(P＜0.05),while the expression levels of serum hsa_circRNA_104348 decreased sequen-tially(P＜0.05).The levels of alanine aminotransferase and aspartate aminotransferase in the liver cancer group and the liver cirrhosis group were higher than those in the control group(P＜0.05),and the level of al-bumin was lower than that in the control group(P＜0.05).The area under the curve(AUC)for the diagnosis of liver cancer by hsa_circRNA_0002980 combined with hsa_circRNA_104348 was 0.888(95％CI:0.838-0.928),which was obviously higher than those of hsa_circRNA_0002980(Z=3.526,P＜0.001)and hsa_cir-cRNA_104348 alone(Z=2.184,P=0.029).The expression level of serum hsa_circRNA_0002980 in the poor prognosis group was lower than that in the good prognosis group(P＜0.05),and the expression level of ser-um hsa_circRNA_104348 and the proportion of TNM stage Ⅲ+Ⅳ were higher than those in the good progno-sis group(P＜0.05).The AUC for predicting prognosis in liver cancer patients by the combination of hsa_cir-cRNA_0002980 and hsa_circRNA_104348 was 0.870(95％CI:0.790-0.928),and there was no statistically significant difference compared to the AUC predicted separately by hsa_circRNA_0002980 and hsa_circRNA_104348(P＞0.05).The expression of serum hsa_circRNA_0002980,hsa_circRNA_104348 and TNM stage were influencing factors for the prognosis of liver cancer patients(P＜0.05).Conclusion The expression lev-el of hsa_circRNA_0002980 in the serum of liver cancer patients is relatively low,while the expression level of hsa_circRNA_104348 is relatively high.Both have certain clinical significance in the diagnosis and prognosis e-valuation of liver cancer.