Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Objective:To analyze the advantages and disadvantages of online and offline laboratory medicine continuing education and training, and to discuss the future continuing education and training mode under new technology development and new situation.Methods:A questionnaire was administered to the trainees who participated in the 2019 and/or 2020 national continuing medical education project—Clinical Application and Evaluation of New Technologies and Methods of Laboratory Medicine—sponsored by the Department of Laboratory Medicine, West China Hospital, Sichuan University. One hundred and twenty-four questionnaires were completed for the 2019 offline training, and 503 questionnaires were completed for the 2020 online training. The rank sum test, Fisher's exact test, and chi-square test were performed for statistical analysis with the use of SPSS 26.0.Results:The participants in 2020 were significantly younger and the proportion of female participants in 2020 was significantly higher compared with those in 2019. Intermediate titles or above accounted for 66.93% (83/124) in 2019, and intermediate titles or below accounted for 88.67% (446/503) in 2020. The proportion of people from Sichuan Province was significantly higher in 2019. The proportion of trainees from primary institutions was significantly lower in 2019. In 2019, public institutions were mainly tertiary hospitals (74.31%, 81/109), and the majority of participants from private institutions were from third party testing institutions (60.00%, 9/15). In 2020, the percentage of tertiary hospitals in public institutions decreased to 60.99% (258/423), while the percentage of community medical institutions increased to 10.64% (45/423), and 75.00% (60/80) of trainees from private institutions were from tertiary and secondary medical institutions. Trainees with lower educational levels were more likely to appreciate the value of the training course, especially with higher degrees of satisfaction with improvements in theoretical levels and practical skills, and participants from primary institutions believed that the training course could effectively improve their theoretical and practical levels. The number of participants who provided suggestions on laboratory medicine continuing education and training needs in 2019 (83.75%, 67/80) was higher than that in 2020 (48.51%, 244/503). The overall pass rate of post-training assessment in 2020 was 88.52% (424/479).Conclusions:Online and offline training modes have different audience groups and training effects. Online continuing education can provide training opportunities to more primary care personnel and junior and intermediate professionals, which is conducive to improving the basic professional literacy and testing skills of laboratory personnel on the whole. At the same time, the integration of online and offline modes will promote the development of laboratory medicine continuing education.

Objective:To conduct a scoping review of research on the self-advocacy of adult cancer patients to identify their self-advocacy needs, behaviors, strengths and weaknesses, so as to provide guidance for future research in this field.Methods:Using the scoping review guidelines of Joanna Briggs Institute in Australia as a methodological framework, relevant literatures were searched in PubMed, Web of Science, Cochrane Library, Embase, Science Direct, CINAHL, Scopus, China National Knowledge Infrastructure, Wanfang, VIP and China Biology Medicine disc. The search period was from establishment of the databases to December 2023, and the results were summarized and analyzed.Results:A total of 14 articles were included, and self-advocacy needs included six types of needs, such as symptom management, communication, interpersonal support, disease information, decision-making and emotional management. Self-advocacy included four aspects, including seeking information, self-decision-making, strengthening contact with the outside world and effective communication.Conclusions:Adult cancer patients have diverse types of self-advocacy needs and certain self-advocacy behaviors. Future research should pay attention to self-advocacy needs assessment, develop corresponding tools, focus on self-advocacy behaviors, leverage the advantages of self-advocacy and explore strategies to achieve effective self-advocacy support.

Objective:To conduct a scoping review of the application of mobile health applications (MHA) in the care of patients with colorectal cancer, summarizing the development process, the functions achieved, as well as the evaluation metrics, to provide references for MHA practice and related research.Methods:Following the scoping review framework, a comprehensive search was conducted across both domestic and international databases, including the China Biomedical Literature Database, Wanfang Database, China National Knowledge Infrastructure (CNKI), VIP Database, Cochrane Library, PubMed, Embase, CINAHL, Web of Science, and Scopus. The search period was from the database inception to February, 2024.Results:A total of 16 studies were included. The development of MHA involved multiple methods including literature reviews, qualitative interviews, consultations with multidisciplinary teams, and guidance from theoretical models. The functions of MHA include health education, peer support, guided feedback, monitoring, and reminder features. Evaluation metrics for MHA comprise usability, adherence, and effectiveness.Conclusions:MHA has demonstrated positive effects in enhancing patients' knowledge and alleviating symptoms such as fatigue and vomiting in colorectal cancer patients. However, it is still in its early stages, and further high-quality studies are needed to scientifically develop MHA that meets patients' needs.

Objective:This study aims to explore the synergistic effects of DIP and other medical insurance supply-side policies.Method:City A that has piloted DIP reform was set as the treatment group,and City B without reform was set as the control group.A total of 1 120 public medical institution samples from 2019 to 2022 were collected.The total medical expenses during hospitalization and some structural expenses were analyzed using DID method.Result:DIP had a significant inhibitory effect on the medical expenses,and the expenses of checkups and examinations during hospitalization in city A,but had no impact on the drug and the material expenses during hospitalization.Conclusion:DIP played a significant cost control role and effectively controlled the total medical expenses during hospitalization.The synergistic effects of price adjustment of medical services policy and national centralized drug/material procurement policy on cost control were insufficient.DIP synergized with other supply-side policies to promote rational medical cost structure.It is suggested that medical insurance departments should focus on the synergistic effects of medical insurance supply-side policies to jointly improve the efficiency of medical insurance fund utilization.

Objective:Analyze the medical reimbursement rate and influencing factors under the DIP payment method to refine the DIP payment policy,promote the optimization of internal operations in medical institutions,and ensure reasonable compensation.Methods:Based on the 2022 DIP fund settlement data from 196 medical institutions in City A,the study used multiple linear regression to analyze the factors affecting medical reimbursement rate and conducted a heterogeneity analysis for medical institutions of different levels.Results:The medical reimbursement rate for medical institutions in City A in 2022 was 103.32%.Medical institutions with lower CMI standardized inpatient costs,lower rates of deviation cases,tertiary care institutions,lower proportion of level-four surgeries,and lower ratios of resident to employee medical insurance cases have higher medical reimbursement rate(P<0.05).Heterogeneity analysis reveals that therates of deviation cases,the proportion of primary care diseases,the ratio of resident to employee medical insurance cases,and the low-standard admission rate have different impacts on medical institutions of different levels.Conclusion:Medical insurance departments should improve policies for primary care diseases,dynamically adjust disease catalogs and payment standards,optimize funding levels and institutional coefficients,and increase penalties for violations to ensure effective use of funds.Medical institutions need to strengthen their understanding of policies,focus on refined internal management,promote standardized and rational diagnosis and treatment through performance assessment transformation,and leverage their own advantages in medical services to reasonably increase the medical reimbursement rate.