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: Para-aortic lymph node dissection (PALND) is a widely used treatment that causes many complications. This study is to evaluate the efficacy and safety of nerve-sparing para-aortic lymph node dissection (NSPALND) by comparing it with conventional PALND in gynecological malignancies and to prove whether locating the superior hypogastric plexus (SHP) can help reveal the para-aortic nerves. Methods: This is a retrospective study of the patients who underwent para-aortic lymphadenectomy from January 2020 to December 2022 at Zhejiang Cancer Hospital. All of them were divided into NSPALND and PALND groups according to whether or not nervesparing was performed. The surgical, functional and oncological outcomes were evaluated. Results: There were 43 patients enrolled, of which, 20 patients underwent NSPALND and 23 patients underwent PALND. The para-aortic nerves were successfully revealed by locating the SHP in all 20 cases of NSPALND. The post-operative anal exhaust time in the NSPALND group was significantly shorter than that in the PALND group (2.5 vs. 4 days, p=0.006), and the incidence of acute intestinal obstruction in the NSPALND group was significantly lower than that in the PALND group (10% vs. 39%, p=0.029). There was no difference between the two groups in terms of catheterization duration, urinary retention, dysuria, as well as the number of lymph nodes removed and the para-aortic recurrence rate. Conclusion NSPALND can significantly reduce the rate of acute intestinal obstruction and improve post-operative intestinal function. Locating the SHP and using it as an anatomical landmark to reveal the para-aortic nerves is feasible. Its exact clinical value needs to be further studied.

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: Para-aortic lymph node dissection (PALND) is a widely used treatment that causes many complications. This study is to evaluate the efficacy and safety of nerve-sparing para-aortic lymph node dissection (NSPALND) by comparing it with conventional PALND in gynecological malignancies and to prove whether locating the superior hypogastric plexus (SHP) can help reveal the para-aortic nerves. Methods: This is a retrospective study of the patients who underwent para-aortic lymphadenectomy from January 2020 to December 2022 at Zhejiang Cancer Hospital. All of them were divided into NSPALND and PALND groups according to whether or not nervesparing was performed. The surgical, functional and oncological outcomes were evaluated. Results: There were 43 patients enrolled, of which, 20 patients underwent NSPALND and 23 patients underwent PALND. The para-aortic nerves were successfully revealed by locating the SHP in all 20 cases of NSPALND. The post-operative anal exhaust time in the NSPALND group was significantly shorter than that in the PALND group (2.5 vs. 4 days, p=0.006), and the incidence of acute intestinal obstruction in the NSPALND group was significantly lower than that in the PALND group (10% vs. 39%, p=0.029). There was no difference between the two groups in terms of catheterization duration, urinary retention, dysuria, as well as the number of lymph nodes removed and the para-aortic recurrence rate. Conclusion NSPALND can significantly reduce the rate of acute intestinal obstruction and improve post-operative intestinal function. Locating the SHP and using it as an anatomical landmark to reveal the para-aortic nerves is feasible. Its exact clinical value needs to be further studied.

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: Para-aortic lymph node dissection (PALND) is a widely used treatment that causes many complications. This study is to evaluate the efficacy and safety of nerve-sparing para-aortic lymph node dissection (NSPALND) by comparing it with conventional PALND in gynecological malignancies and to prove whether locating the superior hypogastric plexus (SHP) can help reveal the para-aortic nerves. Methods: This is a retrospective study of the patients who underwent para-aortic lymphadenectomy from January 2020 to December 2022 at Zhejiang Cancer Hospital. All of them were divided into NSPALND and PALND groups according to whether or not nervesparing was performed. The surgical, functional and oncological outcomes were evaluated. Results: There were 43 patients enrolled, of which, 20 patients underwent NSPALND and 23 patients underwent PALND. The para-aortic nerves were successfully revealed by locating the SHP in all 20 cases of NSPALND. The post-operative anal exhaust time in the NSPALND group was significantly shorter than that in the PALND group (2.5 vs. 4 days, p=0.006), and the incidence of acute intestinal obstruction in the NSPALND group was significantly lower than that in the PALND group (10% vs. 39%, p=0.029). There was no difference between the two groups in terms of catheterization duration, urinary retention, dysuria, as well as the number of lymph nodes removed and the para-aortic recurrence rate. Conclusion NSPALND can significantly reduce the rate of acute intestinal obstruction and improve post-operative intestinal function. Locating the SHP and using it as an anatomical landmark to reveal the para-aortic nerves is feasible. Its exact clinical value needs to be further studied.

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.

With the continuous improvement of medical information and intelligence, multi-modal data fusion technology is increasingly widely used in the medical field. Multi-modal data not only has a large quantity, but also has rich information content, which can provide strong support for clinical nursing decision-making. However, due to the uneven level of informatization and intelligence development among medical institutions, the development and application of nursing decision support system is still in a fragmented state. Based on this, this study explores in depth the current application status and challenges faced by multi-modal data fusion in nursing decision support systems, with the aim of providing reference for the design and improvement of nursing decision support system at all levels of medical institutions in the future.

With the continuous advancement of information technology, electronic medical records (EMR) have accumulated vast amounts of clinical data, which can assist nursing staff in making clinical decisions, thereby improving the quality of care, enhancing work efficiency, and promoting patient safety. However, due to varying levels of information technology development across medical institutions, nursing decision support systems (NDSS) remain in a fragmented development stage. This article explores the current application status and existing shortcomings of NDSS based on EMR systems, aiming to provide reference for the design and improvement of NDSS in various levels of medical institutions.