Objective:To investigate the value of a multi-parameter MRI nomogram model in evaluating the recurrence risk of hormone receptor (HR)-positive breast cancer.Methods:This study was a retrospective cross-sectional study. A retrospective analysis was conducted on the clinicopathological data (age, menopausal status, axillary lymph node metastasis, etc.) and imaging data of 220 patients with HR-positive breast cancer who underwent breast MRI examination and were pathologically confirmed at the Second Affiliated Hospital of Nantong University from January 2018 to December 2023. All patients underwent preoperative MRI examinations. Their MRI features were analyzed, and the maximum diameter of the lesion and the apparent diffusion coefficient (ADC) value were measured. Finally, the clinical treatment score (CTS5 score) after 5 years was calculated, and all patients were divided into a low recurrence risk (CTS5 score 3.13 points) and a medium to high recurrence risk (CTS5 score≥3.13 points) group. The patients were followed up through the electronic medical record system or by phone until December 31, 2024 to determine recurrence status. The patients were divided into the recurrence group and the non-recurrence group. The differences in clinicopathological data, MRI features and CTS5 scores between the recurrence group and the non-recurrence group were compared using independent sample t-tests, Mann-Whitney U tests or χ2 tests. Indicators with P0.05 in the univariate analysis were included in the multivariate logistic regression to screen the independent risk factors for predicting the recurrence of HR receptor-positive breast cancer, and a nomogram was constructed to establish the nomogram model. The receiver operating characteristic curves and the area under the curve (AUC) were used to evaluate the efficacy of the nomogram model in predicting the postoperative recurrence risk of patients with HR-positive breast cancer. The variance inflation factor (VIF) was used to evaluate the multicollinearity among independent variables. Calibration curves and decision curve analysis (DCA) were used to assess the fit and net clinical benefit of the nomogram model. Results:Among 220 patients with HR-positive breast cancer, 196 cases were in the non-recurrence group and 24 cases were in the recurrence group. There were statistically significant differences in the maximum diameter of the lesion, axillary lymph node metastasis, ADC value, CTS5 grouping, and CTS5 score between the recurrence group and the non-recurrence group ( P0.05). Multivariate logistic regression analysis showed that the maximum diameter of the lesion ( OR=1.110, 95% CI 1.169-1.503, P0.001), ADC value ( OR=0.993, 95% CI 0.993?0.989, P0.001), and axillary lymph node metastasis ( OR=8.842; 95% CI 2.120?36.884, P=0.003) were independent factors influencing postoperative recurrence in patients with HR-positive breast cancer, and a nomogram model was constructed based on this. VIF analysis showed that no significant multicollinearity was detected among the variables (VIF5). The AUC value of the nomogram model for predicting postoperative recurrence in patients with HR-positive breast cancer was 0.868 (95% CI 0.794-0.942), the sensitivity was 0.875, and the specificity was 0.781. The calibration curve showed that the prediction curve of this model for predicting postoperative recurrence in HR-positive breast cancer patients was basically consistent with the ideal curve trend. DCA showed that this model had a relatively high clinical benefit within the threshold probability range of 0.01% to 90.00%. Conclusion:The nomogram constructed based on multi-parameter MRI features can predict the postoperative recurrence risk of HR-positive breast cancer patients, with good consistency and predictive ability.

Objective:To compare the current situation of research on workplace violence (WPV) among nurses at home and abroad, providing directions for further research.Methods:Research on WPV among nurses published in PubMed, Web of Science, EBSCO, China national knowledge infrastructure, Wanfang, and VIP databases from January 1, 2003 to October 14, 2023 were searched and screened, using visualization software CiteSpace and VOSviewer to analyze the distribution and correlation of countries, authors, institutions and keywords of the included studies.Results:A total of 1 082 Chinese articles and 2 770 English articles were included. From 2003 to 2023, the annual publication volume of research on nurse WPV showed a continuous upward trend in both Chinese and English literature. Among domestic institutions, Harbin Medical University published the most articles ( n=25). Among international research institutions, North South University ( n=9) and University of Malaya ( n=9) led in publication output. A total of 67 core authors were identified in Chinese literature and 194 in the English literature. Analysis of high-frequency keywords showed that the research topics could be summarized as research types, occurrence mechanisms, negative effects, high-risk precursors, intervention strategies, negative effects and population differences. Chinese Nursing Research ( n=40) and Journal of Nursing Management ( n=186) published the most Chinese and English articles. Conclusions:The amount of research on workplace violence among nurses has generally increased in recent years. The mechanisms of occurrence, high-risk precursors, and intervention strategies are important research directions. It is still necessary to further deepen the research content in the future.

With the increasing aging population in China and rising incidence rates of diseases such as cancer and cardiovascular conditions, the demand for palliative care services continues to grow. In recent years, the integration of artificial intelligence and medical disciplines has advanced significantly, with machine learning research and applications in the palliative care field progressing steadily. This paper reviews the overview of machine learning, its applications in palliative care, and effectiveness evaluations. It also discusses existing limitations in current research and provides recommendations for future studies. The aim is to assist healthcare professionals in improving palliative care services and offer valuable insights for the development of palliative care in China.

Objective:To investigate the value of a multi-parameter MRI nomogram model in evaluating the recurrence risk of hormone receptor (HR)-positive breast cancer.Methods:This study was a retrospective cross-sectional study. A retrospective analysis was conducted on the clinicopathological data (age, menopausal status, axillary lymph node metastasis, etc.) and imaging data of 220 patients with HR-positive breast cancer who underwent breast MRI examination and were pathologically confirmed at the Second Affiliated Hospital of Nantong University from January 2018 to December 2023. All patients underwent preoperative MRI examinations. Their MRI features were analyzed, and the maximum diameter of the lesion and the apparent diffusion coefficient (ADC) value were measured. Finally, the clinical treatment score (CTS5 score) after 5 years was calculated, and all patients were divided into a low recurrence risk (CTS5 score 3.13 points) and a medium to high recurrence risk (CTS5 score≥3.13 points) group. The patients were followed up through the electronic medical record system or by phone until December 31, 2024 to determine recurrence status. The patients were divided into the recurrence group and the non-recurrence group. The differences in clinicopathological data, MRI features and CTS5 scores between the recurrence group and the non-recurrence group were compared using independent sample t-tests, Mann-Whitney U tests or χ2 tests. Indicators with P0.05 in the univariate analysis were included in the multivariate logistic regression to screen the independent risk factors for predicting the recurrence of HR receptor-positive breast cancer, and a nomogram was constructed to establish the nomogram model. The receiver operating characteristic curves and the area under the curve (AUC) were used to evaluate the efficacy of the nomogram model in predicting the postoperative recurrence risk of patients with HR-positive breast cancer. The variance inflation factor (VIF) was used to evaluate the multicollinearity among independent variables. Calibration curves and decision curve analysis (DCA) were used to assess the fit and net clinical benefit of the nomogram model. Results:Among 220 patients with HR-positive breast cancer, 196 cases were in the non-recurrence group and 24 cases were in the recurrence group. There were statistically significant differences in the maximum diameter of the lesion, axillary lymph node metastasis, ADC value, CTS5 grouping, and CTS5 score between the recurrence group and the non-recurrence group ( P0.05). Multivariate logistic regression analysis showed that the maximum diameter of the lesion ( OR=1.110, 95% CI 1.169-1.503, P0.001), ADC value ( OR=0.993, 95% CI 0.993?0.989, P0.001), and axillary lymph node metastasis ( OR=8.842; 95% CI 2.120?36.884, P=0.003) were independent factors influencing postoperative recurrence in patients with HR-positive breast cancer, and a nomogram model was constructed based on this. VIF analysis showed that no significant multicollinearity was detected among the variables (VIF5). The AUC value of the nomogram model for predicting postoperative recurrence in patients with HR-positive breast cancer was 0.868 (95% CI 0.794-0.942), the sensitivity was 0.875, and the specificity was 0.781. The calibration curve showed that the prediction curve of this model for predicting postoperative recurrence in HR-positive breast cancer patients was basically consistent with the ideal curve trend. DCA showed that this model had a relatively high clinical benefit within the threshold probability range of 0.01% to 90.00%. Conclusion:The nomogram constructed based on multi-parameter MRI features can predict the postoperative recurrence risk of HR-positive breast cancer patients, with good consistency and predictive ability.

Objective:To compare the current situation of research on workplace violence (WPV) among nurses at home and abroad, providing directions for further research.Methods:Research on WPV among nurses published in PubMed, Web of Science, EBSCO, China national knowledge infrastructure, Wanfang, and VIP databases from January 1, 2003 to October 14, 2023 were searched and screened, using visualization software CiteSpace and VOSviewer to analyze the distribution and correlation of countries, authors, institutions and keywords of the included studies.Results:A total of 1 082 Chinese articles and 2 770 English articles were included. From 2003 to 2023, the annual publication volume of research on nurse WPV showed a continuous upward trend in both Chinese and English literature. Among domestic institutions, Harbin Medical University published the most articles ( n=25). Among international research institutions, North South University ( n=9) and University of Malaya ( n=9) led in publication output. A total of 67 core authors were identified in Chinese literature and 194 in the English literature. Analysis of high-frequency keywords showed that the research topics could be summarized as research types, occurrence mechanisms, negative effects, high-risk precursors, intervention strategies, negative effects and population differences. Chinese Nursing Research ( n=40) and Journal of Nursing Management ( n=186) published the most Chinese and English articles. Conclusions:The amount of research on workplace violence among nurses has generally increased in recent years. The mechanisms of occurrence, high-risk precursors, and intervention strategies are important research directions. It is still necessary to further deepen the research content in the future.

With the increasing aging population in China and rising incidence rates of diseases such as cancer and cardiovascular conditions, the demand for palliative care services continues to grow. In recent years, the integration of artificial intelligence and medical disciplines has advanced significantly, with machine learning research and applications in the palliative care field progressing steadily. This paper reviews the overview of machine learning, its applications in palliative care, and effectiveness evaluations. It also discusses existing limitations in current research and provides recommendations for future studies. The aim is to assist healthcare professionals in improving palliative care services and offer valuable insights for the development of palliative care in China.

To evaluate the effects of abdominal belts in colonoscopy for patients with low body mass index (BMI) (BMI<18.5 kg/m2) or a history of abdominal surgery, a prospective, randomized, single-blind study was conducted on colonoscopy outpatients. Patients with low BMI or a history of abdominal surgery who underwent colonoscopy at the Second Affiliated Hospital of Soochow University from January 2018 to January 2022 were enrolled. The patients were divided into the abdominal belts group and non-abdominal belts group according to whether they used abdominal belts. Differences between the two groups were compared in terms of cecal intubation time, length of colonoscope intubation into the cecum, patient repositioning, abdominal pressure, and degree of abdominal distension. A total of 296 patients (98 low BMI patients and 198 patients with a history of abdominal surgery) were enrolled, 148 in each group. The results showed that cecal intubation time (4.35±1.85 min VS 7.99±3.86 min, t=35.624, P<0.001) and length of colonoscope intubation into the cecum (72.03±10.35 cm VS 86.42±17.71 cm, t=38.442, P<0.001) were lower in the abdominal belts group, compared with those of the non-abdominal belts group. The percentage of patients requiring repositioning [18.9% (28/148) VS 71.6% (106/148), χ2=82.959, P<0.001] and abdominal pressure [6.1% (9/148) VS 52.7% (78/148), χ2=77.504, P<0.001] in the abdominal belts group were significantly lower than those in the non-abdominal belts group. There were significant differences in the degree of abdominal distension during and after colonoscopy ( P<0.001). In conclusion, the use of abdominal belts significantly improves the efficiency and effects of colonoscope intubation in difficult colonoscopy patients with low BMI and a history of abdominal surgery.

Objective To study the effects of Danggui-Chuanxiong herb pair medicine on vasoactive substances,adhesion factors,inflammatory factors,and VEGF-PI3K-AKT/NF-κB signaling pathways,in order to elucidate the mechanism of Danggui-Chuanxiong herb pair on the treatment of ischemic stroke(IS).Methods The oxygen glucose deprivation/reoxygenation(OGD/R)model of human umbilical vein endothelial cells(HUVEC)was constructed,and the cell viability was detected by cell proliferation kit(CCK-8 method)to explore the optimal modeling time of seven components;The release of lactate dehydrogenase(LDH)was detected by cytotoxicity kit;The expression of related cytokines was detected by enzyme-linked immunosorbent assay(ELISA);The mRNA expression of key proteins in the signaling pathway was detected by reverse transcription-polymerase chain reaction(RT-PCR).Results Reoxygenation after 6 h of oxygen-glucose deprivation of HUVEC is the best modeling time.High-dose chlorogenic acid group,ferulic acid group,senkyunolide H,low-dose and medium-dose butylidenephthalide group,medium-dose and high-dose senkyunolide A and ligustilide groups significantly decreased LDH leakage rate(P<0.05,P<0.01);The expression of IL-6 in the cells of the partial dose group of chlorogenic acid,caffeic acid,butenylphthalide,senkyunolide H and senkyunolide A was significantly increased,the expression of IL-1 in the cells of the partial dose group of chlorogenic acid,ferulic acid and senkyunolide A was significantly decreased,the expression of VEGF,ICAM-1 and VCAM-1 in the cells of the partial dose group of chlorogenic acid,ferulic acid and senkyunolide H was significantly decreased,the expression of NF-κB in the cells of the partial dose group of chlorogenic acid,ferulic acid,senkyunolide H and ligustilide was significantly decreased,the expression of PAI-1 in the cells of ferulic acid and senkyunolide H partial dose group decreased significantly(P<0.05,P<0.01);The mRNA relative expression levels of ERK,VEGF,NF-κB,VEGFR2 and MMP9 were significantly down-regulated in the cells of chlorogenic acid,ferulic acid,caffeic acid,butylidenephthalide and senkyunolide A partial dose group,while the mRNA relative expression levels of AKT were significantly up-regulated in the cells of senkyunolide H and senkyunolide A partial dose groups(P<0.05,P<0.01).Conclusion The medicinal components of Danggui-Chuanxiong herb pair may play a role in IS by inhibiting the mRNA expression of adhesion factor,inflammatory factor and key protein of VEGF-PI3K-AKT/NF-κB signaling pathway in HUVEC.

Fibromyalgia syndrome （FMS） is a refractory， chronic non-articular rheumatic disease characterized by widespread pain throughout the body， for which there are no satisfactory therapeutic drugs or options. There are rich Chinese medical therapies， and some non-drug therapies， such as acupuncture， Tai Chi， and Ba-Duan-Jin， have shown satisfactory efficacy and safety and definite advantages of simultaneously adjusting mind and body. FMS is taken as a disease responding specifically to traditional Chinese medicine （TCM） by the National Administration of Traditional Chinese Medicine in 2018. In order to clarify the research progress in FMS and the clinical advantages of TCM/integrated Chinese and Western medicine， the China Academy of Chinese Medicine organized a seminar for nearly 20 experts in Chinese and Western medicine， including rheumatology， psychology， acupuncture and moxibustion， and encephalopathy， with the topic of difficulties in clinical diagnosis and treatment of FMS and advantages of TCM and Western medicine. The recommendations were reached on the difficulties in early diagnosis and solutions of FMS， mitigation of common non-specific symptoms， preferential analgesic therapy， TCM pathogenesis and treatment advantages， and direction of treatment with integrated Chinese and Western medicine. FMS is currently facing the triple dilemma of low early correct diagnosis， poor patient participation， and unsatisfactory benefit from pure Western medicine treatment. To solve the above problems， this paper suggests that rheumatologists should serve as the main diagnostic force of this disease， and they should improve patient participation in treatment decision-making， implement exercise therapy， and fully utilize the holistic and multidimensional features of TCM， which is effective in alleviating pain， improving mood， and decreasing adverse events. In addition， it is suggested that FMS treatment should rely on both TCM and Western medicine and adopt multidisciplinary joint treatment， which is expected to improve the standard of diagnosis and treatment of FMS in China.

ObjectiveTo achieve high-dimensional prediction of class imbalanced of adverse drug reaction（ADR） of traditional Chinese medicine（TCM） and to classify and identify risk factors affecting the occurrence of ADR based on the post-marketing safety data of TCM monitored centrally in real world hospitals. MethodThe ensemble clustering resampling combined with regularized Group Lasso regression was used to perform high-dimensional balancing of ADR class-imbalanced data， and then to integrate the balanced datasets to achieve ADR prediction and the risk factor identification by category. ResultA practical example study of the proposed method on a monitoring data of TCM injection performed that the accuracy of the ADR prediction， the prediction sensitivity， the prediction specificity and the area under receiver operating characteristic curve（AUC） were all above 0.8 on the test set. Meanwhile， 40 risk factors affecting the occurrence of ADR were screened out from total 600 high-dimensional variables. And the effect of risk factors on the occurrence of ADR was identified by classification weighting. The important risk factors were classified as follows：past history， medication information， name of combined drugs， disease status， number of combined drugs and personal data. ConclusionIn the real world data of rare ADR with a large amount of clinical variables， this paper realized accurate ADR prediction on high-dimensional and class imbalanced condition， and classified and identified the key risk factors and their clinical significance of categories， so as to provide risk early warning for clinical rational drug use and combined drug use， as well as scientific basis for reevaluation of safety of post-marketing TCM.