Anticipatory anxiety is a negative emotion that arises when individuals encounter potential threats or uncertainties in the future. It is the core symptom of a variety of anxiety disorders, and is closely associated with the occurrence, severity, treatment outcome, and prognosis of anxiety disorders, which has garnered a growing amount of focus in clinical practice. Nevertheless, scientific research on anticipatory anxiety continues to face obstacles such as unclear pathological mechanisms, the absence of simple and consistent self-assessment tools, and effective interventions. To improve understanding of the role of anticipatory anxiety in the diagnosis and treatment of anxiety disorders, this study reviews pertinent domestic and international literature, and briefly introduces the concept, assessment and measurement, activation paradigm, pathological mechanisms, and interventions of anticipatory anxiety.

Objective:To investigate the structural changes in the spinal cord in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) and their relationship with clinical disability.Methods:This study was cross-sectional. A retrospective analysis of clinical and imaging data from 124 patients with MS (MS group), 101 patients with aquaporin-4 antibody-positive NMOSD (NMOSD group), and 110 healthy controls (HC group) from seven medical centers were conducted from January 2018 to October 2021. All subjects underwent 3D T 1WI, and the upper cervical spinal cord cross-sectional area (MUCCA) was segmented and measured. All patients completed the expanded disability status scale (EDSS) assessments at baseline and during follow-up, as well as the baseline 25-foot walk test (T25FW) and the nine-hole peg test (NHPT). Patients were classified into EDSS progression and non-progression groups based on follow-up EDSS scores. Comparisons of MUCCA among the three groups were conducted using analysis of covariance, controlling for age and sex as covariates. Pairwise comparisons between groups were performed using the HSD test. Univariate linear regression and logistic models were employed to identify candidate predictors of baseline clinical disability status or EDSS progression in the MS and NMOSD groups. L1 regularized multivariable linear regression analysis was used to determine independent predictors of baseline clinical disability status or EDSS progression. Independent predictors were then combined to establish a logistic regression model, and the model′s performance in predicting EDSS progression was evaluated using receiver operating characteristic analysis and the area under the curve (AUC). Results:A total of 144 patients completed follow-up EDSS assessments, with a follow-up duration of 3.30 (1.10, 6.42) years, including 82 patients in the MS group and 62 patients in the NMOSD group. Controlling for sex and age as covariates, the overall difference in MUCCA among the MS, NMOSD, and HC groups was statistically significant ( P=0.001). The MUCCA in the MS group was lower than that in the HC group, with a significant difference ( t=-2.54, P=0.007); the MUCCA in the NMOSD group was also lower than that in the HC group, with a significant difference ( t=-2.80, P=0.002). However, the difference in MUCCA between the MS and NMOSD groups was not statistically significant ( t=-0.40, P=0.882). In the MS group, MUCCA was an independent predictor of baseline EDSS score (β=-0.03), baseline T25FW score (β=-0.09), and baseline NHPT score (β=-0.30). In the NMOSD group, MUCCA (β=-0.08), age (β=0.06), and baseline EDSS score (β=-0.43) were independent predictors of EDSS progression, and the logistic regression model incorporating these three factors predicted EDSS progression with an AUC of 0.82. Conclusions:Significant spinal cord atrophy occurs in patients with both MS and NMOSD. Atrophy of the upper cervical spinal cord can predict the degree of disability in MS patients and the progression of clinical disability in NMOSD patients.

Anticipatory anxiety is a negative emotion that arises when individuals encounter potential threats or uncertainties in the future. It is the core symptom of a variety of anxiety disorders, and is closely associated with the occurrence, severity, treatment outcome, and prognosis of anxiety disorders, which has garnered a growing amount of focus in clinical practice. Nevertheless, scientific research on anticipatory anxiety continues to face obstacles such as unclear pathological mechanisms, the absence of simple and consistent self-assessment tools, and effective interventions. To improve understanding of the role of anticipatory anxiety in the diagnosis and treatment of anxiety disorders, this study reviews pertinent domestic and international literature, and briefly introduces the concept, assessment and measurement, activation paradigm, pathological mechanisms, and interventions of anticipatory anxiety.

Objective:To investigate the structural changes in the spinal cord in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) and their relationship with clinical disability.Methods:This study was cross-sectional. A retrospective analysis of clinical and imaging data from 124 patients with MS (MS group), 101 patients with aquaporin-4 antibody-positive NMOSD (NMOSD group), and 110 healthy controls (HC group) from seven medical centers were conducted from January 2018 to October 2021. All subjects underwent 3D T 1WI, and the upper cervical spinal cord cross-sectional area (MUCCA) was segmented and measured. All patients completed the expanded disability status scale (EDSS) assessments at baseline and during follow-up, as well as the baseline 25-foot walk test (T25FW) and the nine-hole peg test (NHPT). Patients were classified into EDSS progression and non-progression groups based on follow-up EDSS scores. Comparisons of MUCCA among the three groups were conducted using analysis of covariance, controlling for age and sex as covariates. Pairwise comparisons between groups were performed using the HSD test. Univariate linear regression and logistic models were employed to identify candidate predictors of baseline clinical disability status or EDSS progression in the MS and NMOSD groups. L1 regularized multivariable linear regression analysis was used to determine independent predictors of baseline clinical disability status or EDSS progression. Independent predictors were then combined to establish a logistic regression model, and the model′s performance in predicting EDSS progression was evaluated using receiver operating characteristic analysis and the area under the curve (AUC). Results:A total of 144 patients completed follow-up EDSS assessments, with a follow-up duration of 3.30 (1.10, 6.42) years, including 82 patients in the MS group and 62 patients in the NMOSD group. Controlling for sex and age as covariates, the overall difference in MUCCA among the MS, NMOSD, and HC groups was statistically significant ( P=0.001). The MUCCA in the MS group was lower than that in the HC group, with a significant difference ( t=-2.54, P=0.007); the MUCCA in the NMOSD group was also lower than that in the HC group, with a significant difference ( t=-2.80, P=0.002). However, the difference in MUCCA between the MS and NMOSD groups was not statistically significant ( t=-0.40, P=0.882). In the MS group, MUCCA was an independent predictor of baseline EDSS score (β=-0.03), baseline T25FW score (β=-0.09), and baseline NHPT score (β=-0.30). In the NMOSD group, MUCCA (β=-0.08), age (β=0.06), and baseline EDSS score (β=-0.43) were independent predictors of EDSS progression, and the logistic regression model incorporating these three factors predicted EDSS progression with an AUC of 0.82. Conclusions:Significant spinal cord atrophy occurs in patients with both MS and NMOSD. Atrophy of the upper cervical spinal cord can predict the degree of disability in MS patients and the progression of clinical disability in NMOSD patients.

Rumination is a pathological habitual thinking pattern commonly observed in various mental disorders. It is closely associated with the severity of symptoms, treatment outcomes, and social functioning outcomes in conditions such as depression, anxiety, post-traumatic stress disorder, and obsessive-compulsive disorder. In recent years, rumination has become a focal point in the clinical diagnosis and treatment of mental disorders. However, research on rumination still faces challenges, including conceptual ambiguity, lack of consistent assessment tools, unclear pathological mechanisms, and a shortage of effective intervention methods. This paper conducts a comprehensive review by examining relevant domestic and international literature to enhance our understanding of rumination across different mental disorders. The review encompasses the concepts, assessments, pathological mechanisms, and intervention methods of rumination, aiming to provide insights and references for the clinical diagnosis and treatment of rumination.

Rumination is a pathological habitual thinking pattern commonly observed in various mental disorders. It is closely associated with the severity of symptoms, treatment outcomes, and social functioning outcomes in conditions such as depression, anxiety, post-traumatic stress disorder, and obsessive-compulsive disorder. In recent years, rumination has become a focal point in the clinical diagnosis and treatment of mental disorders. However, research on rumination still faces challenges, including conceptual ambiguity, lack of consistent assessment tools, unclear pathological mechanisms, and a shortage of effective intervention methods. This paper conducts a comprehensive review by examining relevant domestic and international literature to enhance our understanding of rumination across different mental disorders. The review encompasses the concepts, assessments, pathological mechanisms, and intervention methods of rumination, aiming to provide insights and references for the clinical diagnosis and treatment of rumination.

Humans ; Cardiologists ; Neoplasms/drug therapy* ; Medical Oncology ; Heart ; Oncologists

Objective:To investigate the efficacy of a machine learning model based on radiomics of brain lesions on T 2WI in differentiating multiple sclerosis (MS) from neuromyelitis optica spectrum disorders (NMOSD). Methods:Totally 223 MS and NMOSD patients who were treated from January 2009 to September 2018 in Beijing Tiantan Hospital Affiliated to Capital Medical University, Donghu Branch of the First Affiliated Hospital of Nanchang University, Tianjin Medical University General Hospital, and Xuanwu Hospital of Capital Medical University were analyzed retrospectively, and according to the proportion of 7∶3, 223 patients were completely randomly divided into training set (156 cases) and test set (67 cases). A total of 74 patients with MS and NMOSD who were treated in Huashan Hospital Affiliated to Fudan University and China-Japan Friendship Hospital of Jilin University from January 2009 to September 2018 and in Xianghu Branch of the First Affiliated Hospital of Nanchang University from March 2020 to September 2021 were collected as an independent external validation set. All patients underwent brain cross-sectional MR T 2WI, radiomics features were extracted from T 2WI, and features were selected by max-relevance and min-redundancy and least absolute shrinkage and selection operator algorithms. Then various machine learning classifier models (logistic regression, decision tree, AdaBoost, random forest or support vector machine) were constructed to differentiate MS from NMOSD. The area under curve (AUC) of receiver operating characteristics was used to evaluate the performance of each classifier model in the training set, test set and external validation set. Results:Based on multi-center T 2WI, a total of 11 radiomics features related to the discrimination between MS and NMOSD were extracted and classifier models were constructed. Among them, the random forest model had the best efficiency in distinguishing MS from NMOSD, and its AUC values for distinguishing MS from NMOSD in the training set, test set and external validation set were 1.000, 0.944 and 0.902, with specificity of 100%, 76.9% and 86.0%, and sensitivity of 100%, 92.1% and 79.7%, respectively. Conclusion:The random forest model based on the radiomic features of T 2WI of brain lesions can effectively distinguish MS from NMOSD.

Objective: To explore the current situation of nurses′ working values, working environment and head nurses′ leadership style. To explore the influence factors of nurses′ working environment and head nurse′s leadership style on nurses′ working values. Methods: By applying random stratified sampling, 499 clinical nurses without administrative titles in 6 hospitals were selected. Questionnaires were adopted as the main research tool. Results: Score of nurses′ working values was 3.52 ± 0.56. Score of nurses′ working environment was 3.03 ± 0.44. Score of head nurses′transformational leadership style was 2.70 ± 0.76, and score of head nurses′ transactional leadership style was 2.23 ± 0.47. Working environment, transformational leadership style and transactional leadership style were positively correlated with nurses′ working values (P= 0.452, 0.371, 0.234). Conclusions Working values of nurses in general public hospitals of Changsha city is at moderate level. By improving nurses′ working environment and head nurses adopting positive leadership, and in particular, proposing beneficial measures for improving a solid nursing foundation for quality of care, sufficient human resources and intellectual stimulation, nurses′ working values can be improved.

Objective To study the clinical effects of the Tanreqing injection combined with Danshen-Chuanxiongqin injection for the patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and its effects on plasma NO and endothelin-1 (ET-1) levels. Methods A total of 79 patients with AECOPD in our hospital from May 2014 to January 2017 were enrolled in this study. The subjects were randomly divided into the control group (n=39) and the combined therapy group (n=40). The control group were treated with Tanreqing injection, the combined therapy group were treated with Tanreqing injection combined with Danshen-Chuanxiongqin injection.The two groups were treated for 10 days.The clinical effects of the two groups after treatment were compared. The MPAP, PASP, PADP, PaO2, PaCO2, SaO2, NO and ET-1 of the two groups before and after treatment were compared. Results The total efficacy rate of the combined therapy group was 97.5% (39/40), which was significantly higher than 82.1% (32/39) of the control group (x2=5.178,P=0.023).After treatment,the MPAP(25.19 ± 8.71 mmHg vs.35.28 ± 9.52 mmHg,t=4.917),PASP (44.35 ± 12.26 mmHg vs.57.24 ± 11.17 mmHg,t=4.881),PADP(17.16 ± 4.05 mmHg vs.26.40 ± 3.85 mmHg, t=10.38),PaCO2(42.70 ± 6.31 mmHg vs. 51.44 ± 6.83 mmHg, t=5.910)of the combined therapy group were significantly lower than those of the control group(P<0.05).After treatment,the PaO2(73.95 ± 7.82 mmHg vs. 67.21 ± 7.16 mmHg,t=3.993),SaO2(94.86% ± 5.11% vs.83.63% ± 4.27%,t=10.586)of the combined therapy group were significantly higher than those of the control group (P<0.05). After treatment, the plasma NO (55.82 ± 10.08 μmol/L vs.46.34 ± 8.50 μmol/L,t=4.513)of the combined therapy groupwas significantly higher than the control group(P<0.05)and the plasma ET-1(80.41 ± 8.95 ng/L vs.87.68 ± 9.24 ng/L,t=3.552)of the combined therapy groupwere significantly lower than the control group (P<0.05). Conclusions The Tanreqing injection combined with Danshen-Chuanxiongqin injection showed good efficacy for the patients with AECOPD,and the therapy can reduce the pulmonary arterial hypertension and ET-1, improve the lung tissue oxygen supply and NO release, and improve the cardiopulmonary function.