Objective To study the application effect of Snyder hope theory combined with Satir model in the rehabilitation therapy of young and middle-aged patients with stroke. Methods A total of 224 young and middle-aged patients with stroke admitted to Zhongshan Hospital of Fudan University between August 2018 and August 2020 were divided into four groups (control group, Satir group, Snyder group, and combined group) according to the random number table method by taking admission time as sequence. All patients were given rehabilitation training on the basis of conventional treatment, and the Satir group was given group guidance of Satir model, the Snyder group was given hope therapy based on Snyder hope theory, and the combined group was given intervention combined Snyder hope theory with Satir model. All patients were continuously treated for six weeks. The scores of Herth Hope Index (HHI), Self-perceived Burden Scale (SPBS), exercise rehabilitation willingness questionnaire, Health Promoting Lifestyle Profile Ⅱ (HPLP Ⅱ), and Simplified Coping Style Questionnaire (SCSQ) were compared among the four groups before and after intervention. Results There were 53, 52, 54, and 52 patients enrolled in the control group, the Satir group, the Snyder group, and the combined group, respectively. The differences among the four groups in basic information such as sex, age, and type of stroke and the scores of the above scales before intervention were not statistically significant (P>0.05). After intervention, the total scores of HHI scale (27.65±6.34, 30.54±6.85, 32.79±7.12, 35.08±7.63), scores of exercise rehabilitation willingness (39.85±8.16, 40.52±7.93, 40.17±8.25, 43.81±7.46), total scores of HPLP Ⅱ scale (149.87±26.08, 159.32±26.73, 165.89±28.01, 173.18±28.54), and scores of positive coping style of SCSQ scale (19.65±5.08, 22.46±5.29, 25.04±4.91, 28.45±5.12) of the four groups significantly increased compared with those before intervention (P<0.05), while the total scores of SPBS scale (27.35±4.92, 23.74±5.02, 25.16±4.98, 21.49±5.27) and scores of negative coping style of SCSQ scale (4.83±1.25, 3.71±1.02, 3.94±1.08, 4.13±0.96) significantly decreased compared with those before intervention (P<0.05); the scores of HHI scale, exercise rehabilitation willingness, HPLP Ⅱ scale, and positive coping style of SCSQ scale of the combined group were higher than those of the other three groups (P<0.05), while the score of SPBS scale was lower than that of the other three groups (P<0.05). Conclusions Snyder hope theory combined with Satir model for rehabilitation therapy of young and middle-aged patients with stroke can help to improve the hope level, reduce the self-perceived burden, and improve the exercise rehabilitation willingness, health behaviors and coping styles. In addition, it is of great significance for promoting the rehabilitation of patients.
Present study used diffusion tensor image and tractography to construct brain white matter networks of 15 cerebral palsy infants and 30 healthy infants that matched for age and gender. After white matter network analysis, we found that both cerebral palsy and healthy infants had a small-world topology in white matter network, but cerebral palsy infants exhibited abnormal topological organization: increased shortest path length but decreased normalize clustering coefficient, global efficiency and local efficiency. Furthermore, we also found that white matter network hub regions were located in the left cuneus, precuneus, and left posterior cingulate gyrus. However, some abnormal nodes existed in the frontal, temporal, occipital and parietal lobes of cerebral palsy infants. These results indicated that the white matter networks for cerebral palsy infants were disrupted, which was consistent with previous studies about the abnormal brain white matter areas. This work could help us further study the pathogenesis of cerebral palsy infants.
ObjectiveThis study aimed to revise the perioperative recovery scale for integrative medicine (PRSIM) based on item response theory (IRT). MethodsUnder the guidance of IRT, a total of 349 patient data collected during the development of the original version of PRSIM at Guangdong Provincial Hospital of Chinese Medicine were used. Principal component analysis was performed using SPSS 18.0 software to test the unidimensionality. The R language was utilized for parameter estimation, including discrimination coefficient, difficulty parameters and information content, as well as drawing item characteristic curves to assess item quality and estimate item functioning differences. A comprehensive screening process was carried out by combining expert consultations, patient evaluations, and discussions within a core group. ResultsThe degree of discrimination of all items ranged from ?0.535 to 2.195. The difficulty coefficient ranged from ?10.343 to 5.461, and the average information content of all items ranged from 0.043 to 1.075. Based on the criteria for parameter selection, nine items were retained. The results of expert consultations indicated the removal of 5 items and the modification of 7 items. After discussion within the core group, a final decision was made to remove 5 items. ConclusionBased on a synthesis of IRT and expert consultation feedback, and following discussions within the core group, a revised version comprising 15 items is retained and modified from the original 20 items.
Regurgitation is an abnormal condition happens when left ventricular assist devices (LVADs) operated at a low speed, which causes LVAD to fail to assist natural blood-pumping by heart and thus affects patients’ health. According to the degree of regurgitation, three LVAD’s regurgitation states were identified in this paper: no regurgitation, slight regurgitation and severe regurgitation. Regurgitation index (RI), which is presented based on the theory of dynamic closed cavity, is used to grade the regurgitation of LVAD. Numerical results showed that when patients are in exercising, resting and sleeping state, the critical speed between slight regurgitation and no regurgitation are 6 650 r/min, 7 000 r/min and 7 250 r/min, respectively, with corresponding RI of 0.401, 0.300 and 0.238, respectively. And the critical speed between slight regurgitation and severe regurgitation are 5 500 r/min, 6 000 r/min and 6 450 r/min, with corresponding RI of 0.488, 0.359 and 0.284 respectively. In addition, there is a negative relation correction between RI and rotational speed, so that grading the LVAD’s regurgitation can be achieved by determining the corresponding critical speed. Therefore, the detective parameter RI based on the signal of flow is proved to be able to grade LVAD’s regurgitation states effectively and contribute to the detection of LVAD’s regurgitation, which provides theoretical basis and technology support for developing a LVADs controlling system with high reliability.
Objective To investigate the differences in the topology of functional brain networks between populations with good spatial navigation ability and those with poor spatial navigation ability. Methods From September 2020 to September 2021, 100 college students from PLA Army Border and Coastal Defense Academy were selected to test the spatial navigation ability. The 25 students with the highest spatial navigation ability were selected as the GN group, and the 25 with the lowest spatial navigation ability were selected as the PN group, and their resting-state functional MRI and 3D T1-weighted structural image data of the brain were collected. Graph theory analysis was applied to study the topology of the brain network, including global and local topological properties. Results The variations in the clustering coefficient, characteristic path length, and local efficiency between the GN and PN groups were not statistically significant within the threshold range (P>0.05). The brain functional connectivity networks of the GN and PN groups met the standardized clustering coefficient (γ)>1, the standardized characteristic path length (λ)≈1, and the small-world property (σ)>1, being consistent with small-world network property. The areas under curve (AUCs) for global efficiency (0.22±0.01 vs. 0.21±0.01), γ value (0.97±0.18 vs. 0.81±0.18) and σ value (0.75±0.13 vs. 0.64±0.13) of the GN group were higher than those of the PN group, and the differences were statistically significant (P<0.05); the between-group difference in AUC for λ value was not statistically significant (P>0.05). The results of the nodal level analysis showed that the AUCs for nodal clustering coefficients in the left superior frontal gyrus of orbital region (0.29±0.05 vs. 0.23±0.07), the right rectus gyrus (0.29±0.05 vs. 0.23±0.09), the middle left cingulate gyrus and its lateral surround (0.22±0.02 vs. 0.25±0.02), the left inferior occipital gyrus (0.32±0.05 vs. 0.35±0.05), the right cerebellar area 3 (0.24±0.04 vs. 0.26±0.03), and the right cerebellar area 9 (0.22±0.09 vs. 0.13±0.13) were statistically different between the two groups (P<0.05). The differences in AUCs for degree centrality and nodal efficiency between the two groups were not statistically significant (P>0.05). Conclusions Compared with people with good spatial navigation ability, the topological properties of the brains of the ones with poor spatial navigation ability still conformed to the small-world network properties, but the connectivity between brain regions reduces compared with the good spatial navigation ability group, with a tendency to convert to random networks and a reduced or increased nodal clustering coefficient in some brain regions. Differences in functional brain network connectivity exist among people with different spatial navigation abilities.
Developmental and epileptic encephalopathy (DEE) is a group of diseases that severely affects the neurological development of children, characterized by frequent seizures and significant neurodevelopmental impairments. These diseases not only impact the quality of life of affected children but also impose a heavy burden on families and society. In recent years, the development of brain network theory has provided a new perspective on understanding the pathological mechanisms of DEE, especially the role of structural and functional brain networks in the process of epilepsy. This review systematically summarized the research progress of structural and functional brain networks in DEE, highlighted their importance in seizure activity, disease progression, and prognosis evaluation.
Objective To construct an intervention program for postoperative fear of falling in elderly patients with hip fracture based on cognitive behavioral theory. Methods Based on cognitive behavioral theory and literature review, an initial draft of intervention plan for postoperative fear of falling in elderly patients with hip fracture was constructed. From January to March 2025, after two rounds of expert consultations and revisions, the final plan was formed. Results A total of 16 experts across the country were invited to participate in two rounds of Delphi expert consultations, covering areas such as orthopedic clinical nursing, orthopedic clinical medicine, nursing education, nursing management, rehabilitation therapy, and psychological therapy. The active participation rates for the two rounds of consultations were 94.12% and 100.00%, respectively. The expert authority coefficients were 0.860 and 0.907, respectively, and the Kendall harmony coefficients were 0.369 and 0.524, respectively. Ultimately, a program composed of 5 primary indicators (fall fear management team, fall fear management goals, fall fear assessment, fall fear intervention measures, and post-intervention effect evaluation), 17 secondary indicators, and 31 tertiary indicators was constructed. Conclusion The intervention program for postoperative fear of falling in elderly patients with hip fracture based on cognitive behavior theory constructed in this study is scientific and operable, which can provide reference and guidance for clinical nursing staff.
As a complex system, the topology of human’s brain network has an important effect on further study of brain’s structural and functional mechanism. Graph theory, a kind of sophisticated analytic strategies, is widely used for analyzing complex brain networks effectively and comparing difference of topological structure alteration in normal development and pathological condition. For the purpose of using this analysis methodology efficiently, it is necessary to develop graph-based visualization software. Thus, we developed VisConnectome, which displays analysis results of the brain network friendly and intuitively. It provides an original graphical user interface (GUI) including the tool window, tool bar and innovative double slider filter, brain region bar, runs in any Windows operating system and doesn’t rely on any platform such as Matlab. When importing the user-defined script file that initializes the brain network, VisConnectome abstracts the brain network to the ball-and-stick model and render it. VisConnectome allows a series of visual operations, such as identifying nodes and connection, modifying properties of nodes and connection such as color and size with the color palette and size double slider, imaging the brain regions, filtering the brain network according to its size property in a specific domain as simplification and blending with the brain surface as a context of the brain network. Through experiment and analysis, we conclude that VisConnectome is an effective visualization software with high speed and quality, which helps researchers to visualize and compare the structural and functional brain networks flexibly.
Objective To investigate the network reorganization and dynamic brain activity in visuospatial neglect (VSN) patients using resting-state electroencephalography (rEEG), and to develop classification models to facilitate its identification. Methods In this retrospective study, stroke patients admitted to the Department of Rehabilitation, Xuanwu Hospital, Capital Medical University between August 2022 and December 2024 were included and divided into VSN (n=22) and non-VSN (n=21) groups based on paper-and-pencil assessments. A healthy control group (n=20) was also recruited. Microstate segmentation and graph-theoretical analysis were applied to rEEG data to extract microstate parameters and topological network features. Four machine learning models (logistic regression, na?ve Bayes, k-nearest neighbors, and decision tree) were built for classification. Results Compared with the non-VSN group, the VSN group showed significantly increased mean duration and time coverage in microstate C, and significantly decreased coverage and occurrence in microstate D. Graph-theoretical analysis revealed higher average clustering coefficients in the VSN group. Degree centrality in the frontal-central regions (C1, CZ) was significantly lower, while that in the parietal-occipital regions (P5, P3, PO7, PO5) was significantly higher than in the non-VSN group. Among the classification models, logistic regression and na?ve Bayes models performed best, with the mean duration of microstate C contributing most to classification performance. Conclusions Patients with VSN exhibit distinct alterations in electroencephalography microstate dynamics and functional network topology. Microstate parameters play a crucial role in distinguishing VSN from non-VSN stroke cases, and combining these features with machine learning offers a promising approach for early identification and personalized intervention of VSN.
Objective To explore the application effect of day surgery nursing based on finite time theory in patients undergoing gastroesophageal reflux surgery. Methods A total of 108 patients undergoing gastroesophageal reflux surgery in Day Surgery Center of the First Affiliated Hospital of Air Force Medical University were enrolled and divided into control group (n=54, routine nursing) and study group (n=54, finite time theory intervention on basis of control group) according to random number table method between May 2023 and May 2025. The scores of Visual Analogue Scale (VAS) for pain before and after surgery, postoperative recovery indexes, total incidence of postoperative complications, scores of Self-rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS) before surgery and discharge, and patients satisfaction in the two groups were compared. Results After surgery, the VAS score in the study group was lower than that in the control group (2.86±0.31 vs. 3.58±0.39, P<0.05). The first leaving bed time, the first time for liquid intake, and the postoperative anal exhaust time in the study group [(6.23±0.68), (4.22±0.53), and (16.78±2.03) h, respectively] were shorter than those in control group [(8.24±1.34), (6.68±0.86), (19.14±2.21) h, respectively; P<0.05]. Before discharge, the scores of SAS and SDS in the study group (49.14±5.11 and 41.26±4.31, respectively) were lower than those in the control group (53.79±5.58 and 49.85±5.06, respectively; P<0.05). The scores of patients satisfaction with daytime medical treatment process, doctor-nurse-patient communication, service attitude of medical staff and health education methods in the study group (91.56±3.58, 93.27±3.24, 92.07±5.37, and 92.68±4.22, respectively) were higher than those in the control group (82.35±4.11, 83.51±5.20, 84.11±4.33, and 81.70±5.41, respectively; P<0.05). There was no significant difference in the total incidence of postoperative complications between the two groups (9.25% vs. 16.67%, P>0.05). Conclusion The day surgery nursing based on finite time theory can effectively alleviate postoperative pain, accelerate postoperative recovery, improve psychological state and nursing satisfaction in patients undergoing gastroesophageal reflux surgery.