Objective To analyze the clinical intervention effect of multi-disciplinary team (MDT) nursing mode on patients after transcatheter aortic valve implantation (TAVI). Methods A total of 89 patients who were admitted to our hospital and underwent TAVI surgery from April to December 2021 were selected, including 64 males and 25 females, with an average age of 64.7±11.8 years. The subjects were divided into a MDT intervention group (n=42) and a control group (n=47) according to different postoperative nursing intervention methods. Clinical effectivenesses were compared between the two groups. Results The left ventricular ejection fraction in the two groups significantly increased on the 7th day after the operation, and the increase in the MDT intervention group was more obvious, with no statistical difference between the two groups (P=0.14). On the 7th day after surgery, forced vital capacity/predicated value and forced expiratory volume in one second/predicated value significantly decreased, and decreased more significantly in the control group than those in the MDT intervention group with statistical differences (P=0.01). The ICU stay time (P=0.01), hospital stay time (P<0.01) and total postoperative pulmonary complications rate (P=0.03) in the MDT intervention group were significantly shorter or lower than those in the control group The evaluation results of the anxiety and depression status of the patients before and after nursing intervention showed that the scores of anxiety and depression in the two groups were significantly lower than before, and the scores of each scale in the MDT intervention group were lower. The score of quality of life of the two groups significantly improved at the end of 6 months after surgery, and in the MDT intervention group it was significantly higher than that in the control group (P=0.02). Conclusion MDT intervention mode can promote the rapid recovery of patients after TAVI, effectively reduce the risk of postoperative pulmonary complications, and improve the postoperative quality of life.
ObjectiveTo investigate the negative emotions of patients before cardiac surgery in West China Hospital in order to analyze the related factors.MethodsThe Huaxi emotional-distress index (HEI), a screening tool for mood disorders developed by the Mental Health Center of West China Hospital, was used for preoperative psychological evaluation of 1 968 adult patients hospitalized in cardiac surgery from March 2016 to July 2014. There were 835 males and 1 133 females at age of 49±13 years.Results Fifty-one patients (2.6%) had negative emotions, among whom 6 patients were screened for suicide risk. After intervention, none of them had serious consequences caused by adverse emotions, such as automatic discharge from hospital, avoidance of surgery and suicide.ConclusionThis study found that most of the cardiac surgery patients in West China Hospital have good psychological status before surgery, and a few suffered from negative emotions. “Huaxi emotional-distress index” is simple, effective and worth promoting.
The result of the emotional state induced by music may provide theoretical support and help for assisted music therapy. The key to assessing the state of emotion is feature extraction of the emotional electroencephalogram (EEG). In this paper, we study the performance optimization of the feature extraction algorithm. A public multimodal database for emotion analysis using physiological signals (DEAP) proposed by Koelstra et al. was applied. Eight kinds of positive and negative emotions were extracted from the dataset, representing the data of fourteen channels from the different regions of brain. Based on wavelet transform, δ, θ, α and β rhythms were extracted. This paper analyzed and compared the performances of three kinds of EEG features for emotion classification, namely wavelet features (wavelet coefficients energy and wavelet entropy), approximate entropy and Hurst exponent. On this basis, an EEG feature fusion algorithm based on principal component analysis (PCA) was proposed. The principal component with a cumulative contribution rate more than 85% was retained, and the parameters which greatly varied in characteristic root were selected. The support vector machine was used to assess the state of emotion. The results showed that the average accuracy rates of emotional classification with wavelet features, approximate entropy and Hurst exponent were respectively 73.15%, 50.00% and 45.54%. By combining these three methods, the features fused with PCA possessed an accuracy of about 85%. The obtained classification accuracy by using the proposed fusion algorithm based on PCA was improved at least 12% than that by using single feature, providing assistance for emotional EEG feature extraction and music therapy.
ObjectiveTo explore the effect of family-school-hospital application in continuous nursing care for children with epilepsy. Methods120 children with epilepsy admitted to Children's Hospital Affiliated to Jiangnan University from January 2021 to October 2022 were randomly divided into two groups, each with 60 cases. The control group received routine care, while the experimental group received family-school-hospital continuous care. Compare the awareness of epilepsy knowledge, disease control effectiveness, medication compliance, negative emotions, physical and mental status, and quality of life before and after nursing between the families of two groups of children with epilepsy. ResultsAfter 2 months of nursing care, the scores of family members' knowledge of epilepsy in the experimental group were higher than the control group (P<0.05). The effect of disease control in the experimental group was better the control group (P<0.05). The drug compliance of the experimental group was higher than the control group (P<0.05). The quality of life score in the intervention group was higher than the control group (P<0.05). ConclusionThe application of family-school-hospital in the continuous care of children with epilepsy can improve their family members' awareness of epilepsy knowledge, effectively control the disease, improve medication compliance, improve negative emotions and physical and mental conditions, and thus improve the quality of life of children.
ObjectiveTo investigate the job satisfaction, emotional state and related factors of medical staff participating in online consultation of West China Internet Hospital during the COVID-19 epidemic.MethodsThrough literature review and expert consultation (Delphi method), the questionnaire was developed, and the online consulting medical staff of West China Hospital of Sichuan University were invited to conduct the questionnaire survey from 26 January to 19 June 2020, and finally the statistical analysis was summarized.ResultsA total of 132 valid questionnaires were retrieved. Of the 132 subjects, 127 people (96.2%) expressed satisfaction or special satisfaction with the online consulting office format; 103 respondents (78.0%) said that online consulting did not affect or completely did not affect the work and life; 81 people (61.4%) consulted online more than 5 days a week, and 108 people (81.8%) worked within 2 hours a day; the vast majority (97.7%) of the research subjects were satisfied with the content of the training materials and the related support work of the coordination group. Only 29 (22.0%) of the study participants believed that the epidemic caused negative emotions, mainly due to the severity of the epidemic.ConclusionThe online consulting medical staff are satisfied with the office form, training materials and coordination work group of the COVID-19 epidemic, and think that it does not affect their work and life. 22.0% of medical staff have negative emotions, and the severity of the epidemic is the main reason.
Emotion recognition will be prosperious in multifarious applications, like distance education, healthcare, and human-computer interactions, etc. Emotions can be recognized from the behavior signals such as speech, facial expressions, gestures or the physiological signals such as electroencephalogram and electrocardiogram. Contrast to other methods, the physiological signals based emotion recognition can achieve more objective and effective results because it is almost impossible to be disguised. This paper introduces recent advancements in emotion research using physiological signals, specified to its emotion model, elicitation stimuli, feature extraction and classification methods. Finally the paper also discusses some research challenges and future developments.
ObjectiveTo examine the effect of preoperative adverse emotion on rehabilitation outcomes in lung cancer patients undergoing thoracoscopic major pulmonary resection.MethodsWe retrospectively analyzed the clinical data of 1 438 patients with lung cancer who underwent thoracoscopic lobectomy and segmentectomy in West China Hospital of Sichuan University from February 2017 to July 2018 including 555 males and 883 females. All patients were assessed by Huaxi emotional-distress index scoring, and were divided into three groups including a non-negative emotion group, a mild negative emotion group, and a moderate-severe negative emotion group. All patients underwent thoracoscopic lobectomy or segmentectomy plus systematic lymph node dissection or sampling. The volume of postoperative chest drainage, postoperative lung infection rate, time of chest tube intubation and postoperative duration of hospitalization were compared among these three groups.ResultsThere were different morbidities of adverse emotion in age, sex, education level and smoking among patients before operation (P<0.05). Univariate analysis showed that there was no statistical difference in the duration of indwelling drainage tube, drainage volume, postoperative pulmonary infection rate or the incidence of other complications among these three groups, but the duration of hospitalization in the latter two groups was less than that in the first group with a statistical difference (P<0.05). After correction of confounding factors by multiple regression analysis, there was no statistical difference among the three groups.ConclusionYoung patients are more likely to develop bad emotions, women are more likely to develop serious bad emotions, highly educated patients tend to develop bad emotions, and non-smoking patients tend to develop bad emotions. There is no effect of preoperative adverse emotions on the rapid recovery of lung cancer patients after minimally invasive thoracoscopic surgery.
Fear emotion is a typical negative emotion that is commonly present in daily life and significantly influences human behavior. A deeper understanding of the mechanisms underlying negative emotions contributes to the improvement of diagnosing and treating disorders related to negative emotions. However, the neural mechanisms of the brain when faced with fearful emotional stimuli remain unclear. To this end, this study further combined electroencephalogram (EEG) source analysis and cortical brain network construction based on early posterior negativity (EPN) analysis to explore the differences in brain information processing mechanisms under fearful and neutral emotional picture stimuli from a spatiotemporal perspective. The results revealed that neutral emotional stimuli could elicit higher EPN amplitudes compared to fearful stimuli. Further source analysis of EEG data containing EPN components revealed significant differences in brain cortical activation areas between fearful and neutral emotional stimuli. Subsequently, more functional connections were observed in the brain network in the alpha frequency band for fearful emotions compared to neutral emotions. By quantifying brain network properties, we found that the average node degree and average clustering coefficient under fearful emotional stimuli were significantly larger compared to neutral emotions. These results indicate that combining EPN analysis with EEG source component and brain network analysis helps to explore brain functional modulation in the processing of fearful emotions with higher spatiotemporal resolution, providing a new perspective on the neural mechanisms of negative emotions.
Objective To analyze and explore positive emotional experiences of patients, in order to provide reference for improving the medical services. Methods Using NVivo software, praise letters from a tertiary hospital in Guangdong in 2020 and 2021 were used as the research object for three-level coding. The positive emotional experiences of patients were explored through tools such as analytic hierarchy process and node item map. Results A total of 8601 patient praise letters were received, and after screening, a total of 8128 valid texts were obtained. In 2020, there were 2570 patient praise letters, including 69 from the emergency department, 638 from the outpatient department, and 1863 from the inpatient department. In 2021, there were 5558 patient praise letters, including 203 from the emergency department, 2071 from the outpatient department, and 3284 from the inpatient department. The most praise letters were from the inpatient department, with a total of 5147 letters (63.3%). There were 2709 letters (33.3%) from outpatient department, and 272 letters (3.3%) from emergency department. The classification of patient praise letters showed that patient praise for the process and individuals were most common (77.4%). After step-by-step encoding, the valid text formed 36 third level nodes, 8 second level nodes, and 3 first level nodes. Patient praise letters mainly focused on emotional evaluation at the first level node, followed by emotional expression and emotional response. Word frequency analysis showed that in terms of positive emotional experiences, the word “thank you” had the highest frequency among patients. In terms of patient perception of service, the term “patience” had the highest frequency. Conclusions When patients express praise for medical services, they pay more attention to the personal performance of medical staff and the experience of the service process compared to the final result. In the process of hospital management, the emotions of patients should be fully considered.
Objective To evaluate the changes in depressive symptoms and emotional responses in obstructive sleep apnea (OSA) patients after six months of continuous positive airway pressure (CPAP) therapy. Methods From June 2021 to December 2023, adult patients diagnosed with OSA at our hospital who were recommended for CPAP therapy as a first-line treatment were recruited. Demographic data (age, body mass index, gender), oxygen desaturation index, maximum duration of apnea and maximum duration of apnea were recorded. The patients were divided into a CPAP group and a non-CPAP group according to whether they were compliant to CPAP treatment. All patients completed questionnaires (including CES-D, DERS, ERS, and ESS) at 0, 1, 2, 4, and 6 months. Differences in general data and questionnaire results were compared between the two groups. Results The patients in the CPAP group showed significantly lower levels of depression and daytime sleepiness at 1, 2, 4, and 6 months compared with the non-CPAP group, with statistically significant differences (all P<0.05). Additionally, the CPAP group exhibited significantly lower scores in emotional responses and difficulties in emotion regulation across the same time points, with statistically significant differences (all P<0.05). In the non-CPAP group, increases in the apnea hypopnea index (AHI) and worsening emotional responses were key factors contributing to the exacerbation of depressive symptoms in OSA patients, with statistically significant differences (P<0.05). Conclusions CPAP therapy significantly improves depressive symptoms, emotional responses, and emotional regulation in OSA patients. Increases in the AHI and worsening emotional responses are primary factors leading to the worsening of depressive symptoms in OSA patients.