ObjectiveTo investigate the effect of video-based educational intervention combined with maternal presence on perioperative adverse outcomes in preschool children undergoing general anesthesia， including cooperation in anesthesia induction， perioperative anxiety， pain and agitation during recovery. MethodsA total of 300 preschool children scheduled for general anesthesia in our hospital from June to December 2023 were randomly assigned to control group （n=150） and intervention group （n=150）. The control group received routine recovery care. For the intervention group， in addition to routine recovery care， a preoperative visit was scheduled one day before surgery. During this visit， mothers were guided to watch anesthesia videos with their children. During the waiting period in the operating room and 30 minutes after awakening， the mothers were guided to accompany the children for more than 30 minutes. Recovery conditions were recorded using the surgical anesthesia information system， and the children’s anesthetic induction compliance， perioperative anxiety， pain， and agitation were evaluated and recorded using the modified Yale Preoperative Anxiety Scale （m-YPAS）， the Induction Compliance Scale （ICC）， the Children’s Pain Behavior Scale （FLACC）， and the Pediatric Agitation and Emergence Delirium Scale （PAED）. ResultsOn the preoperative visit day， there were no statistically significant differences in baseline data between the two groups （P > 0.05）. For perioperative anxiety， the m-YPAS scores of the intervention group were significantly lower than those of the control group， both when entering the operating room waiting area （35.27±6.48 vs. 41.79±6.68， P < 0.05） and 30 minutes after postoperative recovery （20.13±7.05 vs. 35.75±9.51， P < 0.05）. In terms of anesthesia induction cooperation， the ICC scores of the intervention group were significantly lower than those of the control group （1.84±0.95 vs. 3.17±0.62， P < 0.05）， and the proportion of good induction cooperation was significantly higher than that of the control group （24.00% vs. 12.67%， P < 0.05）. There was no significant difference in awakening duration between the two groups， but the intervention group had a significantly shorter length of stay in the post-anesthesia care unit than the control group （0.90±0.29 hours vs. 1.29±0.42 hours， P < 0.001）. For perioperative agitation， the PAED scores of the intervention group were significantly lower than those of the control group （entering in the operating room waiting area： 8.5 vs. 9.2， P < 0.05； 30 minutes after postoperative recovery： 4.2 vs. 7.8， P < 0.05）. In terms of pain scores， the FLACC scores of the intervention group were also significantly lower than those of the control group， both when entering the operating room waiting area （ 5.3 vs. 6.7， P < 0.05； 30 minutes after postoperative recovery： 2.1 vs. 4.9， P < 0.05）. ConclusionsVideo-based educational intervention combined with maternal presence reduces the perioperative anxiety， pain and agitation of preschool children undergoing general anesthesia， and improved the compliance of anesthesia induction. It is recommended to promote this intervention measure in clinical practice.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective To summarize the best evidence for perioperative exercise in renal transplant patients and provide evidence-based evidence for clinical staff to perform exercise in renal transplant patients.Methods Evidence-based questions were identified according to the PIPOST model,and computerized searches were conducted on BMJ Best Practice,UpToDate,the World Health Organization,the US National Guidelines,the website of the Chinese Society of Nephrology,the website of the British Renal Association,the website of the American Society of Nephrology,CNKI,the knowledge service platform of Wanfang Data,the Wipo database and other databases for all evidence on perioperative exercise in renal transplant recipients,including clinical guidelines,clinical decision-making,systematic evaluations,evidence summaries,and expert consensus,with a timeframe for searching from the establishment of the database to August 2023.Quality assessment and evidence extraction of the literature were performed independently by 2 nursing graduate students.Results A total of 13 publications were included,including 1 clinical decision,1 guideline,3 expert consensus,and 8 systematic evaluations.A total of 24 pieces of best evidence were summarized in 7 areas:exercise benefits,exercise assessment,preoperative exercise strategies,postoperative exercise strategies,precautions,exercise instruction monitoring,and exercise support.Conclusions This study summarizes the best evidence about perioperative exercise exercise in renal transplantation and provides a reference for standardizing perioperative exercise exercise in renal transplantation.Clinical staff should fully identify the impediments and facilitators of exercise exercise in renal transplant patients,and develop personalized exercise exercise programs based on medical scenarios,patient conditions,and combined with patients'exercise wishes.

To sum up integrative nursing experience of a case with chronic refractory wound formation caused by drug extravasation.The essentials of integrative nursing are:structured nursing intervention of"assessment-management-treatment"based on the Triangle of Wound Assessment;determination of the timing for integrative nursing according to the theory of TCM sores and ulcers;implementation of copper board scraping method to promote circulation of qi and blood;use of Huo-long Comprehensive Moxibustion Therapy to promote muscle regeneration.With the help of the cooperation of the multidisciplinary specialist nursing team,the wound was completely healed after 59 days of integrated traditional Chinese and Western medicine nursing interventions.

Objective:To investigate the effect and of piperine(PIP)on nerve injury in rats with cerebral infarction.Meth-ods:The rat model of cerebral infarction was prepared by modified thread embolism method.The rats were divided into Sham group,Model group,piperine group(PIP group,20 mg/kg piperine),piperine+PKA inhibitor group(PIP+H-89 group,20 mg/kg PIP+5 mg/kg H-89).The rats were scored for neurological impairment,the volume of cerebral infarction,neuronal damage and neuronal apoptosis were observed,and the levels of cAMP,IL-1β and IL-6 in hippocampus and the protein expressions of GFAP,NSE,AC6,PKA,p-CREB,CREB and BDNF were detected.Results:Compared with Sham group,Model group had large cerebral infarction,cerebral in-farction volume,the neurological deficit score,neuronal apoptosis rate,the levels of IL-6 and IL-1β in hippocampus,and number of GFAP positive cells,the positive expression rates of NSE protein increased,the number of Nissl bodies,and the expressions of cAMP,AC6,PKA,p-CREB and BDNF proteins in hippocampus decreased(P<0.05);compared with Model group,cerebral infarc-tion volume,the neurological deficit score,neuronal apoptosis rate,the levels of IL-6 and IL-1β in hippocampus,and number of GFAP positive cells,the positive expression rates of NSE protein in the PIP group decreased,the number of Nissl bodies,and the ex-pressions of cAMP,AC6,PKA,p-CREB and BDNF proteins in hippocampus increased(P<0.05);the effect of piperine in improving nerve injury in rats with cerebral infarction was able to be reversed by H-89.Conclusion:PIP can inhibit the apoptosis of hippocampal neurons,and improve the neural injury induced by cerebral infarction by activating AC/PKA/CREB signal pathway.

Objective Meta-analysis was used to evaluate the effect of the solution-focused brief therapy on im-proving the anxiety and depression status of patients with HIV/AIDS.Methods Computer search of PubMed,Embase,Web of Science,Cochrane Library,CINAHL,PsycINFO,Chinese Biomedical Literature Database,China Na-tional Knowledge Infrastructure,Wanfang Database,CQVIP were conducted,and the search time frame was from the establishment of databases until April 9,2023.There were 2 investigators who independently screened the literature according to inclusion and exclusion criteria,extracted data and performed quality evaluation,and performed Meta-analysis using RevMan 5.4 software.Results A total of 11 publications were included,including 9 randomized controlled trials and 2 quasi-experimental studies,with a total of 1 219 patients with HIV/AIDS.Meta-analysis re-sults showed that solution-focused brief therapy reduced anxiety scores(SMD=-1.89;95%CI:-2.79～-0.99,P＜0.001),depression scores(SMD=-2.45;95%CI:-3.51～-1.39,P＜0.001).Subgroup analysis showed that improved anxiety(SMD=-4.16;95%CI:-7.97～-0.35,P＜0.001),depression(SMD=-5.69;95%CI:-11.20～-0.19,P＜0.001)in pregnant HIV/AIDS patients was significantly better than that in ordinary patients.Conclusion Solution-focused brief therapy is effective in improving anxiety and depression levels in patients with HIV/AIDS,and the application of this model in pregnant patients with HIV/AIDS has a more significant improvement effect,but high-quality,multicenter,large-sample clinical trial studies are needed to further confirm this conclusion in the future.

Objective:To analyze the effect of integrated care model on relocation stress and sense of coherence in caregivers of severe multiple injuries patients after ICU transfer.Methods:From January 2017 to October 2019, 102 caregivers of severe multiple injuries patients in ICU of Liuzhou Worker′s Hospital were selected and divided into control group and observation group by random digits table method,with 51 cases in each group. In the process of ICU transfer the control group received routine nursing, while the observation group carried out integrated care model based on the control group scheme. Before and after ICU transfer, the degree of relocation stress and sense of coherence of caregivers in two groups were evaluated by Family Relocation Stress Scale (FRSS) and Sense of Coherence Scale (SOCS) respectively.Results:The scores of migration preparation dimension, migration satisfaction dimension,caregiver stress dimension and the total scores of FRSS were 17.51 ± 3.46, 4.81 ± 0.48, 11.69 ± 1.82 and 49.91 ± 4.51 in the observation group, which were significantly higher than those in the control group after transfer (13.61 ± 2.83, 3.32 ± 0.53, 9.42 ± 2.17, 39.25 ± 4.01)( t values were 5.12-7.64, all P<0.05). The scores of manage ability dimension, comprehensibility dimension, meaningfulness dimension and the total scores of SOCS were 29.58 ± 4.96, 24.07 ± 2.72, 22.04 ± 3.64 and 75.52 ± 6.80 in the observation group, which were significantly higher than those in the control group (24.34 ± 4.13, 20.50 ± 2.99, 17.19 ± 3.96, 64.80 ± 6.12) after transfer ( t values were 4.51-7.01, all P<0.05). Conclusions:The integrated care model can significantly alleviate relocation stress and promote sense of coherence in caregivers of severemultiple injuriespatients after ICU transfer.

ObjectiveTo analyze the changing trend of cerebrovascular disease burden in Minhang District of Shanghai from 1996 to 2021， and to provide scientific evidence for government to formulate targeted cerebrovascular disease prevention and control strategies. MethodsMortality， years of life lost（YLL）， years of lived with disability（YLD） and disability⁃adjusted life years（DALY） were used to evaluate the burden of cerebrovascular diseases in Minhang District. Joinpoint linear regression was used to analyze the trend of disease burden. ResultsFrom 1996 to 2021， the YLL rate of cerebrovascular diseases in Minhang District showed a downward trend （whole population： APC=-1.69%， t=-6.9， P<0.05）， The YLD rate of cerebrovascular diseases showed a slow upward trend （whole population： APC=1.17%， t=3.5， P<0.05）， The DALY rate of cerebrovascular diseases showed a downward trend， and fluctuated since 2003 （whole population： APC= -1.43%， t=-5.6， P<0.05）. The YLL rate of cerebrovascular diseases in men was higher than that in women， and the YLD rate of cerebrovascular diseases in women was higher than that in men. After 2014， the DALY of cerebrovascular diseases in men was higher than that in women. With the increase of age， the burden of cerebrovascular diseases increased， and the burden of disease increased significantly in the age group above 70. ConclusionThe burden of cerebrovascular diseases in Minhang District is at a high level， and there are differences in age， gender and other aspects. Measures such as screening， intervention and rehabilitation need to be improved to reduce disability and premature death caused by cerebrovascular diseases and to reduce the burden of cerebrovascular diseases on individuals， families and society.

ObjectiveTo screen out the microRNAs (miRNAs) associated with the prognosis of hepatocellular carcinoma (HCC) through data mining of miRNA transcriptome data of HCC downloaded from The Cancer Genome Atlas (TCGA) database, to establish a miRNA risk score model, and to investigate its value in predicting the prognosis of HCC. MethodsThe miRNA expression data and clinical data of HCC samples were downloaded from TCGA database and R language was used to screen out differentially expressed miRNAs between HCC tissue and adjacent tissue, which were randomly divided into training set and testing set after being integrated into clinical data. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed for the training set to screen out the miRNAs associated with the prognosis of HCC, and then a miRNA risk score model was established. The Kaplan-Meier method was used to evaluate the robustness of the model and whether it could predict the prognosis of patients in the same clinical stage. Finally, the receiver operating characteristic (ROC) curve was plotted and the area under the ROC curve (AUC) was calculated to compare the predictive accuracy of the model versus TNM staging in the training set, the testing set, and the entire set. ResultsA total of 300 differentially expressed miRNAs were screened out and the LASSO Cox regression analysis revealed that hsa-miR-139-5p, hsa-miR-1180-3p, hsa-miR-1269b, hsa-miR-3680-3p, hsa-miR-509-3-5p, and hsa-miR-31-5p were associated with the prognosis of HCC. The risk score was calculated for each sample according to the established miRNA risk score model, and the samples were divided into high-risk group and low-risk group according to the median risk score. The Kaplan-Meier curve showed that in both training and testing sets, the high-risk group had a significantly lower survival rate than the low-risk group (P＜0.05). The ROC curve was used to evaluate the prediction efficiency of this model, and the results showed that in the training set, the testing set, and the entire set, the miRNA model had an AUC of 0.817, 0.808, and 0.814, respectively, while TNM staging had an AUC of 0.667, 0.665, and 0.663, respectively. The results of independent prognostic analysis also showed that this miRNA score model could be used as an independent prognostic factor for HCC (P＜0.05). ConclusionHsa-miR-139-5p, hsa-miR-1180-3p, hsa-miR-1269b, hsa-miR-3680-3p, hsa-miR-509-3-5p, and hsa-miR-31-5p are associated with the prognosis of HCC, and the miRNA risk score model has a better prediction accuracy than TNM staging in the training set, the testing set, and the entire set. The stratified analysis also shows that the model can predict the prognosis of patients within the same TNM stage, and therefore, it has a certain reference value in clinical practice and can be used as an independent model for predicting the prognosis of HCC patients.