Objective To evaluate the effect of Orem self‐care mode on sense of well‐being in patients with schizophrenia by Me‐ta analysis .Methods The databases of CBM ,VIP ,CNKI and Wan Fang Data were searched .All randomized controlled trials(RCT ) about Orem self‐care mode for patients about sense of well‐being were included .Data collection and literature review were per‐formed by two reviewers independently .The RevMan 5 .2 software was taken for analysis .Results Three literatures were includ‐ed .All these articles were regarded as low quality ,and only one article′s score of methodological quality are more than three .The Meta analysis showed there were significant differences between the Orem self‐care mode group and the normal nursing mode group in sense of well‐being .Besides the scores of the Orem self‐care mode group are higher(MD = 16 .29 ,95% CI(14 .54 - 18 .05) ,P<0 .05) .Conclusion The Orem self‐care mode is better than normal nursing for sense of well‐being in patients .However ,trials are only three ,and most trials included in the review are of low quality .So large scale randomized controlled trials of higher quality are needed to confirm the result .

Objective:To investigate the value of tumor hemodynamics and morphological features from conventional dynamic contrast-enhanced MRI (DCE-MRI) scan before surgery in predicting postoperative recurrence time in breast cancer patients.Methods:A retrospective analysis of 58 patients with breast cancer who had recurred after operation from November 2012 to December 2014 in Liaoning Cancer Hospital was performed. According to the recurrence time, the patients were divided into early recurrence group (≤2 years after surgery, 33 cases) and late recurrence group (>2 years after surgery, 25 cases). All patients underwent routine DCE-MRI scans before surgery, and hemodynamic features of the three-dimensional volume of the tumor and the morphological and textural features of the tumor in each phase were extracted by computer. The counts and measurement data of patients in early recurrence group and late recurrence group were compared by Fisher′s exact probability method and Mann-Whitney U test, and receiver operating characteristic (ROC) curves were drawn. The multivariate logistic regression was used to calculate the combined efficacy in predicting early recurrence and late recurrence. Kaplan-Meier method was used to analyze the survival prognosis, and Log-Rank test was used to compare the differences in survival curves between groups. Results:There was no significant difference in background parenchymal enhancement, lesion margin, lesion internal enhancement characteristics, lesion morphology, time-signal intensity curve type and the degree of whole-breast vascularity increase between early recurrence and late recurrence groups ( P>0.05).There were significant differences in the maximum concentration of contrast (Max Conc), the area under the time signal curve (AUC) and the maximum slope value of the time signal curve (Max Slope) ( P<0.05). Comparative analysis of the radiomics parameters of 8 phases DCE-MRI found that the sphericity of morphological characteristic parameters in the phase 3 was statistically different between the early recurrence and late recurrence groups ( P=0.03). Area under the ROC curve of AUC, Max Conc, Max Slope and parameter sphericity of phase 3 morphological characteristics for predicting early and late recurrence were 0.664, 0.659, 0.684 and 0.670, respectively. The area under the ROC combined with the above four parameters for prediction was 0.765, with a specificity of 63.6% and a sensitivity of 84.0%; the predictive efficacy was higher than that of univariate. Fifty-eight patients were followed up for 17 to 64 months with a median follow-up of 47 months. The disease-free survival and overall survival in the early recurrence group were significantly lower than those in the late recurrence group, and the difference was statistically significant ( P<0.05). Conclusion:It is of certain value to predict the postoperative recurrence time of breast cancer based on the tumor hemodynamic characteristics combined with morphological characteristics from preoperative non-invasive conventional DCE-MRI.