Objective To review systemically the effectiveness and safety of mesh versus traditional colporrhaphy for pelvic organ prolapse . Methods The literature were retrieved from the PubMed ( 1980 -2013 ) , Cochrane ( 1995 -2013 ) , Google Scholar (1980-2013), CNKI (1980-2013), and SinoMed (1980-2013).The randomized controlled trials (RCT) were collected and compared, and the data were analyzed by using the RevMan 5.0 software. Results There were totally 10 randomized controlled trials collected .Meta-analysis showed that:the operation time was significantly longer in the mesh group than that in the colporrhaphy group [WMD:16.57 min, 95%CI:14.06-19.08 min, P<0.00001]; the intraoperative blood loss was significantly more in the mesh group than that in the colporrhaphy group [ WMD: 24.98 ml, 95%CI:7.13 -42.84 ml, P=0.006]; the mesh group was superior to colporrhaphy group in the increase of objective cure rate [OR:4.16, 95%CI:3.10-5.58,P<0.00001] and subjective cure rate [OR:2.13, 95%CI:1.55-2.91, P<0.00001]; as compared with all various relating operations , the incidence rate of dyspareunia was statistically significant (P=0.04), whereas there were no statistical differences in postoperative recurrence of urinary incontinence and re-operation (P=0.13, P=0.06). Conclusion Apllication of mesh for pelvic organ prolapse can improve the objective and subjective cure rates .Mesh may be usefully applied to the treatment of pelvic organ prolapse , and further high-quality prospective studies are needed .

OBJECTIVE: To develop a noninvasive method for prediction of 1p/19q codeletion in diffuse lower-grade glioma (DLGG) based on multimodal magnetic resonance imaging (MRI) radiomics. METHODS: We collected MRI data from 104 patients with pathologically confirmed DLGG between October, 2015 and September, 2022. A total of 535 radiomics features were extracted from T₂WI, T₁WI, FLAIR, CE-T₁WI and DWI, including 70 morphological features, 90 first order features, and 375 texture features. We constructed logistic regression (LR), logistic regression least absolute shrinkage and selection operator (LRlasso), support vector machine (SVM) and Linear Discriminant Analysis (LDA) radiomics models and compared their predictive performance after 10-fold cross validation. The MRI images were reviewed by two radiologists independently for predicting the 1p/19q status. Receiver operating characteristic curves were used to evaluate classification performance of the radiomics models and the radiologists. RESULTS: The 4 radiomics models (LR, LRlasso, SVM and LDA) achieved similar area under the curve (AUC) in the validation dataset (0.833, 0.819, 0.824 and 0.819, respectively; P>0.1), and their predictive performance was all superior to that of resident physicians of radiology (AUC=0.645, P=0.011, 0.022, 0.016, 0.030, respectively) and similar to that of attending physicians of radiology (AUC=0.838, P>0.05). CONCLUSION Multiparametric MRI radiomics models show good performance for noninvasive prediction of 1p/19q codeletion status in patients with in diffuse lower-grade glioma.
Humans ; Magnetic Resonance Imaging ; Chromosome Aberrations ; Area Under Curve ; Glioma/genetics* ; ROC Curve