Prevalence and risk factors for mesh erosion after laparoscopic-assisted sacrocolpopexy

The purpose of this study is to identify risk factors for mesh erosion in women undergoing minimally invasive sacrocolpopexy (MISC). We hypothesize that erosion is higher in subjects undergoing concomitant hysterectomy. This is a retrospective cohort study of women who underwent MISC between November 2004 and January 2009. Demographics, operative techniques, and outcomes were abstracted from medical records. Multivariable regression identified odds of erosion. Of 188 MISC procedures 19(10%) had erosions. Erosion was higher in those with total vaginal hysterectomy (TVH) compared to both post-hysterectomy (23% vs. 5%, p = 0.003) and supracervical hysterectomy (SCH) (23% vs. 5%, p = 0.109) groups. In multivariable regression, the odds of erosion for TVH was 5.67 (95% CI: 1.88–17.10) compared to post-hysterectomy. Smoking, the use of collagen-coated mesh, transvaginal dissection, and mesh attachment transvaginally were no longer significant in the multivariable regression model. Based on this study, surgeons should consider supracervical hysterectomy over total vaginal hysterectomy as the procedure of choice in association with MISC unless removal of the cervix is otherwise indicated

A systematic review of outcome and outcome-measure reporting in randomised trials evaluating surgical interventions for anterior-compartment vaginal prolapse: a call to action to develop a core outcome set

INTRODUCTION: We assessed outcome and outcome-measure reporting in randomised controlled trials evaluating surgical interventions for anterior-compartment vaginal prolapse and explored the relationships between outcome reporting quality with journal impact factor, year of publication, and methodological quality. METHODS: We searched the bibliographical databases from inception to October 2017. Two researchers independently selected studies and assessed study characteristics, methodological quality (Jadad criteria; range 1-5), and outcome reporting quality Management of Otitis Media with Effusion in Cleft Palate (MOMENT) criteria; range 1-6], and extracted relevant data. We used a multivariate linear regression to assess associations between outcome reporting quality and other variables. RESULTS: Eighty publications reporting data from 10,924 participants were included. Seventeen different surgical interventions were evaluated. One hundred different outcomes and 112 outcome measures were reported. Outcomes were inconsistently reported across trials; for example, 43 trials reported anatomical treatment success rates (12 outcome measures), 25 trials reported quality of life (15 outcome measures) and eight trials reported postoperative pain (seven outcome measures). Multivariate linear regression demonstrated a relationship between outcome reporting quality with methodological quality (β = 0.412; P = 0.018). No relationship was demonstrated between outcome reporting quality with impact factor (β = 0.078; P = 0.306), year of publication (β = 0.149; P = 0.295), study size (β = 0.008; P = 0.961) and commercial funding (β = -0.013; P = 0.918). CONCLUSIONS: Anterior-compartment vaginal prolapse trials report many different outcomes and outcome measures and often neglect to report important safety outcomes. Developing, disseminating and implementing a core outcome set will help address these issues

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe