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Abstract Objective To systematically evaluate existing developed and validated predictive models for stress urinary incontinence after pelvic floor reconstruction. Methods Relevant literature in PubMed, Embase, Web of Science, Cochrane Library, OVID, China National Knowledge Infrastructure(CNKI), Wan Fang Database, VIP database and Chinese Biomedical Literature Service System (SinoMed) were search from inception to 1 March 2024. Literature screening and data extraction were performed independently by two researchers. The chosen study’s statistics included study design, data sources, outcome definitions, sample size, predictors, model development, and performance. The Predictive Modelling Risk of Bias Assessment Tool (PROBAST) checklist was used to assess risk of bias and applicability. Results A total of 7 studies containing 9 predictive models were included. All studies had a high risk of bias, primarily due to retrospective design, small sample sizes, single-center trials, lack of blinding, and missing data reporting. The meta-analysis revealed moderate heterogeneity (I² = 68.8%). The pooled AUC value of the validated models was 0.72 (95% CI: 0.65, 0.79), indicating moderate predictive ability. Conclusion The prediction models evaluated demonstrated moderate discrimination, but significant bias and methodological flaws. The meta-analysis revealed moderate heterogeneity (I² = 68.8%) among the included studies, reflecting differences in study populations, predictors, and methods, which limits the generalizability of the findings. Despite these challenges, these models highlight the potential to identify high-risk patients for targeted interventions to improve surgical outcomes and reduce postoperative complications. The findings suggest that by integrating these models into clinical decision-making, clinicians can better tailor surgical plans and preoperative counseling, thereby improving patient satisfaction and reducing the incidence of postoperative stress urinary incontinence. Future research should follow TRIPOD and PROBAST principles, focus on addressing sources of heterogeneity, improve model development through robust designs, large sample sizes, comprehensive predictors, and novel modelling approaches, and validate tools that can be effectively integrated into clinical decision-making to manage stress urinary incontinence after pelvic floor reconstruction.

Background Kangaroo mother care (KMC) is a care of preterm and low birthweight infants carried skin-to-skin contact with the mother’s chest and breastfeeding when possible. KMC has been proven to reduce mortality and morbidity in these infants. However, research on KMC has been limited by significant variability and inconsistency in reported outcomes across studies. These discrepancies hinder the inclusion of KMC clinical research in systematic reviews or meta-analyses, reducing its research value, leading to resource wastage and raising concerns about selective reporting biases. A core outcome set (COS), which defines a list of critical outcomes, can help harmonise the outcomes reported across studies in the same healthcare field. Further, how these outcomes should be measured and/or reported is defined in a core measurement set (CMS). This study aims to develop both a COS and a CMS for KMC to standardise outcome reporting, improve the quality assessments in clinical trials and facilitate data integration. This protocol outlines the methodology for developing a COS and CMS for KMC.Methods and analysis The development of the COS and CMS for KMC will follow six phases: (1) a systematic review, (2) semistructured interviews, (3) merging outcomes, (4) two/three rounds of international Delphi survey, (5) a consensus meeting and (6) development of the CMS. In phases 1 and 2, we will conduct a systematic review and semistructured interviews to identify potential core outcomes and measurements, which will form an initial outcome pool. In phase 3, these outcomes will be categorised into domains based on the core outcome measures for effectiveness (COMET) classification, creating a long list of outcomes for the Delphi survey. In phase 4, the Delphi survey will involve two/three rounds with key stakeholders, including neonatal clinical experts (including doctors and nurses), users of COS (including editors, public health experts, experts in evidence-based medicine and researchers), parents of neonates and policymakers, to refine the candidate core outcomes and measurements. In phase 5, an online consensus meeting with representatives of all stakeholders will finalise the COS. In phase 6, the CMS will be following Consensus-based Standards for the selection of health Measurement Instruments guidelines, which involve conceptual considerations, finding existing outcome measurement instruments, assessing their quality and selecting appropriate instruments for the COS. Parents of neonates will participate in phases 2, 4 and 5.Ethics and dissemination Ethical approval of this study has been granted by the Medical Ethics Committee of West China Second University Hospital (Medical Research 2024 ethics approval no. 167). The finalised COS and CMS will be disseminated through publication in peer-reviewed journals.Trial registration number We have registered the COS in the COMET database (http://www.comet-initiative.org/Studies/Details/2940).

Abstract Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015–2020. The coefficient of determination (R2) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.