BMJ Evidence-Based Medicine最新文献

Objective: To systematically consolidate the most consistently applicable risk factors and assess their predictive performance for gestational diabetes mellitus (GDM) prediction.

Design: Systematic review and meta-analysis.

Data sources: A comprehensive search included several databases (PubMed, Web of Science, Scopus, EMBASE via OVID and CINAHL) from inception to 30 October 2024.

Review: Methods prediction studies conducted in pregnant women during the first and second trimesters were included. Predictive parameters, including true positive, false positive, false negative and true negative values for each factor, were extracted from the 2×2 table. The Prediction model Risk Of Bias ASsessment Tool (PROBAST) was used to evaluate the risk of bias and the applicability of the included studies. A predictive meta-analysis was performed using Stata V.17. Variability was assessed through subgroup analysis.

Results: Seventy-seven eligible studies involving a total of 477 673 participants were included. Among these, 52 had an overall low risk of bias, and 65 demonstrated low concern regarding applicability. Common risk factors used to predict GDM included maternal age, body mass index (BMI), ethnicity, family history of diabetes mellitus (DM), previous GDM, previous macrosomia, multiparity, hypertensive disorders of pregnancy (HDP) and polycystic ovarian syndrome (PCOS). Among all factors, previous macrosomia showed the highest discriminatory power (area under the curve (AUC)=0.77), followed by previous GDM (AUC=0.73), PCOS (AUC=0.66), BMI (AUC=0.65), family history of DM (AUC=0.64), HDP (AUC=0.64), age over 30 (AUC=0.60), Asian ethnicity (AUC=0.59) and multiparity (AUC=0.56). A combination of age, BMI, family history of DM, previous GDM, ethnicity and multiparity achieved the highest AUC of 0.88, followed by the combination of age, BMI, family history of DM and previous GDM, with an AUC of 0.75.

Conclusions: Previous macrosomia and previous GDM are clinically essential risk factors with the highest discriminatory power, indicated by an AUC >0.7. Combining risk factors improves predictive performance, reaching an AUC of 0.88. Our findings highlight the need to enhance existing risk-based screening tools for early detection of GDM and to prevent its adverse pregnancy outcomes and future cardiometabolic risks.

Prospero registration number: CRD 42024598399.

In 2023, the World Health Assembly adopted a resolution to strengthen rehabilitation within health systems, calling for rehabilitation research. Within health, the term rehabilitation has multiple meanings, including a core strategy, a sector, a service and an intervention. The latter has been defined as complex and characterised as a 'black box', similar to complex interventions in other fields. The existing reporting guidelines are not sufficiently effective in describing interventions within the rehabilitation field. We developed the GUideline for Intervention DEscription in Rehabilitation (GUIDE-Rehab) to address these challenges.According to the Enhancing the QUAlity and Transparency Of health Research Network, we followed a Delphi process with multiple Consensus Meetings and piloting and used ACcurate COnsensus Reporting Document for reporting. The background research involved 21 papers. We based GUIDE-Rehab on the Rehabilitation Treatment Specification System, developed over 15 years of research to improve rehabilitation description; the definition of rehabilitation for research purposes; and the Template for Intervention Description and Replication reporting guideline. 68 representatives from global rehabilitation stakeholders (scientific societies, journals, evidence and methods groups), including individuals with lived experience of disability, from 26 countries across all continents and economies, participated. The piloting involved 17 chief editors, 7 research groups and participants from 10 scientific meetings.The complete version comprises 16 items, while the version for uncontrolled studies includes 13. The short version (10 items for text, 6 for appendix) helps reduce the manuscripts' length. The GUIDE-Rehab graphical illustration (nine items) facilitates the intervention description. GUIDE-Rehab will assist in the reporting of interventions in rehabilitation to enhance clinical research and support clinical implementation.

A multidisciplinary framework for designing rapidly deployable, scalable and context-specific decarbonisation interventions for clinical care has been developed within the National Health Service, devised at a care pathway level to identify modifiable emissions hotspots while addressing wider priority outcomes and implementation.