BMJ Evidence-Based Medicine最新文献

Objectives: To map the risk profile of drug classes at the population level by identifying associations between newly prescribed reimbursed drugs and sudden cardiac arrest (SCA), thereby providing a systematic basis for assessing individual drug effects.

Design: Population-based, matched case-control study.

Setting: Greater Vienna area, Austria, using linked data from the Austrian Healthcare Reimbursement Database and the Vienna Ambulance Service between 2013 and 2020.

Participants: A total of 31 330 insured individuals were included from an estimated 14 448 612 person-years at risk. Cases (n=6266) were patients with SCA, each matched 1:4 to controls (n=25 064) without SCA by age, sex and event date. The estimated absolute case risk equals 43.4 per 100 000 person-years.

Interventions: Newly prescribed reimbursed drugs within 4 weeks before the SCA event, classified according to four-digit Anatomical Therapeutic Chemical (ATC) codes.

Main analyses: Associations between newly prescribed drug classes and SCA, estimated using conditional logistic regression and expressed as ORs with 95% CIs, adjusted for comorbidities and concomitant medications prescribed 120-29 days before the event.

Results: Among 322 relevant ATC drug classes, 245 were newly prescribed within 28 days prior to the SCA event. Of these, 57 (23%) were significantly associated with SCA. Eight drug classes demonstrated a markedly elevated risk (OR≥10), including oripavine derivatives (OR 64, 95% CI 8 to 486), other cardiac preparations (OR 22, 95% CI 2 to 204), plain antiandrogens (OR 18, 95% CI 1.2 to 275) and phenylpiperidine derivatives (OR 16, 95% CI 7 to 38). The most frequently prescribed associated drug classes were penicillins with beta-lactamase inhibitors (179 cases; OR 2.17, 95% CI 1.8 to 2.7), pyrazolones (167 cases; OR 2.14, 95% CI 1.7 to 2.7) and adrenergics combined with anticholinergics (130 cases; OR 2.94, 95% CI 2.2 to 3.9).

Conclusions: Numerous outpatient-prescribed drug classes were associated with SCA. This exploratory, population-based analysis provides a systematic map of potential safety signals to inform more detailed pharmaco-epidemiological investigations, in which confounding and causality can be examined more rigorously.

Objectives: To systematically review the utilisation of the Grading of Recommendations Assessment, Development and Evaluations (GRADE) framework within the context of WHO public health guidelines (PHGs), identifying key features, areas of concentration and potential deficiencies.

Design and setting: From 2007 to February 2024, a comprehensive search of the WHO website was conducted to identify PHGs that have incorporated the GRADE methodology.

Participants: The study focused on the PHGs identified through the above search.

Interventions: Data extraction and analysis were independently conducted by researchers using Microsoft Excel 2019.

Main outcome measures: For each PHG, key recorded characteristics included publication details, thematic areas, the strength of recommendations, the certainty of evidence, and characteristics of the GRADE downgrading/upgrading domains.

Results: Out of 228 PHGs examined, 9234 (90.55%) outcome indicators used the GRADE rating system, predominantly in the area of sexual and reproductive health (50%). Only 31.62% of the outcomes reported moderate and high certainty in evidence. The main clustering results were dominated by adverse events. Among the 4013 recommendations, 2067 (51.51%) were strong, while 1477 (36.81%) were weak/conditional. It is noteworthy that 46.83% of the strong recommendations were based on low or very low confidence in evidence. Among these strong recommendations, 119 met the criteria of five paradigmatic situations where it was necessary to issue a strong recommendation despite low or very low confidence in the effect estimates. Among the 13 230 instances of downgrading, 41.09% were due to the risk of bias and 35.90% were due to imprecision. Only 0.25% outcomes were upgraded by the magnitude of effect size and 0.03% by dose-response gradient.

Conclusion: The GRADE approach is widely used in the development of PHGs. More than half of the recommendations in PHGs are based on low or very low-quality evidence, primarily due to risks of bias and imprecision. Additionally, strong recommendations based on low-confidence or very low-confidence estimates are frequently made. Therefore, it is necessary to enhance guideline developers' understanding of the GRADE methodology and to further investigate and clarify discordant recommendations in PHGs.

Background: The adaptation of clinical practice guidelines (CPGs) is increasingly used to efficiently develop contextualised recommendations for local, regional and national settings. However, adaptation approaches lack standardisation, and their application remains unclear.

Objective: To identify existing literature on CPG adaptation approaches, synthesise and analyse the definitions, rationales, key steps and their applications.

Methods: We conducted a scoping review and identified studies through (1) database searches in MEDLINE and EMBASE (October 2024); (2) forward citation searches (January 2024); (3) manual searches; and (4) expert recommendations. We included documents describing adaptation approaches that allow reproducibility or adapted guidelines reflecting their application, without language restriction. We analysed data using descriptive and content analysis, with visualisations using Tableau.

Results: We identified 49 adaptation approaches (2000-2024) and 151 applications (2007-2024). 28 approaches originated from high-income countries (57.1%), primarily aimed at improving guideline development efficiency. We categorised these approaches into methodological frameworks (n=16, 32.7%), medical association frameworks (n=7, 14.3%), organisational handbooks (n=12, 24.5%), national or regional approaches (n=13, 26.5%) and one topic-specific methodology. From the key adaptation steps of the identified approaches, we found that 'judging quality of evidence' and 'establishing guideline group processes' were the least addressed. Approximately 20% of applications modified the original approaches during the adaptation process. ADAPTE (n=50, 33.1%) and the Grading of Recommendations, Assessment, Development and Evaluations (GRADE)-ADOLOPMENT (n=41, 27.2%) are the most commonly used adaptation approaches. Also, over half of the identified applications were adapted at the evidence level (n=88, 58.3%) and completed the process within 12 months (range: 2-36 months).

Conclusions: 49 adaptation approaches were identified, with a recent surge in interest and utilisation. Although adaptation can save time and resources, substantial variations among existing approaches and their applications remain. These findings highlight the need for comprehensive guidance to support standardisation and optimise the quality of the adaptation process.

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.