BMJ Evidence-Based Medicine最新文献

{"title":"Toward automating GRADE classification: a proof-of-concept evaluation of an artificial intelligence-based tool for semiautomated evidence quality rating in systematic reviews.","authors":"Alisson Oliveira Dos Santos, Vinícius Silva Belo, Tales Mota Machado, Eduardo Sérgio da Silva","doi":"10.1136/bmjebm-2024-113123","DOIUrl":"10.1136/bmjebm-2024-113123","url":null,"abstract":"<p><strong>Background: </strong>Evaluation of the quality of evidence in systematic reviews (SRs) is essential for assertive decision-making. Although Grading of Recommendations Assessment, Development and Evaluation (GRADE) affords a consolidated approach for rating the level of evidence, its application is complex and time-consuming. Artificial intelligence (AI) can be used to overcome these barriers.</p><p><strong>Design: </strong>Analytical experimental study.</p><p><strong>Objective: </strong>The objective is to develop and appraise a proof-of-concept AI-powered tool for the semiautomation of an adaptation of the GRADE classification system to determine levels of evidence in SRs with meta-analyses compiled from randomised clinical trials.</p><p><strong>Methods: </strong>The URSE-automated system was based on an algorithm created to enhance the objectivity of the GRADE classification. It was developed using the Python language and the React library to create user-friendly interfaces. Evaluation of the URSE-automated system was performed by analysing 115 SRs from the Cochrane Library and comparing the predicted levels of evidence with those generated by human evaluators.</p><p><strong>Results: </strong>The open-source URSE code is available on GitHub (http://www.github.com/alisson-mfc/urse). The agreement between the URSE-automated GRADE system and human evaluators regarding the quality of evidence was 63.2% with a Cohen's kappa coefficient of 0.44. The metrics of the GRADE domains evaluated included accuracy and F1-scores, which were 0.97 and 0.94 for imprecision (number of participants), 0.73 and 0.7 for risk of bias, 0.9 and 0.9 for I² values (heterogeneity) and 0.98 and 0.99 for quality of methodology (A Measurement Tool to Assess Systematic Reviews), respectively.</p><p><strong>Conclusion: </strong>The results demonstrate the potential use of AI in assessing the quality of evidence. However, in consideration of the emphasis of the GRADE approach on subjectivity and understanding the context of evidence production, full automation of the classification process is not opportune. Nevertheless, the combination of the URSE-automated system with human evaluation or the integration of this tool into other platforms represents interesting directions for the future.</p>","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":"36-45"},"PeriodicalIF":10.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adverse events of inhaled corticosteroids in adult patients with asthma or chronic obstructive pulmonary disease: pairwise, network and dose-response meta-analyses.","authors":"Xiaofeng Pu, Yinhui Zhang, Li Peng, Yunbei Huang, Xinrui Jiang, Maolin Wang, Zhengji Zhang, Mengyao Xu, Guojun Wang","doi":"10.1136/bmjebm-2024-113216","DOIUrl":"10.1136/bmjebm-2024-113216","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objectives: &lt;/strong&gt;This study aimed to evaluate the associations between inhaled corticosteroids (ICSs) and adverse events (AEs) in adults with asthma or chronic obstructive pulmonary disease (COPD) and to explore variations by ICS type and dosage.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design and setting: &lt;/strong&gt;Medline/PubMed, Embase, the Cochrane Central Register of Controlled Trials and ClinicalTrials.gov were searched from inception to 20 February 2025. Data extraction and synthesis were performed, estimating risk ratios (RRs) with 95% confidence intervals (CI) or credible intervals (CrI) through pairwise and network meta-analysis (NMA), and an NMA using the Emax model was employed to find the dose-response relationships of the AEs of each ICS. Risk of bias was evaluated across both pairwise and NMAs. The certainty of evidence, based on the GRADE approach, was assessed exclusively for the NMA estimates.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Participants: &lt;/strong&gt;Adults diagnosed with asthma or COPD treated with ICSs compared with non-ICS controls or those receiving different types or doses of ICSs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcome measures: &lt;/strong&gt;The primary outcomes were AEs, including pneumonia, oral candidiasis, upper respiratory tract infection (URTI), fracture, diabetes, cataract and plasma cortisol abnormalities. Secondary outcomes included efficacy-related endpoints: asthma exacerbations, COPD exacerbations and all-cause mortality.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;129 trials (120 900 participants) were included. According to pairwise meta-analysis, ICSs were associated with a higher risk of pneumonia (RR 1.49, 95% CI 1.38 to 1.61) and oral candidiasis (RR 2.29, 95% CI 2.01 to 2.60) and with a slightly higher risk of URTI (RR 1.17, 95% CI 1.10 to 1.25), compared with control. Besides, ICSs were linked to a reduced risk of asthma exacerbations (RR 0.30, 95% CI 0.20 to 0.45) and COPD exacerbations (RR 0.90, 95% CI 0.86 to 0.94) vs control. The results of the NMA that explored differences by ICS type showed that beclomethasone and fluticasone increased pneumonia risk compared with control, with absolute risk increases of up to 2.3%. Fluticasone also showed a slightly higher pneumonia risk than budesonide. Besides, mometasone, beclomethasone, budesonide and fluticasone were associated with increased risk of oral candidiasis, with the highest increase observed for mometasone (4.3%). In contrast, ciclesonide consistently showed lower risk across comparisons, reducing oral candidiasis by up to 4.5% with other ICSs. Fluticasone modestly increased URTI, while ciclesonide reduced it. Budesonide and mometasone were also associated with a small increase in cataract risk. Most of the outcomes reported here were supported by moderate- to high-certainty evidence. Furthermore, the dose-response relationship estimated from the Emax model indicated significant associations between fluticasone dose and the risks of pneumonia and URTI, between multiple ICS doses and oral candidiasis and betw","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":"23-35"},"PeriodicalIF":10.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145530581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Children's and caregivers' participation in the development of paediatric core outcome sets: a cross-sectional analysis.","authors":"Ruobing Lei, Janne Estill, Haiyun Wang, Jin Xiong, Qiu Li, Yaolong Chen, Paula Williamson","doi":"10.1136/bmjebm-2024-113521","DOIUrl":"10.1136/bmjebm-2024-113521","url":null,"abstract":"<p><strong>Objectives: </strong>This study aims to address the status of children's and caregivers' participation in the development of paediatric core outcome sets (COS).</p><p><strong>Methods: </strong>We included all paediatric COS from a previous systematic review and searched the Core Outcome Measures in Effectiveness Trials database to 26 February 2024 for recent paediatric COS. We used descriptive and thematic analysis methods to present the characteristics of the included COS and to describe children's and caregivers' participation in the development, including any facilitators and barriers. We assessed the degree of participation of children and caregivers in two steps: by rating whether their views were considered in forming the outcome list (yes/no) and then whether their views were integrated in determining the most important outcomes (fully integrated/partially integrated/not integrated).</p><p><strong>Results: </strong>A total of 114 paediatric COS were included. 60 (53%) COS involved children and caregivers in the development process. 29 (48%) of the 60 COS considered children's and caregivers' views in forming the initial outcome list, which was most often conducted by interview (n=12 of 29, 41%). Regarding determining the most important outcomes, 35 (58%) of the 60 COS fully integrated children's and caregivers' views, and the most common method was the Delphi survey with consensus meeting (n=29 of 35, 83%); the youngest child participants were aged 7 years. The most frequently mentioned facilitator of children's and caregivers' participation was the engagement of patient groups or organisations.</p><p><strong>Conclusion and relevance: </strong>We evaluated the degree of children's and caregivers' participation in the development of COS and found that strategies to promote children's and caregivers' participation should be constructed.</p>","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":"57-65"},"PeriodicalIF":10.8,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methylphenidate denied access to WHO's list of essential medicines for the third time.","authors":"Ole Jakob Storebø, Henriette Edemann-Callesen, Johanne Pereira Ribeiro, Sophie Juul, Sabrina Katja Nestved, Helene Speyer, Andreas Hoff, Charlotte Lunde, Christian Gluud","doi":"10.1136/bmjebm-2025-114219","DOIUrl":"https://doi.org/10.1136/bmjebm-2025-114219","url":null,"abstract":"","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145932025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using and distinguishing evidence from non-randomised studies of interventions.","authors":"Jamie Hartmann-Boyce, Nicola Lindson, Lisa Bero, Jo Dumville, Ella Flemyng, Barney Reeves, Peter Tugwell, David B Wilson, Hugh Sharma Waddington","doi":"10.1136/bmjebm-2025-114125","DOIUrl":"https://doi.org/10.1136/bmjebm-2025-114125","url":null,"abstract":"","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the performance of maternal risk factors in predicting gestational diabetes mellitus: a systematic review and meta-analysis.","authors":"Alemu Degu Ayele, Getnet Gedefaw Azeze, Beklau Kassie Alemu, Yao Wang, Chi Chiu Wang","doi":"10.1136/bmjebm-2025-114065","DOIUrl":"https://doi.org/10.1136/bmjebm-2025-114065","url":null,"abstract":"<p><strong>Objective: </strong>To systematically consolidate the most consistently applicable risk factors and assess their predictive performance for gestational diabetes mellitus (GDM) prediction.</p><p><strong>Design: </strong>Systematic review and meta-analysis.</p><p><strong>Data sources: </strong>A comprehensive search included several databases (PubMed, Web of Science, Scopus, EMBASE via OVID and CINAHL) from inception to 30 October 2024.</p><p><strong>Review: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Prospero registration number: </strong>CRD 42024598399.</p>","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145817839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ataluren for Duchenne: how politics and social pressure undermined evidence-based decisions.","authors":"Juan Erviti, Luis Carlos Saiz, Marta Gutiérrez-Valencia","doi":"10.1136/bmjebm-2025-113995","DOIUrl":"https://doi.org/10.1136/bmjebm-2025-113995","url":null,"abstract":"","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145751786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regression to the mean: a primer for evidence-based medicine practitioners.","authors":"Mohammad Hassan Murad, Neha Ramachandran, Lifeng Lin, Fan Li","doi":"10.1136/bmjebm-2025-113948","DOIUrl":"https://doi.org/10.1136/bmjebm-2025-113948","url":null,"abstract":"","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145751724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Less is more - but for whom? Evaluating patient reported outcomes in de-implementation.","authors":"Eva Willemiek Verkerk, Paula Riganti","doi":"10.1136/bmjebm-2025-113957","DOIUrl":"https://doi.org/10.1136/bmjebm-2025-113957","url":null,"abstract":"","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145713345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opportunities, challenges and risks of using artificial intelligence for evidence synthesis.","authors":"Waldemar Siemens, Erik von Elm, Harald Binder, Daniel Böhringer, Angelika Eisele-Metzger, Gerald Gartlehner, Piet Hanegraaf, Maria-Inti Metzendorf, Jacob-Jan Mosselman, Artur Nowak, Riaz Qureshi, James Thomas, Siw Waffenschmidt, Valérie Labonté, Joerg J Meerpohl","doi":"10.1136/bmjebm-2024-113320","DOIUrl":"10.1136/bmjebm-2024-113320","url":null,"abstract":"","PeriodicalId":9059,"journal":{"name":"BMJ Evidence-Based Medicine","volume":" ","pages":"381-384"},"PeriodicalIF":7.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142944306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}