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Enregistrement W2987582517 · doi:10.1182/blood-2019-124130

Evaluating the Quality of Systematic Reviews & Meta-Analyses Published on Direct Oral Anticoagulants in the Past 5 Years

2019· article· en· W2987582517 sur OpenAlexaffabout
Ali Eshaghpour, Allen Li, Natalie Chen, Sarah Yang, Mark Crowther

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueMeta-analysis and systematic reviews
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésMedicineSystematic reviewData extractionMEDLINEMeta-analysisPublication biasImpact factorAlternative medicineFamily medicineMedical physicsInternal medicinePathology

Résumé

récupéré en direct d'OpenAlex

Introduction In the past decades evidence-based medicine has begun to drive clinical decision making. With direct oral anti-coagulants (DOACs) emerging as alternatives to warfarin for the treatment and prevention of thromboembolic disorders, it has become crucial that clinicians utilize unbiased and robust evidence to inform their decisions about their use. Systematic reviews (SRs) sit at the "top" of the hierarchy of research evidence - the goal of this study was to evaluate the quality of SRs published on DOACs using AMSTAR criteria. Methods A comprehensive search of Medline, EMBASE, and the Cochrane Database of Systematic Reviews from Jan 2013 to February 2019 was performed. Screening was done across two stages with title and abstract followed by full-text analysis. Any study that was a SR (with or without a meta-analysis) published on DOACs was included. Data extracted included AMSTAR rating, journal of publication, year of publication, number of studies included, reporting adherence to PRISMA guidelines, number of citations, and journal of publication impact factor. Screening and data extraction were both done by two reviewers independently in duplicate. AMSTAR evaluation was done by three reviewers, one of which was a senior author. Statistical analyses comparing AMSTAR scores in relation to the above factors were done. Results A total of 3729 articles were found with 249 being included for analysis. Quality of SRs was highly variable across years with the mean (SD) being 5.68 (2.21). [Figure 1]. There were no significant relationships between quality vs citation rate (r=-0.04; 95% CI -0.17, 0.09; p=0.26) and impact factor (r=-0.05; 95% CI -0.18, 0.08; p=0.219). One-way ANOVA revealed no significant difference of AMSTAR scores between years (F6,242 = 1.85 p=0.09) [Figure 1.]. Reporting adherence to PRISMA guidelines increased the likelihood of being moderate (AMSTAR Score = 5-8) or high-quality evidence (AMSTAR Score = 9-11) (OR = 4.159; 95% CI 2.32, 7.46, p<0.01). Studies included/excluded in reviews (17, 7%) and conflicts of interests in both the review and included studies (21, 8%) were the least reported AMSTAR criteria while characteristics of included studies (226, 90%) and appropriate use of combining findings (217, 87) were the most. [Figure 2.] Conclusions The overall quality of SRs published on DOACs was moderately low and there was no relationship between journal impact factor and quality of the reviews that journals published. Our findings highlight specific areas within which authors can improve their reporting. Reviewers and editors of journals should familiarize themselves with AMSTAR criteria to ensure robust and transparent quality reporting in an effort to increase the quality of evidence being used to guide clinical decision making. Disclosures Crowther: Diagnostica Stago: Other: preparing educational material and/or providing educational presentations, Research Funding; Bayer: Other: Data and Safety Monitoring Board, Research Funding, Speakers Bureau; BMS Canada: Membership on an entity's Board of Directors or advisory committees, Research Funding; Servier Canada: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Other: preparing educational material and/or providing educational presentations; CSL Behring: Other: preparing educational material and/or providing educational presentations; Asahi Kasei: Membership on an entity's Board of Directors or advisory committees; Octapharma: Membership on an entity's Board of Directors or advisory committees; Shionogi: Membership on an entity's Board of Directors or advisory committees; Alexion: Speakers Bureau; Alnylam: Equity Ownership.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,234
score de la tête « metaresearch » (Gemma)0,494
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesMétarecherche
DomaineSignal candidat: Évaluation · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,766
Score d'incertitude au seuil0,945

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,2340,494
Méta-épidémiologie (sens strict)0,0030,003
Méta-épidémiologie (sens large)0,0190,039
Bibliométrie0,0490,043
Études des sciences et des technologies0,0020,003
Communication savante0,0090,007
Science ouverte0,0040,005
Intégrité de la recherche0,0040,002
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,949
Tête enseignante GPT0,648
Écart entre enseignants0,300 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.

Devis d'étudeRevue systématique
DomaineÉvaluation
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission2
Résumé présentoui

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