Defining the publication source of high‐quality evidence in urology: an analysis of EvidenceUpdates
Notice bibliographique
Résumé
OBJECTIVES: To determine the publication sources of urology articles within EvidenceUpdates, a second-order peer review system of the medical literature designed to identify high-quality articles to support up-to-date and evidence-based clinical decisions. MATERIALS AND METHODS: Using administrator-level access, all EvidenceUpdates citations from 2005 to 2014 were downloaded from the topics 'Surgery-Urology' and 'Oncology-Genitourinary'. Data fields accessed included PubMed unique reference identifier, study title, abstract, journal and date of publication, as well as clinical relevance and newsworthiness ratings as determined by discipline-specific physician raters. The citations were then coded by clinical topic (oncology, voiding dysfunction, erectile dysfunction/infertility, infection/inflammation, stones/endourology/laparoscopy, trauma/reconstruction, transplant, or other), journal category (general medical journal, oncology journal, urology journal, non-urology specialty journal, Cochrane review, or other), and study design (randomised controlled trial [RCT], systematic review, observational study, or other). Articles that were perceived to be misclassified and/or of no direct interest to urologists were excluded. Descriptive statistics using proportions and 95% confidence intervals, as well as means and standard deviations (SDs) were used to characterise the overall data cohort and to analyse trends over time. RESULTS: We identified 731 unique citations classified under either 'Surgery-Urology' or 'Oncology-Genitourinary' for analysis after exclusions. Between 2005 and 2014, the most common topics were oncology (48.6%, 355 articles) and voiding dysfunction (21.8%, 159). Within the topic of oncology, prostate cancer contributed over half the studies (54.6%, n = 194). The most common study types were RCTs (42.3%, 309 articles) and systematic reviews (39.6%, 290). Systematic reviews had a nearly fourfold relative increase within less than a decade. The largest proportion of studies relevant to urology were published in general oncology journals (20.0%, n = 146), followed by the Cochrane Library (19.3%, n = 141) and general medical journals (17.2%, n = 126). Urology-specific journals contributed to only approximately one-tenth of EvidenceUpdates alerts (9.4%, n = 69), with the highest contribution occurring during the 2013/2014 period. For clinical relevance and newsworthiness scores (each graded on scales of 1-7), urology journals scored the highest in clinical relevance with a mean (SD) of 5.9 (0.75) and general medical journals scored highest for newsworthiness at 5.3 (0.94). On average, RCTs scored highest both for clinical relevance and newsworthiness with mean (SD) scores of 5.71 (0.81) and 5.22 (0.91), respectively. CONCLUSION: A large number of high-quality, clinically relevant, and newsworthy peer-reviewed urology publications are published outside of traditional urology journals. This requires urologists to implement well-defined strategies to stay abreast of current best evidence.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,308 | 0,821 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,009 | 0,010 |
| Bibliométrie | 0,140 | 0,145 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,024 | 0,017 |
| Science ouverte | 0,006 | 0,014 |
| Intégrité de la recherche | 0,005 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».