PD49-06 ASSESSING THE METHODOLOGICAL AND REPORTING QUALITY OF CLINICAL SYSTEMATIC REVIEWS AND META-ANALYSES IN PAEDIATRIC UROLOGY: CAN WE BUILD PRACTICES ON CONTEMPORARY HIGHEST LEVELS OF EVIDENCE?
Bibliographic record
Abstract
You have accessJournal of UrologyPediatrics: Health Services & Population Research (PD49)1 Apr 2019PD49-06 ASSESSING THE METHODOLOGICAL AND REPORTING QUALITY OF CLINICAL SYSTEMATIC REVIEWS AND META-ANALYSES IN PAEDIATRIC UROLOGY: CAN WE BUILD PRACTICES ON CONTEMPORARY HIGHEST LEVELS OF EVIDENCE? Fardod O'Kelly*, Keara De Cotiis, Luis Braga, Armando Lorenzo, and Martin Koyle Fardod O'Kelly*Fardod O'Kelly* More articles by this author , Keara De CotiisKeara De Cotiis More articles by this author , Luis BragaLuis Braga More articles by this author , Armando LorenzoArmando Lorenzo More articles by this author , and Martin KoyleMartin Koyle More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000556869.45800.5fAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Systematic reviews and meta-analyses provide a comprehensive summary of research studies and are used to assess clinical evidence, form policy and construct guidelines. This is pertinent in childhood surgery with issues of consent, and condition prevalence. Our aims were to evaluate the methodological and reporting quality of these reviews, and to identify how these reviews might guide clinical practice amongst those conditions most commonly encountered and managed by paediatric urology residents and fellows METHODS: A systematic search of the English literature was performed to identify systematic reviews and meta-analyses focusing on clinical paediatric urology (1/1/2000-7/9/2018) to include common paediatric urological conditions managed by paediatric urology residents/fellows. To these reviews, AMSTAR-2 and PRISMA scores were applied. Univariate linear regression and descriptive statistical methods were performed RESULTS: From an initial literature review of 389 articles, 101 were included in the analysis. Inter-reviewer agreement was high (κ = 0.92). 70% systematic reviews/meta-analyses were published since 2013. The overall impact factor was 3.38 (0.83 – 17.58), with adherence to AMSTAR-2 criteria 48.46% and PRISMA criteria 73.32%. From a methodological perspective, 62.5% reviews were of poor quality, with 37.5% of fair quality, 50% reviews were found to have good quality reporting CONCLUSIONS: Despite the continued increase of systematic reviews and meta-analyses in paediatric urology from which many guidelines are based, a significant number contain poor methodology, and to a lesser extent poor reporting quality. Journals should consider having specific “a priori” criteria based on checklists prior to publication of manuscripts in order to ensure the highest possible reporting quality Source of Funding: None Toronto, Canada; Hamilton, Canada; Toronto, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e907-e908 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Fardod O'Kelly* More articles by this author Keara De Cotiis More articles by this author Luis Braga More articles by this author Armando Lorenzo More articles by this author Martin Koyle More articles by this author Expand All Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.795 | 0.945 |
| Meta-epidemiology (narrow) | 0.003 | 0.008 |
| Meta-epidemiology (broad) | 0.012 | 0.016 |
| Bibliometrics | 0.036 | 0.032 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.042 | 0.026 |
| Open science | 0.014 | 0.022 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.031 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".