Randomized Controlled Trials in Pediatric Urology: Room for Improvement
Bibliographic record
Abstract
PURPOSE: The primary purpose of this study was to ascertain what proportion of the body of published literature in pediatric urology is represented by randomized controlled trials. The secondary purpose was to assess the quality of these trials. MATERIALS AND METHODS: Using a predefined strategy, we conducted systematic computerized searches of the MEDLINE (years 1966 to 2004) and EMBASE (1980 to 2004) databases to identify all English language randomized controlled trials related to pediatric urology. Full text versions of identified studies were reviewed in blinded fashion for key demographic, methodological and statistical characteristics. Trial quality was assessed with the previously validated Jadad tool. RESULTS: The 77 identified randomized controlled trials represented only 0.4% to 0.9% of the indexed pediatric urology literature. The origins of these trials were Europe (40%), North America (26%) and a variety of other geographic centers (34%). A primarily surgical focus was present in 43% of the studies. Trials with negative results represented only 19% of the total randomized controlled trials. Generally, the trials were of low to fair quality (median Jadad score 3), with substandard methodological reporting and planning. There was not a significant trend toward improved quality in recent years. Trials from North America and Europe had higher quality (p = 0.007), as did those reporting negative results (p = 0.0001). CONCLUSIONS: Randomized controlled trials in pediatric urology constitute only a small proportion of the body of published literature in the field. High quality studies are uncommon. Efforts should be made to increase the number of well designed, randomized controlled trials in pediatric urology.
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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 | 0.709 | 0.833 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.021 | 0.014 |
| Bibliometrics | 0.018 | 0.027 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.020 | 0.040 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.016 | 0.021 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".