A descriptive analysis of a representative sample of pediatric randomized controlled trials published in 2007
Bibliographic record
Abstract
BACKGROUND: Randomized controlled trials (RCTs) are the gold standard for trials assessing the effects of therapeutic interventions; therefore it is important to understand how they are conducted. Our objectives were to provide an overview of a representative sample of pediatric RCTs published in 2007 and assess the validity of their results. METHODS: We searched Cochrane Central Register of Controlled Trials using a pediatric filter and randomly selected 300 RCTs published in 2007. We extracted data on trial characteristics; outcomes; methodological quality; reporting; and registration and protocol characteristics. Trial registration and protocol availability were determined for each study based on the publication, an Internet search and an author survey. RESULTS: Most studies (83%) were efficacy trials, 40% evaluated drugs, and 30% were placebo-controlled. Primary outcomes were specified in 41%; 43% reported on adverse events. At least one statistically significant outcome was reported in 77% of trials; 63% favored the treatment group. Trial registration was declared in 12% of publications and 23% were found through an Internet search. Risk of bias (ROB) was high in 59% of trials, unclear in 33%, and low in 8%. Registered trials were more likely to have low ROB than non-registered trials (16% vs. 5%; p = 0.008). Effect sizes tended to be larger for trials at high vs. low ROB (0.28, 95% CI 0.21,0.35 vs. 0.16, 95% CI 0.07,0.25). Among survey respondents (50% response rate), the most common reason for trial registration was a publication requirement and for non-registration, a lack of familiarity with the process. CONCLUSIONS: More than half of this random sample of pediatric RCTs published in 2007 was at high ROB and three quarters of trials were not registered. There is an urgent need to improve the design, conduct, and reporting of child health research.
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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 | 0.092 | 0.335 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.034 | 0.028 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".