Adherence to CONSORT harms-reporting recommendations in publications of recent analgesic clinical trials: An ACTTION systematic review
Bibliographic record
Abstract
Recommendations for harms (ie, adverse events) reporting in randomized clinical trial publications were presented in a 2004 extension of the Consolidated Standards of Reporting Trials (CONSORT) statement. Our objectives were to assess harms reporting in 3 major pain journals (European Journal of Pain, Journal of Pain, and PAIN®) to determine whether harms reporting improved following publication of the 2004 CONSORT recommendations, and to examine study factors associated with adequacy of harms reporting. A total of 101 randomized, double-blind, noninvasive pharmacologic trials were identified in the 2000-2003 (epoch 1) and 2008-2011 (epoch 2) issues of these journals. Out of 10 reporting recommendations, the mean number fulfilled was 6.08 (SD2.65). Although more harms recommendations were fulfilled in epoch 2 (m(2)=6.49, SD2.66) than in epoch 1 (m(1)=5.39, SD2.52; P=0.04), only the recommendation to report harms per arm was satisfied by >90% of trials in epoch 2, whereas <60% reported withdrawals due to harms. Several trial characteristics (study design, participant type, pain type, frequency of treatment administration, treatment administration method, sponsor, and number of randomized participants) were significantly associated with harms reporting. However, when trial characteristics and epoch were entered into a multiple regression analysis, only trials studying pain patients, those using oral treatments, and industry-sponsored trials were associated with better harms reporting. Despite some improvement in harms reporting, greater improvement is needed to provide informative, consistent reporting of adverse events and safety in analgesic clinical trials.
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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 | 0.790 | 0.846 |
| Meta-epidemiology (narrow) | 0.004 | 0.007 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.020 | 0.024 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.017 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".