Quality of reporting of outcomes in trials of therapeutic interventions for pressure ulcers in adults: a protocol for a systematic survey
Bibliographic record
Abstract
Pressure ulcers (PUs) have a high incidence, especially in hospital units. Randomised clinical trials (RCTs) of therapeutic interventions for PU should include a clear description of the outcomes and results to enhance transparency and replicability. OBJECTIVES: The primary objective of this study is to assess the completeness of the descriptions of the outcomes of therapeutic interventions in RCTs in adult patients with PU. The secondary objectives are to evaluate the types of reported primary outcomes, measurement methods or tools used to evaluate the outcomes and the results of reported outcomes. METHODS: We will conduct a systematic survey of RCTs published from January 2006 to April 2018. The selection process of the studies will be done in two stages of screening: title and abstract, and full text revision, always by two researchers independently. The completeness of the outcome will be assessed according to five criteria: domain (outcome title), specific measurement or technique/instrument used, specific metric or format of the outcome data that will be used for analysis, method of aggregation (how data from each group will be summarised) and time-points that will be used for analysis. The quality of the results of the outcome will be classified as either complete, incomplete or unreported. We will conduct a descriptive analysis of the number, type and degrees of outcome specification in the included RCTs. The frequency of categories in each domain of the outcomes will also be reported. The median and IQR will be estimated for each element of the specified outcome (out of five). ETHICS AND DISSEMINATION: This will be the first systematic assessment of the outcomes of therapeutic interventions used for pressure ulcers. After completion, this review will be submitted to a peer-reviewed journals.
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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 | 0.406 | 0.458 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.012 | 0.018 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.032 | 0.014 |
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".