Deficiencies in reporting inclusion/exclusion criteria and characteristics of patients in randomized controlled trials of therapeutic interventions in pressure injuries: a systematic methodological review
Bibliographic record
Abstract
Wound care is a complex procedure and the related research may include many variables. Deficiencies in the sample inclusion and exclusion criteria may limit the generalizability of randomized controlled trials (RCTs) for wound patients in the real world. This study aimed to evaluate deficiencies in reporting the inclusion and exclusion criteria and the characteristics of patients in RCTs of pressure injuries (PI) therapeutic interventions. We conducted a systematic methodological review in which 40 full text RCTs of PI treatment interventions published in English, from 2008 to 2020, were identified. Data on the general characteristics of the included RCTs and data about inclusion/exclusion criteria and characteristics of patients were collected. The inclusion/exclusion criteria were categorized into five domains (definition of disease, precision, safety, ethical/legal and administrative). Study duration (in weeks) was 8.0 (quartile 1: 2.0; quartile 3: 48.0); only 5.0% of the trials mentioned race, skin colour or ethnicity, and 37.5% reported the duration of the wound. Only 9 (22.5%) studies reported the drugs that the included patients were using and 10 (25.0%) RCTs reported adverse events. The presence of the five domains was observed only in 12.5% of RCTs and only 12 (30.0%) had the precision domain. Much more research is required in systematic assessments of the external validity of trials because there is substantial disparity between the information that is provided by RCTs and the information that is required by clinicians. We concluded that there are deficiencies in reporting of data related to inclusion/exclusion criteria and characteristics of patients of RCTs assessing PI therapeutic interventions.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reporting · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | MetaresearchMeta-epidemiology (broad) Domain: Reporting · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.525 | 0.784 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.019 | 0.019 |
| Bibliometrics | 0.017 | 0.022 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".