Bibliographic record
Abstract
Abstract Objective: To estimate the clinical and cost effectiveness of compression systems for treating venous leg ulcers. Methods: Systematic review of research. Search of 19 electronic databases including Medline, CINAHL, and Embase. Relevant journals and conference proceedings were hand searched and experts were consulted. Main outcome measures: Rate of healing and proportion of ulcers healed within a time period. Study selection: Randomised controlled trials, published or unpublished, with no restriction on date or language, that evaluated compression as a treatment for venous leg ulcers. Results: 24 randomised controlled trials were included in the review. The research evidence was quite weak: many trials had inadequate sample size and generally poor methodology. Compression seems to increase healing rates. Various high compression regimens are more effective than low compression. Few trials have compared the effectiveness of different high compression systems. Conclusions: Compression systems improve the healing of venous leg ulcers and should be used routinely in uncomplicated venous ulcers. Insufficient reliable evidence exists to indicate which system is the most effective. More good quality randomised controlled trials in association with economic evaluations are needed, to ascertain the most cost effective system for treating venous leg ulcers. Key messages Compression treatment increases the healing of ulcers compared with no compression High compression is more effective than low compression but should only be used in the absence of significant arterial disease No clear differences in the effectiveness of different types of compression systems (multilayer and short stretch bandages and Unna9s boot) have been shown Intermittent pneumatic compression appears to be a useful adjunct to bandaging Rather than advocate one particular system, the increased use of any correctly applied high compression treatment should be promoted
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.269 | 0.068 |
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".