Negative-Pressure Therapy versus Standard Wound Care
Bibliographic record
Abstract
BACKGROUND: Several randomized controlled trials comparing negative-pressure therapy to standard wound care for chronic wounds have been published. Although these studies suggest a benefit for negative-pressure therapy, the majority of the review articles on the topic conclude that the studies are inconclusive. The authors conducted a quantitative meta-analysis of the effectiveness of negative-pressure therapy for the management of chronic wounds. METHODS: The MEDLINE, EMBASE, and Cochrane databases were searched from 1993 to March of 2010 for randomized controlled trials comparing negative-pressure therapy to standard wound care for chronic wounds. Measures of wound size and time to healing, along with the corresponding p values, were extracted from the randomized controlled trials. Relative change ratios of wound size and ratios of median time to healing were combined using a random effects model for meta-analysis. RESULTS: Ten trials of negative-pressure therapy versus standard wound care were found. In the negative-pressure therapy group, wound size had decreased significantly more than in the standard wound care group (relative change ratio, 0.77; 95 percent confidence interval, 0.63 to 0.96). Time to healing was significantly shorter in the negative-pressure therapy group in comparison with the standard wound care group (ratio of median time to healing, 0.74; 95 percent confidence interval, 0.70 to 0.78). CONCLUSIONS: This quantitative meta-analysis of randomized trials suggests that negative-pressure therapy appears to be an effective treatment for chronic wounds. An effect of publication bias cannot be ruled out. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, II.
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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 | 0.032 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".