Low-Frequency Ultrasound Debridement in Chronic Wound Healing: A Systematic Review of Current Evidence
Bibliographic record
Abstract
Chronic wounds are painful and debilitating to patients, pose a clinical challenge to physicians, and impose financial burden on the health-care system. New treatment options are therefore highly sought after. Ultrasound debridement is a promising technology that functions to disperse bacterial biofilms and stimulate wound healing. In this review, we focus on low-frequency ultrasound (20-60 kHz) and summarize the findings of 25 recent studies examining ultrasound efficacy. Ultrasound debridement appears to be most effective when used 3 times a week and has the potential to decrease exudate and slough, decrease patient pain, disperse biofilms, and increase healing in wounds of various etiology. Although current studies are generally of smaller size, the results are promising and we recommend the testing of low-frequency ultrasound therapy in clinical practice on a larger scale.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".