The effect of 22.5 kHz low‐frequency contact ultrasound debridement (LFCUD) on lower extremity wound healing for a vascular surgery population: A randomised controlled trial
Bibliographic record
Abstract
The aim of this study was to compare changes in wound size and appearance and health complication rates in patients with vasculopathy and lower-extremity wounds treated with or without low-frequency contact ultrasound debridement (LFCUD) This study was a randomised controlled trial. The study was conducted in a vascular surgery service, including outpatient wound clinic and inpatient ward, in a tertiary care academic centre. In total, 70 patients with vasculopathy and lower-extremity wounds of mixed aetiology were enrolled in the trial; 68 completed the study. Patients were randomised to receive LFCUD plus usual care (n = 33) or usual care (n = 37) at 4 weekly visits, and were followed thereafter for up to 12 wk. The main outcome measures included closed wounds, change in wound surface area (WSA), and wound appearance by the revised Photographic Wound Assessment Tool (revPWAT). After 4 weekly LFCUD treatments, patients in the LFCUD group had significantly better wound appearance (total revPWAT score) compared with the control group treated only with usual care (P = <0.05). LFCUD-treated wounds also had a significant reduction in WSA over 4 wk that was not found in the UC group. LFCUD treatment was also associated with a greater number of healed wounds, odds ratio 5.00 (95% CI 1.24-20.25), and fewer instances of wound deterioration. Weekly LFCUD applications to patients with significant vasculopathy resulted in superior healing outcomes when compared with current usual wound care practice.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".