Evaluation of a muscle pump‐activating device for non‐healing venous leg ulcers
Bibliographic record
Abstract
This evaluation involves an innovative muscle pump-activating device (geko™) as an adjunctive therapy with best practices for non-healing venous leg ulcers (VLUs). Stimulating the common peroneal nerve (at the fibular head), the geko™ device creates a response that acts as foot and calf muscle pumps, increasing venous, arterial and microcirculatory flow. The aim was to evaluate and determine if the geko™ is effective in this population and if it should be added to the medical supply formulary. In all, 12 patients with 18 recalcitrant VLUs (defined as less than 30% reduction in wound size in 30 days with best practices) in two community settings in Ontario consented to the evaluation and were treated with the geko™ for up to 20 weeks. A total of 44% of wounds healed, and 39% decreased in size. One patient non-adherent with the geko™ and best practices had deterioration in his or her wounds. With the patients as their own control, the mean weekly healing rate with the geko™ was 9·35% (±SD 0·10) compared to 0·06% (±SD 0·10) prior to baseline, which was statistically significant (P < 0·01). Three patients not in optimal therapy increased compression due to decreased pain, further enabling healing. This study was not a randomised investigation, although the patients acted as their own controls. A pragmatic evaluation reflects the reality of the community sector; in spite of best practices or evidence-based care, therapy is not uniformly applied, with some participants unable to tolerate or indeed comply with optimal compression therapy. Rash occurred under the devices in 7 of 12 (58%) patients. One patient stopped the device due to rash, while another had to take breaks from using the device. Subsequently, the manufacturer (FirstKind Ltd) has developed a new device and protocol specific to the requirements of wound therapy to minimise this response. This small case series demonstrated the highly significant effectiveness of the geko™ device in these hard-to-heal VLUs. Further evaluations to determine dose and patient selection criteria are underway.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".