Potential of shock wave therapy in decubitus foot ulcer ??? clinical efficiency and objectiveassessment
Bibliographic record
Abstract
Current studies confirm the clinical utility of shock wave therapy (SWT) in chronic wounds including venous leg ulcers (VLU), pressure ulcers (PU) and decubitus foot ulcers (DFU). Nevertheless, there is a demand to conduct research in this area using objective measurement methods. The aim of this case study was to assess the effectiveness of the SWT procedure in a DFU patient after a toe amputation. The patient underwent a single radial SWT procedure with CELLACTOR® SC1 device (Storz Medical, AG, Tagerwilen, Switzerland). Treatment parameters included: number of shots 300 baseline + 100 per each cm2, pressure of 2.5 bars, energy of 0.15 mJ/mm2 and frequency of 5 Hz. Planimetric smartphone application (Swift App., Swift Medical, Canada) was used to assess the effects in objective manner. The measurements were taken directly before and one week after the SWT procedure. Planimetric evaluation showed significant improvement in the wound surface. A decrease in all metric parameters of the wound was observed: total area by 50% (from 5.8 to 2.9 cm2), length by 21% (from 3.1 to 2.9 cm) and width by 28% (from 2.7 to 1.9 cm). In conclusion, ESWT seems to be a promising therapeutic option in DFU management
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".