Potentials for implementing pressure‐controlled jet injection in management of keloids with intralesional 5FU and corticosteroids
Bibliographic record
Abstract
BACKGROUND: Needle-free jet injection implements kinetic energy of liquid jet for transcutaneous delivery of drugs into soft tissues. Combination therapy of intralesional 5-fluorouracil and triamcinolone offers efficacious treatment for keloids with a reduced adverse effect of the drug monotherapy. This study evaluates safety and efficacy of the drug combination administered to keloid scars via intralesional jet injections. METHODS: A retrospective analysis of the keloid treatments was performed. Efficacy was assessed by reviewing pre- and post-treatment scores of the Vancouver Scar Scale (VSS) and Patient and Observer Scar Assessment Scale (POSAS) and by comparing baseline and photographs taken 3 months after the treatments. Safety and tolerability were collected and analyzed. RESULTS: Twenty-one subjects (M/F = 11/10) with 39 keloids received the treatments. Treatments were well-tolerated by all patients at mean injection pain of 2.0 ± 1.0 per Numeric Pain Rating Scale (NPRS). Self-resolved lesion ulceration was observed in 4 patients. Post-treatment evaluation demonstrated a 53% decrease in total VSS score (P < 0.05) and in all sub-categories. Mean patient score of POSAS decreased in the color, stiffness, thickness, and irregularity components. Pain and pruritus lessened by 69% and 79% (P < 0.05 in both), respectively, among the patients with complaints prior to the treatment. Independent reviewers reported an average 51%-75% reduction in keloids. CONCLUSIONS: Improved appearance of keloids and symptomatic relief was achieved by intralesional administration of combined 5-fluorouracil and corticosteroid through the high-pressure jet injections. The synergy between the drug combination and the jet physical impact provided clinical effect.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".