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.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".