Efficacy and safety of needle-free jet injector-assisted intralesional treatments in dermatology—a systematic review
Bibliographic record
Abstract
Needle-free jet injectors are used for the intralesional treatment of various dermatological indications. However, a systematic review that evaluates the efficacy and safety of these treatments has not been published. The objectives of this study are to evaluate the efficacy and safety of needle-free jet injections for dermatological indications and to provide evidence-based treatment recommendations. An electronic literature search was conducted in April 2022. Two reviewers independently selected studies based on predefined criteria and performed a methodological quality assessment using the Cochrane Collaborations risk-of-bias 2.0 assessment tool and Newcastle-Ottawa Scale. Thirty-seven articles were included, involving 1911 participants. Dermatological indications included scars, alopecia areata, hyperhidrosis, nail diseases, non-melanoma skin cancer, common warts, local anesthesia, and aesthetic indications. Keloids and other types of scars (hypertrophic, atrophic, and burn scars) were investigated most frequently (n = 7). The included studies reported favorable efficacy and safety outcomes for intralesional jet injector-assisted treatment with triamcinolone acetonide/hexacetonide, 5-fluorouracil, bleomycin, or hyaluronic acid. Two high-quality studies showed good efficacy and tolerability of intralesional jet injections with a combination of 5-fluorouracil and triamcinolone acetonide in hypertrophic scars and with saline in boxcar and rolling acne scars. No serious adverse reactions and good tolerability were reported in the included studies. Overall, the methodological quality of the included studies was low. Limited evidence suggests that needle-free jet injector-assisted intralesional treatment is efficacious and safe for hypertrophic and atrophic acne scars. More well-powered RCTs investigating the efficacy and safety of jet injector treatment in dermatology are warranted to make further evidence-based recommendations.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".