A Prospective Controlled Study on Long-Term Outcomes of Facial Lacerations in Children
Bibliographic record
Abstract
Background: Although skin adhesives have been used for decades to treat skin lacerations, uncertainty remains about long-term results, and complications. Methods: In this prospective, controlled, single-blinded, observational cohort study, outcomes were assessed by five plastic surgeons with standardized photographs at 6–12 months using a modified Patient and Observer Scar Assessment Scale (POSAS) and Vancouver Scar Scale (VSS); additionally, the POSAS was performed by the patients/caregivers and the physician; pain, requirement of anesthesia, treatment time, costs, complications, and quality of live (QoL) were assessed. Results: A total of 367 patients were enrolled; 230 were included in the main analysis; 96 wounds were closed using tissue adhesives (group 1); 134 were sutured (group 2). Assessment by the independent observers revealed an improved mean modified overall POSAS score in group 1 in comparison with group 2 [2.1, 95% CI [1.97–2.25] vs. 2.5, 95% CI [2.39–2.63]; p < 0.001, d = 0.58] and mean VSS score [1.2, 95% CI [0.981–1.34] vs. 1.6, 95% CI [1.49–1.79], p < 0.001, d = 0.53]. At the early follow-up, dehiscence rate was 12.5% in group 1 and 3.7% in group 2 (p < 0.001); later on, one dehiscence remained per group. Mild impairment of QoL was found at the early follow-up in both groups, with no impairment remaining later on. Duration of treatment and treatment costs were lower in group 1. Conclusion: Both modalities of wound closure yield favorable esthetic results, and complications are rare. Adhesives are more cost-effective, and its application is less time-consuming; therefore, tissue adhesives offer considerable advantages when used appropriately. Trial Registration: Public trial registration was performed at www.ClinicalTrials.gov (Identifier: NCT03080467).
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".