Wound healing and pain evaluation following diode laser surgery vs. conventional scalpel surgery in the surgical treatment of oral leukoplakia: a randomized controlled trial
Bibliographic record
Abstract
Objectives This study aimed to compare patient-reported pain scores and clinician-assessed healing outcomes following the treatment of oral leukoplakia (OL) with a diode laser vs. a conventional scalpel. Methods A randomized, double-blind clinical trial (Brazilian Clinical Trials Registry (RBR-7pgcyq) was conducted involving histopathologically confirmed OL patients. Participants were randomly allocated to undergo treatment with either a diode laser or a scalpel. Pain was assessed at 24 h, 48 h, and 7 days using the Visual Analog Scale (VAS), while healing outcomes were clinically evaluated at 7 days, 1-month, and 3-months post-treatment using the Vancouver Scar Scale. Statistical analyses included the Mann–Whitney U-test for comparing pain and healing scores between interventions. Friedman test also was used to analyze healing progress over time. Results 64 patients were analyzed (33 in diode laser and 31 in scalpel group). No significant differences in pain scores were observed between the treatment groups at 24 h (p = 0.75), 48 h (p = 0.92), or 7 days (p = 0.44). Overall, pain levels varied significantly by OL location at 24 h (p = 0.001), 48 h (p = 0.01), and 7 days (p = 0.03), with tongue lesions associated with significantly higher pain compared to gingival lesions at 24 h (p = 0.005) and 48 h (p = 0.01), as well as compared to palatal lesions at 24 h (p = 0.01). Laser group showed significantly better healing compared to the scalpel group at 7 days (p = 0.01), with no significant differences observed at 1 month (p = 0.67) or 3 months (p = 0.25). Healing outcomes improved significantly over time in both arms (p < 0.001). Conclusions There was no significant difference between the diode laser and scalpel treatment arms regarding post operative pain scores. Diode lasers represent better healing at the first week post treatment, but with no differences over time. These findings support the use of either modality as viable management options for OL. Clinical Trial Registration Brazilian Clinical Trials Registry, identifier (RBR-7pgcyq).
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".