Clinical efficacy of fractional carbon dioxide laser in treatment of hypertrophic scars at different stages
Bibliographic record
Abstract
Objective To compare the clinical efficacy of fractional carbon dioxide laser in the treatment of hypertrophic scars at different stages. Methods Forty-five patients with 6-~8-month hypertrophic scars who met our inclusion criteria and were admitted to our department from February 2018 to June 2018 were recruited in this study. They were divided into control group (n=12), half-year group (n=15) and 1-year group (n=18). Each patient was treated with conventional treatments (stress and medication), and the patients in the control group were not treated with laser, those in the half-year group and 1-year group were treated with carbon dioxide laser from scar formation for half year (at admission) and for 1 year (half year after admission), respectively. Laser radiation were performed every 3 months. The scars were scored by Vancouver Scar Scale (VSS) at admission and 24 months after scar formation. The times of treatment, loss of working, incidence of side effects and patient satisfaction were also recorded. Results VSS score, scar thickness score and scar softness score were significantly higher in the control group than the half-year group and 1-year group (P < 0.05), but no such statistical differences were seen between the latter 2 groups (P>0.05). Compared with the 1-year group, the half-year group had obviously higher times of laser radiation (P < 0.05), longer loss of working time (P < 0.05), and similaryly lower incidence of pigmentation (P>0.05). The patient satisfaction rate was notably higher in the half-year group and the 1-year group than that of control (P < 0.05). Conclusion It is safe and effective to treat hypertrophic scar with fractional carbon dioxide laser in half and 1 year after scar formation, and there are no obvious differences in the efficacy between the 2 time points.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".