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Record W4408161539 · doi:10.1111/jocd.70019

A Retrospective Analysis of the Effectiveness of Fractional <scp>CO</scp>₂ Laser Therapy in Treating Linear Scars: Investigating the Ideal Timing for Intervention

2025· article· en· W4408161539 on OpenAlexaboutno aff
Gang Gu, Long Ji, Xiaonan Qiu, Jing Zhang

Bibliographic record

VenueJournal of Cosmetic Dermatology · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineScarsHypertrophic scarSurgeryCosmesisAblative caseRadiation therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Linear scars, resulting from surgical incisions or traumatic injuries, can pose both aesthetic and functional dilemmas. Ablative fractional CO₂ laser (AFCL) therapy has been recognized for its ability to enhance the appearance and flexibility of scars; however, the ideal timing for such treatments remains a subject of debate. AIMS: This study retrospectively evaluates the effectiveness of AFCL in treating linear atrophic and hypertrophic scars, with a focus on identifying the optimal timing to achieve the best possible outcomes. METHODS: Patients who underwent treatment for linear scars using AFCL at our hospital between January 2022 and July 2024 were included in the study. Participants were categorized into two groups: those with atrophic scars and those with hypertrophic scars. Hypertrophic scars were assessed using the Vancouver Scar Scale (VSS), whereas atrophic scars were evaluated with the Scar Cosmesis Assessment and Rating (SCAR) scale. Furthermore, considering the timing of scar formation-with a six-month period as the threshold-two subgroups were categorized as early treatment and late treatment. The disparities in scar improvement rates were then computed and subjected to analysis. RESULTS: Among 55 patients, 31 had atrophic scars and 24 had hypertrophic scars. AFCL treatment significantly improved clinical scores in both groups. The SCAR score for atrophic scars decreased from 6.50 (SD 1.31) to 4.92 (SD 1.71) (p < 0.001), and the VSS score for hypertrophic scars decreased from 6.02 (SD 0.46) to 2.73 (SD 0.39) (p < 0.001). The early-treatment subgroup showed a 35.38% (SD 24.54%) improvement in atrophic scars, significantly higher than the 12.53% (SD 25.65%) in the late-treatment subgroup (p = 0.018). No significant timing effect was found for hypertrophic scars (p = 0.764). CONCLUSION: AFCL is an effective treatment for linear scars. Early intervention, specifically within the first 6 months, leads to superior outcomes for atrophic scars. In contrast, the timing of treatment is less critical for hypertrophic scars. TRIAL REGISTRATION: Chinese clinical trial registry: Registration no. ChiCTR2400092038.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.378
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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