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Record W4394892770 · doi:10.1093/jbcr/irae036.080

81 Effectiveness of Simultaneous Intense Pulsed Light and Fractional CO2 Laser Therapy in Hypertrophic Burn Scars

2024· article· en· W4394892770 on OpenAlexaboutno aff
Djoni Elkady, Brandon Larson, Steffi Sharma, Richard Lou, Anjay Khandelwal

Bibliographic record

VenueJournal of Burn Care & Research · 2024
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHypertrophic scarsIntense pulsed lightLaser therapyHypertrophic scarPulsed laserScarsLaserSurgeryDermatologyOptics

Abstract

fetched live from OpenAlex

Abstract Introduction Hypertrophic burn scars present challenges for patients and clinicians. Intense Pulsed Light (IPL) and Ablative Fractional CO2 Lasers (AFCL) have shown promise in scar treatment by targeting vascular structures and promoting collagen production. While IPL-AFCL has been used in managing hypertrophic scarring in various dermatological conditions, limited data exist for burn scar treatment. In addition, scar vascularity can frequently limit the depth of penetration and density of AFCL yielding delayed results. The author's conducted a study assessing the efficacy of simultaneous IPL-AFCL therapy on hypertrophic burn scars using the Modified Vancouver Scar Scale (MVSS). To the author's knowledge, this is the first reported case series of simultaneous laser treatment in the treatment of hypertrophic burn scars. Methods In this retrospective study (April 2021 to July 2023), data from patients (pediatric and adult) receiving at least two IPL-AFCL treatments were analyzed. Demographics, burn details, and complications were collected. Linear regression assessed the impact of time from burn to first treatment on MVSS scores. Unpaired t-tests compared pre/post-MVSS scores for partial-thickness (PT) and full-thickness (FT) burns, and paired t-tests evaluated pre/post-treatment MVSS score differences after IPL-AFCL treatment. Results The study involving 33 patients (11 PT burns, 22 FT burns), the mean pre-MVSS score was 12.09 ± 2.77, and post-MVSS score was 6.24 ± 2.96. IPL-AFCL significantly reduced MVSS scores by a mean of 5.85 ± 0.43 (p < 0.0001) with an average of 3.70 ± 1.69 IPL-AFCL treatments per patient. Significant reductions were also observed in pigmentation (p=0.001), vascularity, pliability, height, pain, and pruritus (p < 0.0001). Linear regression analysis showed that the duration from burn injury to the first laser treatment significantly influenced pre-MVSS scores (p=0.008) but not post-MVSS (p=0.062). No significant differences were found in pre-MVSS (p=0.186) and post-MVSS (p=0.233) scores between PT and FT burns. As for complications, 4/33 patients experienced blistering following treatment which did not result in any long-term consequences. Conclusions Our study demonstrated that IPL-AFCL treatment effectively improved hypertrophic burn scars. MVSS scores did not significantly differ between PT and FT burns, but the time from the initial burn to the first treatment significantly influenced pre-MVSS scores. Applicability of Research to Practice Simultaneous use of different light/laser modalities is safe and effective and may offer advantages with symptomatic, functional and cosmetic benefits.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.387
Teacher spread0.352 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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