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Record W3010112395 · doi:10.1093/jbcr/iraa024.305

721 Treatment of Hypertrophic Burn and Wound Scars Using a Novel Cold Laser System

2020· article· en· W3010112395 on OpenAlexaboutno aff
Jenn Tsai, Samy Bendjemil, Colin Dowling, Stathis Poulakidas

Bibliographic record

VenueJournal of Burn Care & Research · 2020
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHypertrophic scarHypertrophic scarsScarsDermisIntense pulsed lightSurgeryWound healingDermatologyPathology

Abstract

fetched live from OpenAlex

Abstract Introduction Hypertrophic scars are seen in 70% of individuals after a burn. Survival from acute burns have psychosocial and functional challenges. Hypertrophic scars contain disorganized whorls of collagen, an increase in occluded blood vessels resulting in raised discoloration, inflamed dermis/epidermis and painful sequelae. Management of such scars have been limited to invasive and non-invasive management. One innovative technology is a non-invasive high-intensity laser operating at 1275 nm and 74 Watts, optimizing increased depth of penetration into the tissue utilizing photomechanical effects to biostimulate tissue to heal and regenerate. We present a series of 10 patients. Methods 10 patients were enrolled with hypertrophic scarring secondary to deep partial or full thickness burns. Hypertrophic areas were identified and numerical pain scale, Vancouver Scar Scale and the World Health Organization Quality of Life score were recorded. The non-contact, high-intensity laser was passed over the hypertrophic scars, continuously moving the laser over the entirety of the scar. Each area of hypertrophic scar tissue was lasered for progressively longer sessions, reaching a therapeutic time of 10 min in each section. Results Patients were utilizing previously known non-invasive therapies for scar reduction, such as, compression garments, scar treatment ointments, as well as steroid injection and non-medical therapies such as acupuncture. In our series, 90% of the patients reported decrease in scar pain, inflammation, pigmentation and improved pliability by the second treatment. Decreased scar height was identified by the eighth session, where conventional protocols could require months to years before any changes were observed. Changes in the scars were even identified after the normal time period identified for maximal improvement using conventional burn therapies. In a survey presented to patient, even pain was improved, identified with reduction in narcotic/NSAID use in patients undergoing the therapies. Conclusions Non-invasive high-intensity laser therapies are useful adjuncts for reduction of hypertrophic burn scars. Our case series presents a treatment option in patients that have functional, physical and cosmetic challenges. We anticipate broader applications for hypertrophic burn scar reduction utilizing adjunctive non-invasive laser therapy, reducing the need for invasive scar revision and limiting psychosocial strain. Applicability of Research to Practice In this case series, non-invasive high-intensity laser therapy provided timely decrease in hypertrophic scar characteristics in an outpatient setting. Thus, leading to decrease in invasive operative therapy and overall improvement in quality of life. Further studies are needed to elucidate other benefits and utility of the laser and possible evaluation of keloid scars.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.163
GPT teacher head0.402
Teacher spread0.239 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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