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Record W3009103032 · doi:10.1093/jbcr/iraa024.268

648 Direct Comparison of Fractional Carbon Dioxide Lasers Systems: Ablative Well Properties and Healing

2020· article· en· W3009103032 on OpenAlexaff
Heather M. Powell, Molly E. Baumann, Kevin L. McFarland, Jennifer Zuccaro, Britani N. Blackstone, J. Kevin Bailey, Dorothy M. Supp, Joel Fish

Bibliographic record

VenueJournal of Burn Care & Research · 2020
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsAblative caseLaserMedicineEx vivoFluenceBiomedical engineeringCarbon dioxide laserErythemaIn vivoNuclear medicineSurgeryOpticsLaser surgery

Abstract

fetched live from OpenAlex

Abstract Introduction Ablative lasers are a common tool for burn scar remodeling with numerous commercially available systems, each with varying capabilities. Among fractional CO2 (FXCO2) laser systems, the same nomenclature is utilized to describe properties of the laser including beam fluence and fractional coverage. Despite identical laser settings for these properties, the outcomes in two patient cohorts utilizing two different FXCO2 laser systems were notably different. As a result, a direct comparison of ablative wells, fractional coverage and healing between the two systems was conducted using ex-vivo and porcine models. Methods An ex-vivo study comparing fractional coverage settings (1%, 3%, and 5%) between the two different FXCO2 laser systems was first carried out (all measurements were obtained by a blinded rater using a high-powered microscope to quantify ablative area). Porcine skin was then treated with the two systems at 10–70 mJ. To compare ablative well properties, biopsies were collected and serial sectioned with the deepest/widest point of each well calculated from the histological section using ImageJ. Fractional coverage for each laser system was quantified for three different settings: 70 mJ 1%, 70 mJ 5%, and 30 mJ 5%. Finally, re-epithelialization rate (as measured by transepidermal water loss), erythema and expression of genes encoding inflammatory cytokines were quantified in a porcine burn model prior to and at multiple time points following treatment with both laser systems (70 mJ, 5% fractional coverage). Results The two laser systems produced significantly different ablative wells. In the ex-vivo study, the fractional coverage measurements obtained differed from those provided by the manufacturer by 1.6 - 8.9%. In the porcine study, at 70 mJ, the ablative wells created from system 1 were deep and narrow, on average 1251 + 183 µm deep and 142 + 32 µm wide whereas wells from system 2 were shallow and wide, 374 + 44 µm deep and 267 + 35 µm wide. Following treatment, scars treated with system 2 re-established barrier function within 7 days whereas scars treated with system 1 re-established within 4 days. A significant increase in gene expression for IL-6 was observed in both systems at 1-hour post laser. Expression levels returned to baseline in system 2 by 24 hours whereas a return to baseline was not observed until the 96-hour time point for system 2. Conclusions While different FXCO2 laser systems utilize the same nomenclature for user selected properties, the same settings are not equivalent between systems resulting in significantly different ablative wells and downstream healing. Applicability of Research to Practice Laser systems should not be considered interchangeable despite being programmed for the same settings.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.169
GPT teacher head0.412
Teacher spread0.243 · 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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Citations2
Published2020
Admission routes1
Has abstractyes

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