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Record W3131637539 · doi:10.1111/wrr.12904

Pulsed dye laser versus ablative fractional <scp>CO<sub>2</sub></scp> laser in treatment of old hypertrophic scars: Clinicopathological study

2021· article· en· W3131637539 on OpenAlexaboutno aff
Lamia Hamouda Elgarhy, Rania Ahmed El‐Tatawy, Dareen Mohamed Abdelaziz, Noha Nabil Dogheim

Bibliographic record

VenueWound Repair and Regeneration · 2021
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsScarsMedicineAblative caseMasson's trichrome stainVascularityH&E stainHypertrophic scarsTrichromeLaser treatmentLaserSurgeryNuclear medicineStainingPathologyOptics

Abstract

fetched live from OpenAlex

Abstract There is a continuous need to find out the best treatment for old hypertrophic scars (OHSs). Thirty patients with OHSs were included. Each scar was divided into right half treated with PDL (handpiece with a 7‐mm spot, pulse duration of 1.5 ms and fluence of 6 J/cm 2 ) and left half treated with FrCo2 laser (15 W, spacing 800 μm, dwelling time 600 μs and stack 3) once every month for three sessions. Scars were assessed before and after treatment clinically by Vancouver Scar Scale (VSS) and histologically using hematoxylin and eosin (H&amp;E), Masson trichrome and orcein stains. Both halves showed statistically significant improvement after treatment. However, there was no statistically significant difference in VSS between them ( P = 0.176). FrCo2 laser showed more significant improvement in pliability and height ( P p = 0.017, P h = 0,011), while, PDL showed more significant improvement in vascularity ( P = 0.039) of OHSs. Both PDL and ablative FrCo2 laser were effective in the treatment of OHSs, however, FrCo2 laser was more effective in improving OHSs pliability, and height which are the main concern in OHSs.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.195
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.048
GPT teacher head0.337
Teacher spread0.288 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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