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Record W4402053093 · doi:10.25259/jcas_181_23

Efficacy of fractional carbon dioxide laser-assisted drug delivery in the management of post-burn scars – A prospective study

2024· article· en· W4402053093 on OpenAlexaboutno aff
Shekhar Neema, Senkadhir Vendhan, Biju Vasudevan, K Lekshmipriya, Senkadhirdasan Dakshinamurthy

Bibliographic record

VenueJournal of Cutaneous and Aesthetic Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineScarsCarbon dioxide laserProspective cohort studySurgeryLaserLaser surgery

Abstract

fetched live from OpenAlex

Objectives: The objective of our study is to assess the efficacy of fractional carbon dioxide (CO2) laser-assisted drug delivery (LADD) in the management of post-burn scars. Material and Methods: It is a prospective study conducted from March 2021 to February 2022, with 32 patients ranging in age from 9 to 52 years. The scars lasted anywhere from 6 months to 18 years. The ethical clearance of the Institutional Ethics Committee was obtained. The patient's median age was 22 (range, 09-52). Patients were assessed using a modified Vancouver scar scale (mVSS) score before and after receiving fractional CO2 laser at monthly intervals. Results: After one treatment, statistically significant improvements in pigment, thickness, and pliability were seen according to the mVSS scores, and these improvements persisted through the final laser session. Conclusion: Our study has demonstrated that fractional CO2 LADD seems to be an encouraging approach in the management of post-burn scars with good patient satisfaction.

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)0.000
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 score0.378
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.288
Teacher spread0.272 · 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
Published2024
Admission routes1
Has abstractyes

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