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Record W4283743958 · doi:10.1111/jocd.15195

<scp>Endo‐Radiofrequency</scp> subcision for acne scars treatment: A case series study

2022· article· en· W4283743958 on OpenAlexaff
Mohammad Ali Nilforoushzadeh, Maryam Heidari‐Kharaji, Tannaz Fakhim, Elham Torkamaniha, Maryam Nouri, Shohreh Rafiee, Masoumeh Roohaninasab, Elham Behrangi, Fariba Jaffary

Bibliographic record

VenueJournal of Cosmetic Dermatology · 2022
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMedicineAcneAcne scarsScarsPatient satisfactionDermatologyDermisPsychosocialSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Acne scars have important psychosocial suffering for patients. Several interventions have been utilized to treat acne scars that have different degrees of efficacy and side effect. Multimodal method can attain better results to improving the physical appearance of the patients that can significantly increase the quality of life. Subcision is a recognized treatment procedure particularly for rolling acne scars, but it needs modification to increase the effect of procedure. AIMS: The aim of the study was to assess the efficacy and safety of Endo-Radiofrequency (Endo-RF) subcision in acne scars treatment. METHODS: In this study, 9 adult patients with atrophic acne scars were enrolled. The patients receive Endo-RF subcision one time and followed up for 6 months. Outcome was measured using biometric assessment by Visioface 1000 D, Mexameter and skin ultrasound imaging system, post-treatment photographs and patient's satisfaction. RESULTS: The results showed that patients had significant improvement from baseline according to the reduction of the number of skin fine and large pore (p < 0.05) and spots (p < 0.05). Also, the density and thickness of the dermis and epidermis were significantly increased (p < 0.05). CONCLUSIONS: Endo-RF subcision modality can consider as a safe and effective method for acne scar treatment.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.044
GPT teacher head0.352
Teacher spread0.308 · 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 designCase report
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

Citations3
Published2022
Admission routes1
Has abstractyes

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