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Record W2333994431 · doi:10.1097/prs.0b013e31826da07e

Scar Treatment with Fractional Laser

2012· article· en· W2333994431 on OpenAlexaboutno aff
Moisés Wolfenson, Fernando Cerqueira Norberto dos Santos Filho

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2012
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineConfidence intervalScarsSurgeryVascularityProspective cohort studyInternal medicine

Abstract

fetched live from OpenAlex

Sir:FigureSeveral nonablative lasers have been developed in an effort to improve scars without compromising the skin and thus to eliminate the majority of risks associated with its use.1–3 Those types of lasers have a greater effect on the skin because they are able to heat the dermis and spare the epidermis. This prospective, analytical, clinical study, type series of cases included 42 patients, 30 female patients (71.4 percent) and 12 male patients (28.6 percent), aged 16 to 75 years (average, 32.43 ± 2.05 years; 95 percent confidence interval, 28.29 to 36.57 years). This research has been approved by the Ethics Committee for Research Involving Humans of Multiplastic Clinic with the support of the Federal University of Pernambuco (no. 409-403). For 17 patients (40.5 percent), the scars were sequelae of accidents, and 25 patients (59.5 percent) had plastic surgery scars. The procedures were performed in three to 12 steps per session, with an average of 9 ± 1 sessions (95 percent confidence interval, 7 to 10) and 89 ± 8 spots (95 percent confidence interval, 72 to 105 spots). The modification of the Vancouver Scar Scale4 consisted of hardening and texture corresponding to pliability; and color representing pigmentation and vascularity. Comparisons of results 90 and 180 days after surgery were performed with chi-square test, and compared using the Wilcoxon test at a significance level of 0.05. At 90 days after surgery, there was a predominance of tough hardening (42.9 percent), thick surface (42.9 percent), and brown pigmentation (38.1 percent) (Table 1). These alterations together were interpreted as bad surgical results for 26 patients (62.0 percent). At 180 days after surgery, 21 patients (50.0 percent) were evaluated as having excellent results, 15 (35.7 percent) had good results, and six (14.3 percent) had bad results because of complications such as keloid (four cases) or scar enlargement (two cases). Regarding surgical results, we identified 26 patients (62.0 percent) with dark, irregular scars and eight cases (19.0 percent) with good or excellent results 90 days after surgery. These results changed at 180 days after surgery to a predominance of excellent scars for 50.0 percent of patients; the remaining six patients (14.3 percent) had bad results, represented by keloid formation or scar enlargement (Fig. 1).Table 1: Intensity of Alterations Obtained in the 42 Patients TreatedFig. 1: Result of necrosis of nasal tip showing sequelae of open rhinoplasty (left, preoperative view; right, postoperative view).The literature considers that this type of laser (fractional) has shortened recovery from 2 to 4 months to 24 to 48 hours, always with the skin/epidermis preserved. It is important to point out the use of the modified Vancouver Scar Scale we adopted in this study, as other authors did.3,4 The fractional laser is a great technical evolution for plastic surgery and yields excellent results in scar treatment. It is safe, simple, and efficient in different face and body regions; in addition, it does not require topical or other anesthetic, which makes it well tolerated in all cases. Moisés Wolfenson, M.D. Clínica Multiplástica do Recife, Recife, Pernambuco, Brazil Fernando Cerqueira Norberto dos Santos Filho Federal University of Pernambuco, Clínica Multiplástica do Recife, Recife, Pernambuco, Brazil DISCLOSURE The authors have no financial interest to declare in relation to the content of this article. PATIENT CONSENT The patient provided written consent for use of the patient's images.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

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)0.0010.000

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 head0.037
GPT teacher head0.288
Teacher spread0.251 · 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.

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

Citations2
Published2012
Admission routes1
Has abstractyes

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