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Record W4387563987 · doi:10.4103/ijd.ijd_883_22

Clinical Effects of Pulsed Dye Laser Dynamically Combined with Triamcinolone Acetonide in the Treatment of Postoperative Recurrence Keloids

2023· article· en· W4387563987 on OpenAlexaboutno aff
Zhennan Liu, Jiamin Zhang, Xin Guo

Post-publication record

OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.

Bibliographic record

VenueIndian Journal of Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKeloidTriamcinolone acetonideSurgeryAdverse effectDermatologyInternal medicine

Abstract

fetched live from OpenAlex

Purpose: This study aimed to explore the clinical effects of pulsed dye laser (PDL) dynamically combined with triamcinolone acetonide (TAC) in the treatment of post-operative keloids recurrence. Materials and Methods: This study retrospectively analysed the clinical data of 29 keloid patients (with 39 keloids) from April 2014 to February 2020. The patients were divided into TAC group (14 patients with 19 keloids) and dynamic treatment group (15 patients with 20 keloids) according to the post-operative treatment that they received. The keloids were assessed by Vancouver scar scale (VSS), patient and observer scar assessment scale (POSAS) and the effect of keloids on the quality of life of patients was evaluated with dermatology life quality index (DLQI) scale before the surgical treatment, at any time of relapse, and 24 months after the surgical treatment. The recurrence-free interval, relative cure time, and the cumulative times of TAC injection when the relative cure could be assessed as achieved, and the incidence of adverse reactions were calculated. Results: Patients experiencing a recurrence within 2 years after surgery included 19 keloids (25.33%) that developed a recurrent event within 6 months, 34 keloids (45.33%) that within 12 months, and 39 keloids (52.00%) that within 24 months after surgery. Anterior chest keloid had the highest recurrence rate and ear keloid had the lowest recurrence rate. The total pigmentation and vascularity (VSS and POSAS) scores of patients' keloids in TAC group and dynamic treatment group 24 months after treatment were significantly lower than those before treatment and at relapse ( P < 0.05), the total VSS and POSAS scores were significantly lower at 24 months than before treatment and at relapse ( P < 0.05), and the DLQI scale score was significantly lower at 24 months than before treatment ( P < 0.05). The VSS and POSAS scores of patients' keloids at 24 months after treatment were significantly lower in the dynamic treatment group than in the TAC group. The relative cure time of patients' keloids in the dynamic treatment group was 6.47 ± 2.72 months, which was significantly shorter than 8.65 ± 3.67 months in the TAC group ( P < 0.05). The cumulative number of TAC injections that were given to achieve a relative cure of patients' keloids in dynamic treatment group was 3.60 ± 1.76, which was significantly less than 5.24 ± 2.25 in TAC group. The total incidence of adverse reactions was lower in the dynamic group than in TAC group, but this difference did not reach statistical significance ( P > 0.05). Conclusions: Compared with TAC injection alone, PDL dynamically combined with TAC in the treatment of keloid with post-operative recurrence can shorten the relative cure time, reduce the number of TAC injections and improve the clinical efficacy.

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)0.000
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.027
GPT teacher head0.360
Teacher spread0.333 · 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 designNon-randomized trial
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

Citations5
Published2023
Admission routes1
Has abstractyes

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