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Record W4311994917 · doi:10.9734/jammr/2022/v34i234889

Evaluation of the Efficacy and Safety of Autologous Adipose Tissue-Derived Stem Cells in Treatment of Keloids

2022· article· en· W4311994917 on OpenAlexaboutno aff
Aya Ashraf Fouda, Naeim Mohamed Abd El-Naby, Mohamed Atteya Saad, Tarek Shoukr, Tarek Al-Sayed Amin

Bibliographic record

VenueJournal of Advances in Medicine and Medical Research · 2022
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdipose tissueVascularityStem cellSurgeryKeloidDermatologyInternal medicine

Abstract

fetched live from OpenAlex

Background: The formation of keloids is accompanied by undesirable aesthetic and psychological impacts. Different therapeutic techniques, including local injection, occlusive dressings, surgical excision, and lasers have been examined for keloids. This work objects to evaluate the efficacy and the safety of autologous adipose tissue-derived stem cells (ADSCs) in keloids treatment.
 Methods: This prospective clinical research involved 15 subjects with keloids who were injected with autologous ADSCs three sessions at monthly intervals. Follow up was done for 3 months after treatment and evaluation was done for improvement in Vancouver scar score, patient's opinion and physician's opinion.
 Results: In the studied patients, 8 patients (53.3%) showed good improvement (25 – 49%), 7 patients (46.7%) showed very good improvement (50 – 74%) and none of the patients (0%) showed excellent improvement. Side effects were mild and tolerable and included pain during injection and abdominal discomfort for few days after lipoaspiration.
 Conclusions: Adipose-derived stem cells are effective, safe and are of more value in improving consistency and vascularity of keloids.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.098
GPT teacher head0.474
Teacher spread0.376 · 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 designOther design
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
Published2022
Admission routes1
Has abstractyes

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Same venueJournal of Advances in Medicine and Medical ResearchSame topicDermatologic Treatments and ResearchFrench-language works237,207