MétaCan
Menu
Back to cohort
Record W4377194908 · doi:10.56056/amj.2023.203

The Use of Acellular Dermal Matrix for the Closure of Skin Defects

2023· article· en· W4377194908 on OpenAlexaboutno aff
Areen Mahmood Salih, Sabir Osman Mustafa

Bibliographic record

VenueAdvanced medical journal · 2023
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSkin graftingSurgeryHematomaWound healingAcellular DermisProspective cohort studyWound closureArtificial skinDermatologyImplant

Abstract

fetched live from OpenAlex

Background & Objectives: Skin substitutes are a diverse set of biologics, synthetics, and biosynthetic materials that can replace open skin wounds temporarily or permanently. Skin substitutes are designed to mimic the qualities of natural skin. One must select an option that accomplishes an excellent wound healing and closure. This study aimed to assess the reliability and effectiveness of ?acellular dermal matrix for potentially more pliable coverage of the wound and for better ?functional and aesthetic appearance of the skin defects. Methods: A prospective cohort study performed on 20 patients with full-thickness skin defects who underwent surgery using acellular dermal substitute and skin grafting in Erbil Governorate from January 2017 to December 2019. Functional and aesthetic outcome has been evaluated in this study. Results: The study included 20 patients with mean age of 18.8 ± 6.2 years, female to male ratio was 1.5:1, and the majority of the cases presented with burn (90%). The Vancouver Scar Scale score was significantly reduced after 1 month of follow-up in which it reduced by 4.12 mm (57.6% reduce from baseline), Mean healing score was 93.5%, and Re-epithelialization after 1 month Was 95.55%, Overall the complication rate is low with 5% had hematoma, 5% had infection and 5% had loss of graft. Conclusion: The use of acellular dermal matrix in conjunction with split thickness skin graft result in substantial improvement in the quality of wound healing and tissue reconstruction.

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)0.002
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 score0.848
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.046
GPT teacher head0.364
Teacher spread0.318 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced medical journalSame topicWound Healing and TreatmentsFrench-language works237,207