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Record W4389306618 · doi:10.1097/dss.0000000000004041

Assessment of Donor Site Scar Outcomes, Healing Time, and Postoperative Complications Associated With Split Thickness Skin Grafts Harvested From the Hair Bearing Scalp

2023· article· en· W4389306618 on OpenAlexaboutno aff
Maria Sarah Bovenberg, Paige E. Williams, Leonard H. Goldberg

Bibliographic record

VenueDermatologic Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsScalpMedicineSurgeryWound healingScar tissueHair transplantationDermatology

Abstract

fetched live from OpenAlex

BACKGROUND: The hair-bearing scalp is an underused donor site for split-thickness skin grafts (STSG). OBJECTIVE: Evaluating the donor site scar outcomes, healing times, and complications associated with STSG harvested from the hair-bearing scalp. MATERIALS AND METHODS: During this prospective observational study, donor site healing was assessed on postoperative Days 8 and 30. Donor site scar outcomes were quantified at 1 month using the Vancouver Scar Scale. All postoperative complications were collected during the 30-day follow-up window. RESULTS: 80% of donor sites was fully healed at 1-week follow-up. Vancouver Scar Scale score at the donor site was 0.26 at 1-month follow-up. All patients experienced full hair regrowth. Maximum pain scores were reported on the night of surgery (Vancouver Scar Scale 1.8), with quick resolution in days to follow. No major complications were reported. All STSG obtained from the scalp had full take and good texture and color match with the recipient site. CONCLUSION: The hair-bearing scalp is an excellent donor site for split-thickness skin graft harvesting.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.281
Teacher spread0.254 · 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 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

Citations4
Published2023
Admission routes1
Has abstractyes

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