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Record W2756276800 · doi:10.1111/ddg.13337

Superiority of occipital donor sites for split‐thickness skin grafting in dermatosurgery: Results of a prospective randomized controlled study

2017· article· en· W2756276800 on OpenAlexaboutno aff
Maximilian Kovács, Syrus Karsai, Maurizio Podda

Bibliographic record

VenueJDDG Journal der Deutschen Dermatologischen Gesellschaft · 2017
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOcciputRandomized controlled trialSurgeryThighSkin graftingProspective cohort study

Abstract

fetched live from OpenAlex

BACKGROUND: Split-thickness skin grafts are commonly used in dermatosurgery. For occipital donor sites, retrospective studies have shown good results with respect to graft take and healing rates. Nevertheless, the majority of grafts in dermatosurgery are harvested from the thigh. To date, there has been no prospective randomized controlled study comparing occipital versus femoral donor sites. PATIENTS AND METHODS: Following micrographically controlled R0 tumor resection, 108 patients were randomized prior to undergoing split-thickness skin grafting (donor site: occiput vs. thigh). Follow-up examinations were carried out on day 3, 5, 7, and 14, as well as one month and three months after surgery. Documented data included graft take rates, re-epithelialization rates at the donor site, pain, cosmetic outcome, Vancouver Scar Scale (VSS), and complications. RESULTS: Occipital donor sites showed significantly faster reepithelization, less pain, fewer complications, a better cosmetic outcome, and better results on the VSS. With regard to graft take rates, grafts harvested from the occiput were significantly superior on days 3 and 5. CONCLUSIONS: This is the first randomized controlled trial showing a significant superiority of occipital compared to femoral donor sites regarding re-epithelialization, pain, cosmetic outcome and the Vancouver Scar Scale.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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Same venueJDDG Journal der Deutschen Dermatologischen GesellschaftSame topicReconstructive Surgery and Microvascular TechniquesFrench-language works237,207