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Record W4224240977 · doi:10.1177/22925503221094106

Keystone Flap for Closure of Skin Cancer Defects on the Upper Extremity

2022· article· en· W4224240977 on OpenAlexaff
Travis Gordon, Andrew P. Golin, Alexander Anzarut

Bibliographic record

VenuePlastic Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineSkin cancerSurgeryBasal cell carcinomaBasal cellCancerForearmPathologyInternal medicine

Abstract

fetched live from OpenAlex

Background: We sought to examine the efficacy of the Keystone Design Perforator Island Flap (KDPIF) for the reconstruction of skin cancer excision defects isolated to the upper extremity. In particular, to examine the size of defects repaired and the complications associated with the keystone flap procedure isolated to the upper extremity. Methods: This is a retrospective chart review including all patients older than 18 years of age who received a KDPIF procedure between February 2013 and February 2019 for the oncologic reconstruction of skin cancer defects isolated to the upper extremities by a single surgeon. All procedures were done according to the original description by Behan. Results: A total of 32 patients, 18 (56%) male and 14 (44%) female, received 35 keystone flaps between February 2013 and February 2019. The mean age of the males and females was 70.5 and 79.7 years of age, respectively. Thirty-five lesions suspicious for cancer were excised and 14 (40%) basal cell carcinoma (BCC), 11 (31%) squamous cell carcinoma (SCC), 9 (26%) melanoma, and 1 (3%) actinic keratoses diagnoses were histopathologically determined. Skin defect excisions varied from 3.53 cm 2 to 31.42 cm 2 . No intraoperative or postoperative complications occurred. Conclusions: The keystone flap is a successful versatile flap procedure with a low or absent complication rate for the reconstruction of skin cancer excision defects of various locations (eg arm, hand, elbow, forearm, shoulder, and wrist), cancer pathologies, and sizes on the upper extremity. When needed, a Doppler may successfully identify adequate perforating blood vessels for the relatively larger flaps.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score1.000

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)0.0010.000

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 head0.264
Teacher spread0.238 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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