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Record W3027609446 · doi:10.1177/2292550320925922

Donor Site Scar Preference in Patients Requiring Free Flap Reconstruction

2020· article· en· W3027609446 on OpenAlexaff
Graham McLeod, Avinash Islur

Bibliographic record

VenuePlastic Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsUniversity of Manitoba
FundersAgency for Healthcare Research and Quality
KeywordsMedicineScarsThighAbdomenSurgeryGroinFree flapUpper abdomen

Abstract

fetched live from OpenAlex

INTRODUCTION: In traumatic reconstruction, surgeons frequently harvest flaps from donor sites that they are comfortable performing and with favourable tissue characteristics without determining the patients preferred site. The study's goal was to determine participants free flap donor site preference based on aesthetics as it relates to the size of the defect being reconstructed. METHODOLOGY: Participants were asked to imagine that they were in a trauma that resulted in a wound of variable sizes. They were presented with a selection of common donor site scars produced from harvesting small, medium, and large free flaps. They were instructed to rank the donor sites in order of preference and score each donor site of 10. RESULTS: Two hundred eighty-seven participants (mean age: 28, female: 62%) completed the survey. For small reconstructions, the preferred donor site scars were on the leg or back compared to arm or abdomen. For medium size reconstructions, scars on the back and upper thigh were preferred over scars on the abdomen and anterior thigh. In small and medium reconstructions, the midline abdominal scar scored significantly lower than other donor sites. Participants preferred donor sites on the back, the thigh, and lower abdomen for large reconstructions. CONCLUSION: Participants preferred back, thigh, and hip locations perhaps relating to the ability to conceal these scars under clothing. If multiple flaps sites could be harvested, providing options to trauma patients undergoing free tissue transfer may result in increased satisfaction.

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)0.005
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 score0.045
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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 head0.036
GPT teacher head0.218
Teacher spread0.182 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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