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Record W4291008770 · doi:10.3390/curroncol29080448

Donor-Site Morbidity and Quality of Life after Autologous Breast Reconstruction with PAP versus TMG Flap

2022· article· en· W4291008770 on OpenAlexvenueno aff
Angela Augustin, Petra Pülzl, Evi M. Morandi, Selina Winkelmann, Ines Schoberleitner, Christine Brunner, Magdalena Ritter, Thomas W. Bauer, Tanja Wachter, Dolores Wolfram

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurgeryBreast reconstructionQuality of life (healthcare)TransplantationBreast cancerCancerInternal medicine

Abstract

fetched live from OpenAlex

The transverse myocutaneous gracilis (TMG) and the profunda artery perforator (PAP) flap are both safe choices for autologous breast reconstruction originating from the same donor region in the upper thigh. We aimed to compare the post-operative outcome regarding donor-site morbidity and quality of life. We included 18 patients who had undergone autologous breast reconstruction with a PAP flap (n = 27 flaps). Prospective evaluation of donor-site morbidity was performed by applying the same questionnaire that had already been established in a previous study evaluating TMG flap (n = 25 flaps) outcome, and results were compared. Comparison of the two patient groups showed equivalent results concerning patient-reported visibility of the donor-site scar and thigh symmetry. Still, the TMG group was significantly more satisfied with the scar (p = 0.015) and its position (p = 0.001). No difference was found regarding the ability to sit for prolonged periods. Donor-site wound complications were seen more frequently in the PAP group (29.6%) than in the TMG group (4.0%). Both groups expressed rather high satisfaction with their quality of life. Both flaps show minimal functional donor-site morbidity and high patient satisfaction. To minimize wound healing problems in PAP patients, thorough planning of the skin paddle is necessary.

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)0.000
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 score0.367
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.079
GPT teacher head0.359
Teacher spread0.281 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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