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2016· letter· en· W3036455313 on OpenAlexaffabout
Christopher J. Coroneos, Sophocles H. Voineskos, Adrian M. Heller, Ronen Avram

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2016
Typeletter
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsJuravinski HospitalMcMaster University
Fundersnot available
KeywordsMedicineDIEP flapBreast reconstructionSurgeryRadiologyBreast cancerInternal medicine

Abstract

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Sir: The publication “SIEA versus DIEP Arterial Complications: A Cohort Study” (Plast Reconstr Surg. 2015;135:802e–807e) has understandably, and intentionally, incited discussion regarding the clinical utility of the superficial inferior epigastric artery (SIEA) flap in an approach to breast reconstruction. The letter by Miyamoto and Fujiki, Criteria for the Use of the SIEA Flap for Breast Reconstruction, identifies points of equipoise in planning and execution of the SIEA flap. In our study, we indicate that preoperative imaging was not performed because of center resource limitations. We disagree with the inference by Miyamoto and Fujiki that preoperative imaging improves outcomes among SIEA flaps. Although comparative evidence and syntheses demonstrate benefit among deep inferior epigastric perforator (DIEP) flaps,1 evidence is limited for SIEA flaps.2 It is unclear whether evidence can be extrapolated from the DIEP literature. Furthermore, no evidence exists to support a relationship between the size and/or reliability of the SIEA, and the presence or absence of a robust deep system. Although previous reports have used an intraoperative artery diameter criterion,3,4 this is unlikely to correlate with preoperative imaging. The SIEA is a superficial vessel, and in our experience it is prone to spasm. We believe an artery measuring 1.5 mm on intraoperative observation is likely larger on preoperative imaging, although evidence is again lacking. Regarding intraoperative decision-making, Miyamoto and Fujiki comment on selection of recipient vessels and intraoperative surrogates of flap viability. These points do not address the inherent limitations of SIEA variability, caliber, and angiosome. We acknowledge that the thoracodorsal artery may limit size mismatch versus use of the internal mammary artery. Furthermore, tissue oxygen saturation may be an accurate intraoperative assessment of flap inflow. However, neither of these intraoperative approaches accounts for four of the six SIEA failures in our study occurring later than 48 hours postoperatively. Issues stemming from vessel size mismatch would lead to a greater proportion of immediate failure; we observed late failure, and a high proportion of partial flap loss with necrosis requiring débridement. Furthermore, the intraoperative period is too short of a time frame for assessment of tissue oxygen saturation to adequately predict late SIEA failure. We appreciate that preoperative and intraoperative modalities and algorithms are increasingly applied to free flaps for breast reconstruction. However, intraoperative algorithms require subjective expert interpretation.4,5 Definitive recommendations for interpretation of preoperative imaging and tissue vascularity with intraoperative laser fluorescence3 or oxygen saturation are lacking. Our discussion does not suggest that SIEA flaps should no longer be performed. Instead, we demonstrate the reliability of the DIEP flap for surgeons and institutions intending to develop a consistent approach to breast reconstruction, and provide an element of comfort to new microsurgeons beginning practice. At our center, microsurgical breast reconstruction is performed by a single surgeon, who is then available for all reexplorations. Most notably for young microsurgeons, DIEP flaps were successful in 98 percent of cases from the onset of a breast reconstruction practice without preoperative imaging, or modalities for intraoperative perfusion assessment. Although we demonstrate moderate success (85 percent) with SIEA flaps, this is not an acceptable success rate in the modern era of breast reconstruction. At our center, it is difficult to justify the uncertainty of an intraoperative algorithm and preoperative imaging associated with SIEA flaps, when we can offer patients the reliability seen with DIEP flaps. DISCLOSURE The authors have no financial interest to declare in relation to the content of this communication. Christopher J. Coroneos, M.D., M.Sc. Sophocles H. Voineskos, M.D., M.Sc. Adrian M. Heller, M.D. Ronen Avram, M.D., M.Sc. Division of Plastic Surgery Department of Surgery McMaster University Hamilton, Ontario, Canada

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0150.022
Insufficient payload (model declined to judge)0.0230.018

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 head0.020
GPT teacher head0.239
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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