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Record W1841283521 · doi:10.1177/229255031302100207

Effects of dextran-40 on flap viability after modified radical mastectomy

2013· article· en· W1841283521 on OpenAlexvenueno aff
Barış Yıldız, Barlas Sülü

Bibliographic record

VenueCanadian Journal of Plastic Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineModified Radical MastectomyDextranSurgeryMastectomyInternal medicineBreast cancerBiochemistryCancerBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Postoperative management of patients after modified radical mastectomy has evolved over the past decades. In the early postoperative period, wound complication rates were reported to be as high as 60%. Flap necrosis after modified radical mastectomy is a common problem encountered by surgeons. Various treatment strategies have been proposed in the literature but none have addressed the use of dextran-40. OBJECTIVE: To determine whether dextran-40 infusion improves skin flap viability after modified radical mastectomy. METHODS: Twenty-eight patients who underwent modified radical mastectomy were randomly assigned to receive dextran-40 or no dextran-40 intraoperatively after flap dissection. Patients were followed prospectively over a five-year period in a community hospital. The incidence of postmastectomy skin flap necrosis and prognosis of the necrotic area after dextran-40 infusion was observed. RESULTS: Flap necrosis was observed in five (17.8%) patients. Hypertension and diabetes mellitus were found to be risk factors for the development of flap necrosis (P<0.05). Flap thickness and tension on the flaps were found to be related to flap necrosis. Six of seven patients with flap perfusion problems (ecchymosis or necrosis) underwent dextran-40 treatment and healed without graft replacement. CONCLUSIONS: Dextran-40 treatment did not affect development of flap necrosis. However, if necrosis had already developed, the necrotic area of the skin flaps improved with dextran-40 treatment.

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)0.001
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 score0.247
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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