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Abstract: Effect of Absorbable Skin Stapler in Autologous Breast Reconstruction Patients: Approach Through Economic and Cosmesis

2016· article· en· W2523077117 on OpenAlexaboutno aff
Min ji Kim, Bo Young Park, Seung Eun Hong, So Ra Kang

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2016
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCosmesisMedicineSurgeryFibrous jointBreast reconstructionWound closureClosure (psychology)Wound healingBreast cancerCancer

Abstract

fetched live from OpenAlex

INTRODUCTION: In abdominal based autologous breast reconstructions, abdominal closure is a time-consuming procedure. The time cost of the skin closure process is difficult to reduce. However, skin suture using absorbable subcuticular staples, which allow for increased rapid closure can provide equivalent healing capacity in various situations of incision closure.1 The purpose of this study was to evaluate the economic efficacy and cosmetic satisfaction of wound closure with an absorbable subcuticular stapling system, and compare these results obtained with conventional dermal sutures in breast reconstruction patients. MATERIALS AND METHODS: The A total 94 patients undergoing autologous breast reconstruction were included the study. Of these, INSORB® was used in 64 patients and we compared 30 patient’s clinical data as a conventional suture group. We provided a controlled surgical environment for evaluate effect of choice of closure material. For exclude the possibility of surgical procedure variety, we divide into free flap and pedicle flap groups and each group has stapler and control groups. For analysis of cost-effectivenss we applied endotracheal anesthesia expenses, and objective assessment by resident and questionnaire by patient was made for scar evaluation.2 RESULTS: Using paired t test, statistical analysis was made. An pedicle flap group represents 387.2hrs (stapler), 480.5hrs(control) (t-value -2.031, p-value 0.043) and free flap group represents 442.0hrs(stapler), 514.8hrs(control) (t-value -2.037, p-value 0.025) as average anesthesia time. A gap of time reduction is 93.3hrs in pedicle flap group and 72.8hrs in free flap group for absorbable stapler used groups. These reduce time of total general anesthesia in absorbable groups, which is equivalent to a 135.67$ in pedicle group and 128.35$ in free flap group. In regards to the expenses of INSORB®, only the group that used 1 stapler is significant. The complication rate, duration of healing period and the patient’s satisfaction of the scar did not differ between each group. CONCLUSION: An absorbable staples are effective materials that allow cost-effective closure when used appropriately. While dealing with cutting-edge technology,3,4 we need to consider patients benefits that would get overwhelming his expenses. In that point, only 1 stapler used in abdominal closure is effective not to be two used. And also we could find this is no way inferior to conventional suture. The availability of time reduction with equivalent cosmetic results is appealing aspects for applying reconstruction operation. DISCLOSURE/FINANCIAL SUPPORT:Nothing to declare. REFERENCES: 1. Gatt D, Quick CR, Owen-Smith MS. Staples for wound closure: a controlled trial. Annals of the Royal College of Surgeons of England 1985;67:318–20. 2. Pauline T. Truong, Standardized Assessment of Breast Cancer Surgical Scars Integrating the Vancouver Scar Scale, Short-Form McGill Pain Questionnaire and Patients’ Perspectives, PLASTIC AND RECONSTRUCTIVE SURGERY, 2005; 116:1291 3. Bastian PJ, Haferkamp A, Albers P, Müller SC. A new form of noninvasive wound closure with a surgical zipper. J Urol 2003;169:1785–6. 4. Luck RP, Flood R, Eyal D, Saludades J, Hayes C, Gaughan J. Cosmetic outcomes of absorbable versus nonabsorbable sutures in pediatric facial lacerations. Pediatr Emerg Care 2008;24:137–42.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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