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Record W4400926227 · doi:10.1111/iwj.70004

Comparison of the wound healing and complications of zipper type closure adhesive tape and stapler for surgical wound suture: A randomized control, single‐centre, open‐label trial

2024· article· en· W4400926227 on OpenAlexaboutno aff
Gyoohwan Jung, Sang Hun Song, Bo Ri Kim, Jae Moon Shin, Chang‐Hun Huh, Sangchul Lee

Bibliographic record

VenueInternational Wound Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsnot available
FundersKorea Health Industry Development Institute
KeywordsMedicineSurgeryScarsFibrous jointWound healingVascularityRandomized controlled trialWound closureBarbed sutureSurgical wound

Abstract

fetched live from OpenAlex

Xkin closure is a newly developed medical suture device for lacerations and surgical wounds that can reduce scarring, pain and the risk of infection compared with conventional sutures or staplers. A randomized controlled study was performed to compare the wound healing effects and complications of Xkin closure with stapler closure. Fifty patients who underwent robot-assisted radical prostatectomy for prostate cancer were randomly assigned. Only the wound above the navel, which was extended to take out the prostate was targeted. The wound was examined at 2, 6 and 12 weeks after surgery, and the modified Vancouver Scar Scale (mVSS), scar height and side effects were assessed with a 3D skin analyser. Forty-six patients (23 Xkin, 23 Stapler) were analysed. The mVSS scores, vascularity and pliability were significantly lower in the Xkin group compared with the stapler group at the 12-week follow-up. No significant differences in the maximum peak and depth of the scars were detected between the two groups using 3D photographs at 12 weeks. Xkin is an effective wound closure method for improving scar outcomes. This method is expected to be widely used for surgical wounds and lacerations caused by trauma in daily life.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.069
GPT teacher head0.394
Teacher spread0.325 · 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 designRandomized trial
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
Published2024
Admission routes1
Has abstractyes

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