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Record W2410413862

GG-01 : What is the ideal skin closure method after single-port laparoscopic surgery?; A randomized clinical trial

2012· article· en· W2410413862 on OpenAlexaboutno aff
Doo Haeng Lee, Sue Yeon Park, Min Kyung Kim, Jee Ye Kim, Jung Hun Lee

Bibliographic record

Venue대한산부인과학회 학술발표논문집 · 2012
Typearticle
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurgeryFibrous jointPatient satisfactionRandomized controlled trialVisual analogue scaleCosmesisAnesthesia
DOInot available

Abstract

fetched live from OpenAlex

The objective of this study was to compare the cosmetic outcomes of umbilical scar and patient`s satisfaction according to closure methods in the women underwent single port laparoscopic surgery (SP-LS). This prospective randomized study was carried out in women who were scheduled to receive elective SP-LS for gynecologic disease. Participating patient were randomized to undergo skin closure of their umbilical incision with either only subcutaneous suture without subcuticular suture (case group) or subcutaneous suture with subcuticular suture (control group). Cosmetic outcome was evaluated at at postoperative 5 and 13 weeks. Objective and subjective scar analysis were performed using the Vancouver scar scale, the patient and observer scar assessment scale (POSAS), and a visual analog scale (VAS). Overall satisfaction with the surgery was evaluated with VAS. 162 women were included in this study, And 68 and 70 women enrolled in the case group and control group. There was no difference in the scar assessment and satisfaction with the surgery between both groups. Comparing with subcutaneous suture with subcuticular suture in umbilical wound closure of SP-LS, only subcutaneous suture without subcuticular suture offers the satisfactory cosmetic outcome and satisfaction with the surgery. However, large, randomized trials including other closure methods are needed to confirm these results.

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)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.383
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.065
GPT teacher head0.383
Teacher spread0.318 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venue대한산부인과학회 학술발표논문집Same topicSurgical Sutures and AdhesivesFrench-language works237,207