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Record W2995085815 · doi:10.4293/jsls.2019.00050

Cosmesis and Patient Satisfaction Following Laparoscopic AdnexalSurgery

2019· article· en· W2995085815 on OpenAlexaboutno aff
Sang Wook Yi

Bibliographic record

VenueJSLS Journal of the Society of Laparoscopic & Robotic Surgeons · 2019
Typearticle
Languageen
FieldMedicine
TopicMinimally Invasive Surgical Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCosmesisMedicinePatient satisfactionSurgeryScarsLaparoscopyGeneral surgery

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Laparoendoscopic single site surgery (LESS), a minimally invasive procedure, is performed in many hospitals. Although its cosmetic superiority is widely touted, some authors have disputed this view. Here, we compare the surgical and long-term cosmetic outcomes of and patient satisfaction with postoperative wounds for LESS and over 2-port laparoscopy (OTPL), including 2-port laparoscopy (TPL) and standard laparoscopy (SL), after a 6-mo follow-up period. METHODS: A total of 125 patients who underwent adnexal surgery performed by the same surgeon at the same institution between March 2005 and May 2017 were included. The patients were divided into 2 groups: the LESS group and the OTPL group. The patients completed an evaluation using the Patient Scar Assessment Scale (PSAS, used to evaluate linear scars) and the Ultimate Question (UQ, used to determine overall patient satisfaction). We evaluated surgical scars using the Observer Scar Assessment Scale, which includes the Umbilical Scar Overall Shape Assessment Scale (USOSAS) and the Vancouver Scar Scale (VSS). RESULTS: There were no significant differences in the PSAS, UQ, USOSAS, and VSS results between the study groups. The USOSAS score was consistently correlated with VSS scores of 2, 3, and 4 and the total VSS score, indicating that the USOSAS score may be as effective as the VSS score. CONCLUSIONS: Because the long-term patient satisfaction with and cosmetic wound outcomes of LESS were not significantly different from those achieved by OTPL, surgeons should consider performing LESS after weighing the pros and cons with regard to the patient's condition.

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)0.000
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 score0.029
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.017
GPT teacher head0.267
Teacher spread0.249 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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