Periumbilical vs transumbilical laparoscopic incision: A patients' satisfaction-centered randomised trial
Bibliographic record
Abstract
BACKGROUND: While studies suggested that transumbilical incisions (TUI) incur better postoperative cosmetic satisfaction scores (CSS) and shorter operative time (OT) than periumbilical incisions (PUI) during general surgery laparoscopic interventions, others did not. Concerns have been raised toward the potential negative impact of TUI on the incidence of surgical site infection (SSI) but this issue is under documented. METHODS: A controlled trial was conducted between August 2014 and August 2015 in our hospital. Individuals aged 18-70 undergoing a laparoscopic rectopexy, cholecystectomy, appendectomy or proctocolectomy were considered. Patients were randomized in two groups (PUI or TUI) following a 1:1 allocation ratio. Participants with a body mass index >40, with a history of abdominal surgery, undergoing co-operations, requesting a specific incision or converted to open surgery were excluded. RESULTS: Among the 56 randomized patients, 50 (27 PUI vs 23 PUI) produced analyzable data. There were no significant difference between the characteristics of both groups. CSS evolution (pre-op vs 1 month post-op), SSI incidence and OT were also comparable. Only 28% of participants valued the appearance of their umbilicus prior to intervention. Those who did had a significantly worst CSS evolution (OR -1.7; IC95-2.6/-0.72, p = 0.001). Higher preoperative CSS was also a predictor of postoperative CSS decline (OR -0.4; IC95-0.6/-0.2, p = 0.001). CONCLUSIONS: SUI and TUI were similar for all tested outcomes. Among the participants, the minority of patients who valued the appearance of their umbilicus and those with a high preoperative CSS were particularly prone to postoperative CSS decline.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".