Population-based trend analysis of 2813 patients undergoing laparoscopic sigmoid resection
Bibliographic record
Abstract
BACKGROUND: The use of laparoscopic sigmoid resection for diverticular disease has become increasingly popular. The objective of this trend analysis was to assess whether clinical outcomes following laparoscopic sigmoid resection for diverticular disease have improved over the past 10 years. METHODS: The analysis was based on the prospective database of the Swiss Association of Laparoscopic and Thoracoscopic Surgery. Some 2813 patients undergoing elective laparoscopic sigmoid resection for diverticular disease from 1995 to 2006 were included. Unadjusted and risk-adjusted analyses were performed. RESULTS: Over time, there was a significant reduction in the conversion rate (from 27.3 to 8.6 per cent; P(trend) < 0.001), local postoperative complication rate (23.6 to 6.2 per cent; P(trend) = 0.004), general postoperative complication rate (14.6 to 4.9 per cent; P(trend) = 0.024) and reoperation rate (5.5 to 0.6 per cent; P(trend) = 0.015). Postoperative median length of hospital stay significantly decreased from 11 to 7 days (P(trend) < 0.001). CONCLUSION: This first trend analysis in the literature of clinical outcomes after laparoscopic sigmoid resection, based on almost 3000 patients, has provided compelling evidence that rates of postoperative complications, conversion and reoperation, and length of hospital stay have decreased significantly over the past 10 years.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".