Short-term clinical outcomes of open, laparoscopic, and robotic-assisted rectal resections: a multicenter real-world evidence study from Indian collaborative group on rectal resections (ICGRR)
Why this work is in the frame
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Bibliographic record
Abstract
This multi-centric real-world study was carried out to assess the perioperative and histopathological clinical outcomes of rectal resections employing open, laparoscopic, and robotic-assisted techniques. A retrospective chart review was undertaken for patients who underwent rectal resections for Stages I, II, and III rectal cancer (RC) between April 2012 and August 2023. All surgical procedures were performed with the principles of total mesorectal excision (TME) or partial mesorectal excision (for tumors located higher in the rectum). The study analyzed data from 829 patients of which 314 were in the robotic-assisted group (RAS), 206 in the laparoscopic surgery group (LG), and 309 in the open-surgery group (OG). The TNM staging and location of RC were evenly distributed across the three groups. The RAS group had a significantly lower length of hospital stay than LG and OG. Compared to LG and OG, the RAS group had less blood loss and postoperative complications, but significantly longer mean operating room time. The conversion rate of the RAS group was significantly lower than that of the LG group (p = 0.03). In comparison to the OG and LG groups, the RAS group had significantly lower (p < 0.05) rates of positive circumferential resection margin (CRM). Adjuvant treatment was administered in the RAS group significantly earlier (median, 24.5 days, IQR 18-37) compared to the LG (median, 31 days, IQR 23-41) and OG (median, 32.5 days, IQR 27-42). This largest multi‑centric study by the ICRR group has validated the value of a relatively newer technology like RAS in real-world Indian settings for rectal resections.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it