Near-infrared (NIR) perfusion angiography in minimally invasive colorectal surgery
Bibliographic record
Abstract
BACKGROUND: Anastomotic leakage is a devastating complication of colorectal surgery. However, there is no technology indicative of in situ perfusion of a laparoscopic colorectal anastomosis. METHODS: We detail the use of near-infrared (NIR) laparoscopy (PinPoint System, NOVADAQ, Canada) in association with fluorophore [indocyanine green (ICG), 2.5 mg/ml] injection in 30 consecutive patients who underwent elective minimally invasive colorectal resection using the simultaneous appearance of the cecum or distal ileum as positive control. RESULTS: The median (range) age of the patients was 64 (40-81) years with a median (range) BMI of 26.7 (20-35.5) kg/m(2). Twenty-four patients had left-sided resections (including six low anterior resections) and six had right-sided resections. Of the total, 25 operations were cancer resections and five were for benign disease [either diverticular strictures (n = 3) or Crohn's disease (n = 2)]. A high-quality intraoperative ICG angiogram was achieved in 29/30 patients. After ICG injection, median (range) time to perfusion fluorescence was 35 (15-45) s. Median (range) added time for the technique was 5 (3-9) min. Anastomotic perfusion was documented as satisfactory in every successful case and encouraged avoidance of defunctioning stomas in three patients with low anastomoses. There were no postoperative anastomotic leaks. CONCLUSION: Perfusion angiography of colorectal anastomosis at the time of their laparoscopic construction is feasible and readily achievable with minimal added intraoperative time. Further work is required to determine optimum sensitivity and threshold levels for assessment of perfusion sufficiency, in particular with regard to anastomotic viability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".