The Use of Indocyanine Green to Visualize the Thoracic Duct and Evaluate Gastric Conduit Perfusion in Esophagectomy
Bibliographic record
Abstract
Background: In this study, we investigate indocyanine green (ICG) dye visualization of the thoracic duct (TD) and conduit perfusion during esophagectomy to reduce anastomotic leak (AL) and chylothorax adverse events (AEs). Methods: Retrospective data of adult patients who underwent esophagectomy for esophageal carcinoma between July 2019 and 2022 were included (n = 105). ICG was delivered intravenously (2 mL, 2.5 mg/mL) to assess conduit perfusion into the small bowel mesentery, inguinal lymph nodes, or foot web spaces for TD visualization using fluorescence imaging. Incidence of TD injury, chylothorax, AL, and AEs were collected. Results: A total of 23 patients received ICG (ICG for TD and perfusion (n = 12) and perfusion only (n = 11)), while 82 patients were controls. TD was visualized in 6 of 12 patients who received ICG for TD. No intraoperative TD injuries or postoperative chylothoraces occurred in these patients. Non-ICG patients had 1 (1.22%) intraoperative TD injury and 10 (12.2%) postoperative chylothoraces (grade I–IIIb). While 10 non-ICG patients (12.2%) developed AL (grade I–IVb), only 2 (8.7%) ICG patients developed AL (grade IIIa). Conclusions: This study demonstrates the utility of ICG fluorescence in intraoperative TD and conduit perfusion assessment for limiting AEs. Standard incorporation of ICG in esophagectomy may help surgeons improve the quality of care in this patient population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".