Surgical Management of Intrahepatic Cholangiocarcinoma in Patients with Cirrhosis: Impact of Lymphadenectomy on Peri‐Operative Outcomes
Bibliographic record
Abstract
BACKGROUND: The consequences of lymphadenectomy (LND) on cirrhotic patients undergoing hepatectomy for intrahepatic cholangiocarcinoma (ICC) have not been investigated. We sought to analyze the impact of LND on morbidity among patients undergoing resection for ICC. METHODS: A total of 1005 patients who underwent hepatectomy for ICC at one of the 14 participating institutions between 1990 and 2015 were identified. A propensity score match analysis was performed to reduce confounding biases between cirrhosis and non-cirrhosis groups. RESULTS: Cirrhosis was diagnosed in 118 (11.7%) patients. Among non-cirrhotic patients, 63% underwent major liver resection versus only 20% among patients with cirrhosis (p < 0.001). LND was also less common among cirrhotic versus non-cirrhotic patients (19 vs. 50%, p < 0.001). The incidence of complications was 41 and 30% among patients who did not and did have cirrhosis, respectively (p = 0.022). The propensity-matched cohort included 150 patients. The incidence of complications was 71% among patients who underwent lymphadenectomy versus 23% among patients who did not undergo lymphadenectomy (OR 8.39) (p < 0.001). In the propensity-matched analysis, the median HLN was comparable among patients independent of cirrhosis status (median HLN: non-cirrhosis, 2.5 vs. cirrhosis, 2) (p = 0.95). While lymphadenectomy was associated with a higher risk of infections (non-cirrhosis, 0% vs. cirrhosis, 21%, p < 0.001) among patients with cirrhosis, infections were not associated with lymphadenectomy among non-cirrhotic patients (p = 0.19). CONCLUSION: Lymphadenectomy was associated with an increased risk of complications among patients with cirrhosis undergoing surgery for ICC. The benefit of lymphadenectomy in cirrhotic patients should be considered in light of the higher risk of postoperative complications compared with non-cirrhotic patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".