Predictors and Prognostic Significance of Postoperative Complications for Patients with Intrahepatic Cholangiocarcinoma
Bibliographic record
Abstract
BACKGROUND: The prognostic impact of major postoperative complications (POCs) for intrahepatic cholangiocarcinoma (ICC) remains ill-defined. We sought to analyze the relationship between POCs and outcomes relative to lymph node metastases (LNM) and tumor burden score (TBS). METHODS: Patients who underwent resection of ICC between 1990-2020 were included from an international database. POCs were defined according to Clavien-Dindo classification ≥ 3. The prognostic impact of POCs was estimated relative to TBS categories (i.e., high and low) and lymph node status (i.e., N0 or N1). RESULTS: Among 553 patients who underwent curative-intent resection for ICC, 128 (23.1%) individuals experienced POCs. Low TBS/N0 patients who experienced POCs presented with a higher risk of recurrence and death (3-year cumulative recurrence rate; POCs: 74.8% vs. no POCs: 43.5%, p = 0.006; 5-year overall survival [OS], POCs 37.8% vs. no POCs 65.8%, p = 0.003), while POCs were not associated with worse outcomes among high TBS and/or N1 patients. The Cox regression analysis confirmed that POCs were significant predictors of poor outcomes in low TBS/N0 patients (OS, hazard ratio [HR] 2.91, 95%CI 1.45-5.82, p = 0.003; recurrence free survival [RFS], HR 2.42, 95%CI 1.28-4.56, p = 0.007). Among low TBS/N0 patients, POCs were associated with early recurrence (within 2 years) (Odds ratio [OR] 2.79 95%CI 1.13-6.93, p = 0.03) and extrahepatic recurrence (OR 3.13, 95%CI 1.14-8.54, p = 0.03), in contrast to patients with high TBS and/or nodal disease. CONCLUSIONS: POCs were independent, negative prognostic determinants for both OS and RFS among low TBS/N0 patients. Perioperative strategies that minimize the risk of POCs are critical to improving prognosis, especially among patients harboring favorable clinicopathologic features.
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 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 | 0.003 |
| 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 | 0.001 |
| 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".