The effect of preoperative jaundice in the surgical management of gallbladder carcinoma: An updated meta‐analysis
Bibliographic record
Abstract
BACKGROUND: An updated meta-analysis was performed on the significance of preoperative jaundice in the surgical management of gallbladder carcinoma (GBC). METHODS: A thorough database searching was performed in PubMed, EMBASE, and the Cochrane library for comparative studies between jaundiced and non-jaundiced GBC patients. RevMan5.3 and Stata 13.0 software were used for statistical analysis. A total of nine measured outcomes were identified: resectability, R0 resection rate, concurrent bile duct resection, major hepatectomy, vital vascular reconstruction, combined adjacent organ resections, postoperative morbidities, mortalities, and overall survival (OS). RESULTS: A total of eight studies were finally included. Newcastle- Ottawa Quality Assessment Scale was used for evaluating the quality of all included studies and the details were recorded in Table S1. Our pooled results revealed that preoperative jaundice was associated with a significantly lower resectability (p < 0.00001), a significantly lower R0 resection rate (p < 0.00001), a significantly higher concurrent bile duct resection rate (p < 0.00001), major hepatectomy rate (≥3 segments) (p < 0.00001), and vital vascular reconstruction rate (portal vein or hepatic artery) (p < 0.00001). Moreover, jaundiced patients experienced more postoperative morbidities (p < 0.00001), mortalities (p < 0.0001), and worse OS (p < 0.00001). However, jaundice was not related to combined adjacent organ resections (p = 0.58). CONCLUSION: Preoperative jaundice in GBC patients seems to be contraindicated to curative resection and the optimal therapeutic strategies should be identified via multidisciplinary team rather than surgery alone. Candidates for curative surgery should be highly selected and experienced centers are preferred. More significant well-designed studies are required for further exploration.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.046 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".