The Type of Arterial Anastomosis Influences Hepatic Hemodynamics and Overall Survival in Liver Graft Recipients
Bibliographic record
Abstract
AIM: Evaluation of the influence of arterial anastomoses on hepatic hemodynamics and overall survival in liver graft recipients using color Doppler ultrasound. METHOD: 224 patients recruited retrospectively were divided into five groups according to arterial anastomoses: (1) common hepatic (CHA)/gastro duodenal, (2) CHA/CHA, (3) aorta/celiac trunc, (4) aorta/aorta, (5) more than one anastomosis. We compared maximum portal [(P)Vmax], systolic [(A)Vmax] and end diastolic [(A)Vmin] arterial velocities, resistance indexes(RI), spleen and liver size between the groups. We analyzed further in a multivariate analysis the influence of time elapsed since orthotopic liver transplantation, age of recipient and donor on significant parameters as well as the overall survival of the patients between the groups. RESULTS: Significant differences were found for: (A) Vmax between groups 2/4 (p<0.007) and 2/5 (p<0.010), (A) Vmin between groups 1/3 (p<0.029) and 2/3 (p<0.015) and RI between the groups 1/3 (p<0.018) and 3/4 (p<0.006). (A)Vmax and RI were only dependent on the type of arterial anastomosis (p<0.008 and p<0.014). The overall survival of the patients between the groups was significantly different (p<0.047). CONCLUSION: In this study we report the natural course of the mean values of portal and arterial velocities in different arterial reconstructions for the first time. (A) Vmax of the hepatic artery is identified as the most promising candidate prognostic parameter for the assessment of hemodynamic alterations after liver transplantation originating in the type of arterial anastomosis performed. The group of patients with more than one anastomosis had the lowest arterial (A) Vmax and simultaneously the lowest overall survival.
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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 | 0.001 |
| 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".