953
Bibliographic record
Abstract
Introduction: Poor donor graft preservation, ischemic time and reperfusion injury contribute to early graft dysfunction (EGD) post liver transplantation. Studies have suggested that prolonged rocuronium-induced neuromuscular blockade could serve as a marker of EGD following liver transplantation. Metabolomics studies in liver transplantation have identified potential biomarkers to predict EGD. Liver transplantation is associated with abnormal clotting function and may need significant blood product transfusions. Though tranexamic acid (TXA) is frequently used to reduce blood transfusion, plasma TXA levels have not been modelled within this patient group. Solid phase micro extraction (SPME) is a new sampling and extraction technique that allows simultaneous measurement of multiple drugs and metabolites from bio-fluids and tissues. Absorption of compounds within the SPME fiber matrix quenches metabolic pathways capturing many more short-lived metabolites compared with previous analytical methods. Methods: Adults undergoing liver transplantation were administered a bolus followed by infusion of TXA during surgery as per previously described regimen. A 0.6mg/kg bolus of rocuronium was given prior to graft reperfusion and return of neuromuscular function was recorded with return of train-of-four (TOF). Concomitant measurement of plasma rocuronium, TXA and metabolomics profile was performed using SPME. Initial study included 9 cadaveric liver recipients. Results: A single testing method was developed for concomitant measurement of rocuronium, TXA and metabolomics using SPME. Concerning rocuronium, average time to return of TOF was 102 min (SD 46min). Delayed return to TOF (120 min) occurred in one patient. Plasma peak concentration was greatest and levels declined slowly. This corresponded with the highest MELD score of 26 and hepatorenal syndrome (creatinine 226). Global metabolomic profile was analyzed in 4 patients. There were significant changes in metabolites pre and post transplant. Profiles were similar in three patients with alcoholic and non-alcoholic cirrhosis. The one patient with cirrhosis due to hepatitis C displayed a trend towards a different metabolic profile. Metabolites displaying significant changes include histidine, bile acids, pyruvate and carbohydrates. Conclusions: We have demonstrated proof of concept in developing a single test that allows simultaneous measurement of multiple pharmacokinetic and metabolomic parameters clinically important in patients undergoing liver transplantation. This will allow medical management to be tailored to an individual patient intraoperatively and in the postoperative critical care setting.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.508 | 0.415 |
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".