Effects of intraoperative hemodynamic management on postoperative acute kidney injury in liver transplantation: An observational cohort study
Bibliographic record
Abstract
BACKGROUND: Intraoperative restrictive fluid management strategies might improve postoperative outcomes in liver transplantation. Effects of vasopressors within any hemodynamic management strategy are unclear. METHODS: We conducted an observational cohort study on adult liver transplant recipients between July 2008 and December 2017. We measured the effect of vasopressors infused at admission in the intensive care unit (ICU) and total intraoperative fluid balance. Our primary outcome was 48-hour acute kidney injury (AKI) and our secondary outcomes were 7-day AKI, need for postoperative renal replacement therapy (RRT), time to extubation in the ICU, time to ICU discharge and survival up to 1 year. We fitted models adjusted for confounders using generalized estimating equations or survival models using robust standard errors. We reported results with 95% confidence intervals. RESULTS: We included 532 patients. Vasopressors use was not associated with 48-hour or 7-day AKI but modified the effects of fluid balance on RRT and mortality. A higher fluid balance was associated with a higher need for RRT (OR = 1.52 [1.15, 2.01], p<0.001 for interaction) and lower survival (HR = 1.71 [1.26, 2.34], p<0.01 for interaction) only among patients without vasopressors. In patients with vasopressors, higher doses of vasopressors were associated with a higher mortality (HR = 1.29 [1.13, 1.49] per 10 μg/min of norepinephrine). CONCLUSION: The presence of any vasopressor at the end of surgery was not associated with AKI or RRT. The use of vasopressors might modify the harmful association between fluid balance and other postoperative outcomes. The liberal use of vasopressors to implement a restrictive fluid management strategy deserves further investigation.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".