MO398DETERIORATION OF RENAL OUTCOMES AND INCREASED MORTALITY RISK DUE TO ACUTE KIDNEY INJURY AFTER ORTHOTOPIC LIVER TRANSPLANTATION: SYSTEMATIC REVIEW AND META-ANALYSIS OF COHORT STUDIES
Bibliographic record
Abstract
Abstract Background and Aims Orthotopic liver transplantation (OLT) procedure is increased as incremental end-stage liver disease patients’ prevalence. Acute kidney injury (AKI) is one of most common post-OLT complications that is associated with poor renal outcomes and increased mortality risk although the results are still inconclusive. This study aims to measure the risk of deterioration of renal outcomes and mortality risk due to AKI incidence in post-OLT patients. Method We did comprehensive searching using predefined terms in online databases of Pubmed, EMBASE, ScienceDirect, and The Cochrane Library, to include all relevant studies from 2000-2020. We included all cohort studies that reported AKI incidence in post-OLT patients and accessed the risk of 3-month renal replacement therapy (RRT) need, 1-year chronic kidney disease (CKD) progression, and 1-year mortality rate. We used The Newcastle-Ottawa Scale for cohort study for accessing bias risk. We conducted analysis to pooled risk ratio (RR) with 95% confidence interval (CI) using random-effect heterogeneity test. Results We included 10 cohort studies met our inclusion criteria. The AKI incidence significantly both increases the need of RRT in post-OLT patients (pooled RR = 8.41. 95% CI = 2.82 to 25.09, p = 0.0001, I2 = 0%) then leads the CKD progression in one year (pooled RR = 6.76. 95% CI = 2.03 to 22.51, p = 0.002, I2 = 84%). The post-OLT patients who suffered from AKI has significant incremental 1-year mortality risk (pooled RR = 7.27. 95% CI = 4.34 to 12.18, p<0.00001, I2 = 5%). Conclusion The incidence of AKI in post-OLT patients significantly increase the deterioration of renal outcomes and mortality risks. However, further trials are needed to establish the causalities.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.033 |
| 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) | 0.004 | 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".