Early Kidney Dysfunction After Liver Transplantation Is Associated With Reduced Graft and Patient Survival
Bibliographic record
Abstract
Introduction: In this study, we aimed at investigating the frequencies of acute renal dysfunction (ARD) and chronic kidney disease (CKD) post-liver transplant (LT), the risk factors associated with renal dysfunction post-LT, and to determine the clinical impact of renal dysfunction with regards to both graft and patient survival after LT. Methods: We analyzed 535 patients with cirrhosis who received a liver transplant over the period of 1989 to 2010. Estimated glomerular filtration rate (eGFR) was determined using the 4 variable MDRD formula, ARD was defined as eGFR >90 ml/min prior to transplant, followed by eGFR <60 ml/min at 3 months post-LT, and CKD was defined as eGFR <60 ml/min after LT, evidence of intrinsic renal disease, or need for renal replacement therapy. Results: Three hundred fifty-nine were males (67%), and the mean age at LT was 52±10 years. Cirrhosis etiology was HCV cirrhosis (35%), alcohol cirrhosis (33%), autoimmune liver disease (25%), NASH (2%), and HBV (6%). Diabetes was present in 180 (34%), and hypertension in 244 patients (46%) prior to LT. Mean serum creatinine level was 111±80 μmol/L, and 186 patients (35%) had a diagnosis of CKD prior to LT. ARD was documented in 34 patients (6%) after LT, and a new diagnosis of CKD post-LT was made in 88 patients (16%). Risk factors associated with development of ARD were age >60 years (14 vs. 6%; p=0.01) and male gender (12 vs. 5%; p=0.01). Risk factors for development of CKD post-LT were diabetes (23 vs. 13%; p=0.003) and hypertension (22 vs. 12%; p=0.001). Graft survival (133±13 vs. 168 ±11 months; p=0.03) and patient survival were significantly reduced when eGFR was <60 ml/min at 3 months (133±13 vs. 185±12 months; p=0.006; Figure 1). Hazard ratio for mortality was 1.6 (95% confidence interval [CI] 1.2-2.3; p=0.006) for those patients with eGFR <60 ml/min at 3 months.Figure 1Conclusion: ARD and CKD are frequent complications after LT. Older age and male gender are associated with a higher risk for ARD, whereas diabetes, hypertension, and early reduction in the eGFR are associated with higher risk of CKD after. Recognition of early kidney dysfunction after LT is important in an effort to establish strategies to improve graft and patient survival after LT.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".