Effect of low-dose tacrolimus with mycophenolate mofetil on renal function following liver transplantation
Bibliographic record
Abstract
AIM: To determine whether low-dose tacrolimus (TAC) combined with mycophenolate mofetil (MMF) is a safe approach to decrease the incidence of chronic kidney disease (CKD) in liver transplantation (LT) recipients. METHODS: We analyzed the medical records of 689 patients who underwent LT between March 1999 and December 2012 in a single Chinese center. Immunosuppression was initiated with a calcineurin inhibitor (TAC or CSA) and prednisone with or without MMF. CKD is defined by the glomerular filtration rate (GFR), estimated by an abbreviated Modification of Diet in Renal Disease formula, < 60 mL/min per 1.73 m(2) for at least 3 consecutive months after LT. Individuals with TAC trough concentrations ≤ 8 ng/mL at 3 mo after LT were defined as the low-dose group. The incidence of CKD within 5 years was compared between the TAC group and the CSA group, as well as between four subgroups (low-dose and high-dose TAC groups with or without MMF). RESULTS: No difference regarding the occurrence of pre-LT renal dysfunction or that of post-LT rejection was found between the TAC and CSA groups or between the four subgroups. With a definition of GFR < 60 mL/min per 1.73 m(2), the overall incidence of CKD was significantly higher in the CSA group than in the TAC group. The incidence of CKD in the low-dose TAC + MMF group (7.7%) was significantly lower than that observed in the low-dose TAC group (15.9%), high-dose TAC group (24.6%) and high-dose TAC + MMF group (18.5%). The cumulative 1-, 3- and 5-year incidence rates of CKD were 12.7%, 14.5% and 16.7%, respectively. The cumulative 5-year survival rates were 61.7% and 82.2% in patients with or without CKD, respectively. CONCLUSION: In LT patients, the choice of immunosuppressive therapy appears to affect renal function and patient 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".