Prolonged lymphopenia following anti-thymocyte globulin induction is associated with decreased long-term graft survival in liver transplant recipients.
Bibliographic record
Abstract
BACKGROUND AND AIM: Induction with anti-thymocyte globulin (ATG) during solid organ transplantation is associated with an improved clinical course and leads to prolonged lymphopenia. This study aims to investigate whether prolonged lymphopenia, caused by ATG induction, has an impact on patient and graft survival following liver and kidney transplantation. PATIENTS AND METHODS: This was a single-center, retrospective study. A total of 292 liver and 417 kidney transplants were performed with ATG induction (6 mg/kgr, divided into four doses), and the transplant recipients were followed for at least three months. The average lymphocyte count for the first 30 days after the operation was calculated, and the cut-off value for defining lymphopenia was arbitrarily set to ≤ 500 cells/mm(3). RESULTS: There were 210 liver transplant recipients (71.9%) who achieved prolonged lymphopenia, whereas the remaining 82 recipients (28.1%) did not. The mean survival time of these patient groups was 10.27 and 12.71 years, respectively (p = 0.1217), and the mean graft survival time was 8.98 and 12.25 years, respectively (p = 0.0147). Of the kidney transplant patients, 330 (79.1%) recipients achieved prolonged lymphopenia, whereas the remaining 87 (20.9%) did not. The mean survival time of these patient groups was 13.94 and 14.59 years, respectively, (p = 0.4490), and the mean graft survival time was 11.84 and 11.54 years, respectively (p = 0.7410). CONCLUSION: The efficacy and safety of ATG induction partially depend on decreased total lymphocyte counts. Following ATG induction in liver transplant recipients, a reasonable average lymphocyte count during the first postoperative month would be above 500 cells/mm(3).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".