Delayed Graft Function and the Risk for Death with a Functioning Graft
Bibliographic record
Abstract
Delayed graft function (DGF) associates with an increased risk for graft failure, but its link with death with graft function (DWGF) is unknown. We used the US Renal Data System to assemble a cohort of all first, adult, deceased-donor kidney transplant recipients from January 1, 1998, through December 31, 2004. In total, 11,542 (23%) of 50,246 recipients required at least one dialysis session in the first week after transplantation. Compared with patients without DGF, patients with DGF were significantly more likely to die with a functioning graft (relative hazard 1.83 [95% confidence interval 1.73 to 1.93] and 1.53 [95% CI 1.45 to 1.63] for unadjusted and fully adjusted models, respectively). The risk for DWGF was slightly higher among women with DGF than among men. There was no significant heterogeneity among other subgroups, and the results were robust to sensitivity analyses. Acute rejection within the first year attenuated the DGF-DWGF association. Cardiovascular and infectious deaths were slightly more prevalent in the DGF group, but the relative hazards of cause-specific death were similar between DWGF and deaths during total follow-up. In summary, DGF associates with an increased risk for DWGF; the mechanisms underlying the negative impact of DGF require further study.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".