The Survival Benefit of Kidney Transplantation in Obese Patients
Bibliographic record
Abstract
Obese patients have a decreased risk of death on dialysis but an increased risk of death after transplantation, and may derive a lower survival benefit from transplantation. Using data from the United States between 1995 and 2007 and multivariate non-proportional hazards analyses we determined the relative risk of death in transplant recipients grouped by body mass index (BMI) compared to wait-listed candidates with the same BMI (n = 208 498). One year after transplantation the survival benefit of transplantation varied by BMI: Standard criteria donor transplantation was associated with a 48% reduction in the risk of death in patients with BMI ≥ 40 kg/m(2) but a ≥ 66% reduction in patients with BMI < 40 kg/m2. Living donor transplantation was associated with ≥ 66% reduction in the risk of death in all BMI groups. In sub-group analyses, transplantation from any donor source was associated with a survival benefit in obese patients ≥ 50 years, and diabetic patients, but a survival benefit was not demonstrated in Black patients with BMI ≥ 40 kg/m(2). Although most obese patients selected for transplantation derive a survival benefit, the benefit is lower when BMI is ≥ 40 kg/m(2), and uncertain in Black patients with BMI ≥ 40 kg/m(2).
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".