Kidney Transplantation in the Elderly
Bibliographic record
Abstract
Transplantation offers superior life expectancy and quality of life compared with dialysis in young patients with end-stage renal failure. However, the initial risks of mortality and morbidity are high. This study used a decision analysis model to evaluate the costs and benefits of kidney transplantation versus continued dialysis for older patients with renal failure. A decision analytic model comparing cadaveric renal transplantation to continued hemodialysis treatment was developed. The base case considered a theoretical cohort of patients aged 65 yr without known comorbidity or contraindications to transplantation who would have to wait 2 yr for a cadaveric transplant. Separate models were constructed for patients with diabetes or cardiovascular disease and for patients receiving an organ after a variety of wait-list times. Probability, utility, and survival data were obtained from published reports and renal registries. For 65-yr-old patients, quality-adjusted life expectancy increased by 1.1 quality-adjusted life years (QALY) at an incremental cost of $67,778 per QALY. Assuming a 2-yr wait-listed time, transplantation remained economically attractive for 70-yr-old patients (incremental cost effectiveness [ICE], $79,359 per QALY) but was less economically attractive for those over 75 yr of age (ICE, $99,553) or for 70-yr-olds with either cardiovascular disease or diabetes (ICE, $126,751 and $161,090 per QALY, respectively). The analytic results were sensitive only to the time spent waiting for the graft. The cost-effectiveness reduced such that the costs associated with one QALY were in excess of $100,000/yr when the probability of a complication was > or = 50% per 3-mo cycle and when the utility of transplantation fell below 0.62. If available within a timely period, transplantation may offer substantial clinical benefits to older patients at a reasonable financial cost. Prolonged waiting times dramatically decrease the clinical benefits and economic attractiveness of transplantation, suggesting that living donor transplantation may be of particular benefit in this population.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".