Bibliographic record
Abstract
Historically, “marginal” kidneys from older deceased donors were not used for transplant. However, over the last decade the demand for kidneys to transplant has grown, and the waiting time for a kidney from a deceased donor has increased. This has resulted in a greater number of “expanded criteria” deceased donor kidneys used in transplantation. Patients on the transplant waiting list are often given a choice to either accept a kidney from an expanded criteria deceased donor when it becomes available, or extend their wait for a future kidney from a standard criteria deceased donor. For some patients “better a small fish than an empty dish,” meaning they would prefer to receive an expanded criteria kidney now than wait any longer for a transplant. A key question then becomes what type of recipient can safely receive an expanded criteria versus standard criteria deceased donor kidney? For example, do kidneys from older deceased donors do equally well in older and younger recipients? Or should we preferentially match older deceased donor kidneys with older recipients (and the corollary, younger standard criteria deceased donor kidneys with younger recipients)? In this issue of the Clinical Journal of the American Society of Nephrology, Ma and colleagues examined whether the use of standard criteria donors (SCD) and expanded criteria donors (ECD) kidneys had a different association with survival among older and younger first kidney transplant recipients (age ≥ or <60 years, respectively) (1). They used data from the Australian and New Zealand Dialysis and Transplant Registry from 1997 to 2009. They found that the risk of mortality was higher when comparing ECD to SCD among younger kidney transplant recipients, but no statistically significant association among older recipients was observed (all-cause mortality: adjusted HR 1.55 for younger recipients versus 1.11 for older recipients; death with graft function: adjusted HR: 1.72 for younger recipients versus 1.30 for older recipients). This effect modification was driven by excess risk of death from cardiovascular disease. Based on their findings, the authors suggest that donor function may play a less important role in influencing long-term patient outcomes in older recipients. An important consideration in the interpretation of these study findings is whether the ECD/SCD dichotomy is an appropriate surrogate for donor quality/function. Previous studies have shown that some ECD kidneys perform well, while some SCD kidneys perform poorly (2). This issue of effect modification by transplant recipient age was also examined in an analysis by Hernandez et al. using data from the United States United Network for Organ Sharing (3). In that study, deceased donor kidney recipients >60 years of age were sub-stratified by decade (i.e., 60–69 years, 70–79 years, and >79 years). They found that mortality risk was statistically increased for patients aged 50–59 years and 60–69 years who received low-quality deceased donor kidneys (as indicated by the Kidney Donor Profile Index [KDPI]), but not for recipients 70–79 years. Furthermore, a benefit in graft and recipient survival was observed for recipients of medium-quality kidneys who were aged 60–69 years, but not for recipients older than 69 years. As briefly discussed by the authors, several allocation systems around the world have formally implemented age-matching criteria into their algorithm. The Eurotransplant Senior Program has been well described (4). In other jurisdictions, additional criteria beyond recipient age are also considered. In Ontario, Canada, ECD kidneys are currently directed to patients who are ≥60 years old, patients with diabetes >50 years old, or recipients with significant co-morbidities (5). In 2014, the United States implemented “longevity matching” based on the KDPI and the estimated post-transplant survival, which takes into account recipient age, time on dialysis, the presence of diabetes, and whether the candidate had a previous solid organ transplant (6). Candidates with an estimated post-transplant survival in the top 20% are eligible for kidneys with a KDPI of <20%. The goal of the program is to maximize the number of life years lived with each donated organ, while minimizing life years lost following death with a functioning graft. Whether older recipients would ultimately benefit more from an ECD kidney versus remaining on the wait list for a longer period of time would require a survival benefit analysis with waitlisted versus transplanted candidates. Nevertheless, the study by Ma et al. is methodologically rigorous, and adds additional evidence to support the use of ECD kidneys in a specific population. This study can be used to guide practice to define explicit criteria for donor/recipient age-matching for kidney donor allocation in Australia and New Zealand. Based on current literature, higher-risk kidneys may be suitable for older recipients, but the criteria to define “older” and whether to include clinical criteria beyond recipient age, as is done in other parts of the world, requires further consideration. Moreover, even though the estimated effect on all-cause mortality and death with graft function from receiving an ECD was blunted, the elevated risk of graft loss even for older recipients was observed. Changing practice in light of these findings would also require acknowledgment of the impact on the local health care system. Recipients would require support following graft loss with either the return to dialysis or re-transplantation (now more likely to be sensitized). For now, this study can be used to guide the information presented to patients when counseling and educating them about transplantation. Finally, it may also impact local practices around which kidneys could be deemed suitable for transplant. In the face of the ever increasing demand for transplant, perhaps a small fish may yield a fulfilling dish. Disclosures None.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".