Does Anybody Really Know What (Warm Ischemia) Time It Is?
Bibliographic record
Abstract
Before the introduction of brain death criteria in 1968, nonheart-beating (NHB) donation was the standard of care in organ transplantation. In 1995, NHB donors were classified into 4 Maastricht categories and the term donation after circulatory death (DCD) gradually supplanted the NHB designation.1 In the early 2000s, the United Kingdom, Netherlands, and other European countries became leaders in the utilization of controlled (Maastricht category 3) DCD donor organs.1,2 In contrast, experience with DCD donors initially lagged in the United States. However, with the burgeoning disparity between organ supply and demand, DCD donor activity has increased dramatically in the past decade. Review of the Organ Procurement and Transplantation Network (OPTN) database reveals that from 2014 to 2019, the annual number of DCD donors in the US doubled, and from 2019 to 2023, the number of DCD donors doubled again.3 In 2023, DCD donors accounted for 36% of deceased donors in the United States, representing a 23% increase from 2022. However, nearly 4000 kidneys recovered from DCD donors were not transplanted in 2023, taxing resources and potentially missing opportunities for gained quality life-years in well-selected recipients.3 The process of DCD organ donation is associated with several unique aspects including withdrawal of life support, the agonal phase, requisite warm ischemia, a period of asystolic activity, declaration of death, the potential for ischemic preconditioning, and higher rates of organ surgical damage, primary nonfunction (PNF), and delayed graft function (DGF) in kidney transplantation. Although DGF has been associated with inferior outcomes in donation after brain death kidney transplantation, the influence of DGF in DCD donor kidney transplant outcomes is less clear as some studies have suggested no detrimental effect.4 Similar to the definition of DGF, the definition of DCD donor warm ischemia time (DWIT) is problematic, not universally recognized, and acceptable limits are debated and organ-specific. This inconsistency is highlighted by variable sets of hemodynamic parameters recommended by the British Transplantation Society, the American Society of Transplant Surgeons, and the OPTN in their delineation of DWIT.5,6 For example, functional DWIT (the period of actual hemodynamic instability) may be more clinically meaningful but again suffers from a lack of consensus and varying definitions (oxygen saturation <60%–80%, systolic blood pressure <60–80 mm Hg, either or both).7 To address this issue of Transplantation, Chumdermpadetsuk et al,8 from Beth Israel Deaconess Medical Center in Boston, MA, performed a retrospective analysis of the OPTN database that included 28 032 primary DCD donor kidney-alone transplants between January 2010 and December 2021. The association of DWIT, defined as the time from withdrawal of life support to in situ cross-clamp, with death-censored graft failure was evaluated by multivariable Cox proportional hazard regression using reference values of a Kidney Donor Risk Index (KDRI) ≤0.78 (which corresponds to a Kidney Donor Profile Index [KDPI] of ≤26%) and a median DWIT of 26 min. Although the definition of DWIT chosen for this analysis is quantifiable and makes sense for study purposes, it is not necessarily the definition that centers use for determining kidney acceptance. In addition, with the expanding use of extracorporeal membrane oxygenation or normothermic regional perfusion initiated at the time of declaration of circulatory death, determining an acceptable DWIT threshold for a given donor continues to evolve. Although the DCD donor is one of 10 variables that comprise the KDRI/KDPI, the true impact of DCD on graft longevity is uncertain, particularly since the KDRI/KDPI classification was formulated at a time when there were relatively few DCD donor kidney transplants performed in the United States. Moreover, the lack of granular data in the OPTN dataset raises questions regarding the interpretation of study findings. The major finding of this study is that DWIT is not universally associated with a higher odds of graft failure unless the donor is in the highest quartile of KDRI (>1.14, or KDPI >63%). Donors that are younger with less comorbidities may have a greater tolerance for ischemic injury and therefore an acceptable DWIT threshold for utilization becomes a spectrum and donor-specific. Machine perfusion was performed in 78.3% of cases and rates of PNF and DGF were 0.6% and 42%, respectively. Not surprisingly, nonutilization, PNF, and DGF rates increased with increasing KDRI/KDPI quartile. However, the median DWIT was 26 min (interquartile range, 21–34 min) so the number of cases with a “prolonged” DWIT (>45–60 min) was limited by standard practice and not specifically analyzed. Median cold ischemia time (CIT) was 18.9 h (interquartile range, 14.1–23.5 h) so again cases with “prolonged” CIT (>24 h) were limited and not specifically analyzed. Consequently, an algorithm for kidney utilization based on acceptable limits of DWIT and CIT according to donor KDRI/KDPI was not provided. In addition, the authors were not able to determine a relationship between DWIT and CIT. In our own experience, a CIT >24 h was associated with a 3-fold increase in the rate of PNF and early graft loss when using kidneys from either DCD or high KDPI donors (KDPI >85%).9 We have also reported on the use of DCD donor kidneys with longer CITs including 88 cases with CITs of 30–40 h and 38 with CITs ≥40 h.10 Not surprisingly, longer CITs were associated with higher rates of PNF, DGF, and early graft failure. However, comparable allograft life-years gained per patient were shown between groups as CIT increased, demonstrating the utility of transplanting these kidneys in selected circumstances. In general, we agree with the take-home message of this study that we as a community need to become more assertive with transplanting kidneys from DCD donors and not focus on DWIT thresholds as an exclusion criterion if other donor characteristics are favorable. Importantly, DCD donor kidneys from high KDRI/KDPI donors have acceptable outcomes if CITs are minimized and recipients are appropriately selected and informed. Finally, with the upsurge in new donation and preservation strategies and the potential to recondition and assess organs ex vivo, utilization of DCD donor kidneys should no longer carry the stigma of being DWIT-dependent suboptimal organs, which will undoubtedly help increase utilization while minimizing discard.
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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 | 0.004 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.018 | 0.009 |
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".