30-Second Takeaway
- Prolonged dual hypothermic oxygenated perfusion safely shifts most liver transplants to daytime hours.
- Recipient and donor exome testing yields actionable diagnoses, favoring targeted genetic screening strategies.
- Dynamic, individualized eGFR thresholds improve prediction of kidney graft failure within two years.
- Kidney-after-lung safety-net policy reduces SLKT use and delisting while shortening kidney wait times.
- Conventional hemodynamic and warm ischemia metrics may misrepresent liver and donor injury, arguing for new physiologic and mitochondrial markers.
Week ending April 4, 2026
Machine perfusion, risk prediction, and peri-transplant management are reshaping organ utilization and allocation
Prolonged DHOPE enables daytime liver transplantation without worsening short-term outcomes
Routine implementation of prolonged dual hypothermic oxygenated machine perfusion (DHOPE-PRO) markedly increased daytime liver transplants at a single center. Daytime reperfusion rose from about half of cases pre-implementation to more than four-fifths afterward, with preservation times up to 31.4 hours. Despite a fivefold increase in perfusion duration, DHOPE-PRO was not associated with higher postoperative complication rates across graft types. One-year graft and patient survival were similar before and after DHOPE-PRO, suggesting extended preservation can safely facilitate daytime scheduling.
Exome sequencing clarifies CKD etiology and identifies at-risk kidney donors
Exome sequencing of 409 CKD-associated genes in 231 kidney transplant recipients identified pathogenic or likely pathogenic variants in 23%. Genetic results led to reclassification of CKD etiology in 37% of recipients with a genetic diagnosis, directly impacting counseling and family risk assessment. Among 46 prospective living kidney donors, 4% carried pathogenic variants, whereas 19% of 122 donors with adverse post-donation outcomes had such variants. These findings support targeted genetic testing of high-risk or phenotypically unclear donors rather than universal screening of all asymptomatic donors. Programs should consider incorporating focused exome testing into recipient workup and donor selection algorithms while monitoring equity implications.
Personalized eGFR thresholds improve prediction of kidney transplant failure
A dynamic model integrating serial eGFR with machine learning predicted kidney graft outcomes using routine pre- and early post-transplant data. Trained on 892 and validated in 847 recipients, the model achieved approximately 0.88 accuracy for first-year clinical events and 0.85 for second-year events. The approach derives an individualized eGFR threshold below which each patient’s risk of graft failure sharply increases. These personalized cutoffs could guide surveillance intensity, biopsy decisions, and immunosuppression adjustments in the first two post-transplant years.
Kidney-after-lung safety net decreases SLKT and delisting while improving early outcomes
UNOS analysis of 1,941 candidates showed that introduction of the kidney-after-lung (KALT) safety-net policy reduced simultaneous lung-kidney transplantation (SLKT). Post-policy, early KALT listings increased and kidney wait times shortened substantially compared with the pre-safety-net era. Listing during the safety-net era was associated with lower odds of delisting from the kidney waitlist due to deterioration or death (aOR 0.34). At one year, SLKT recipients had higher mortality after lung and kidney transplantation than early- and late-KALT recipients. These findings support staged kidney-after-lung strategies under the safety net, while acknowledging potential survivorship bias and need for prospective confirmation.
References
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Additional Reads
Optional additional studies from this edition.