Geographic Variation in Cold Ischemia Time: Kidney vs. Liver Transplantation in the United States, 2003-2011

Spatial inequalities and non-linear association of continuous variables with mortality risk of liver transplantation in Iran: a retrospective cohort study

Liver transplantation is the second most common solid organ transplant and the best option for liver failure. Of course, patient survival after transplantation depends on many risk factors. The aim of this study was to investigate the spatial and non-linear effects of continuous risk factors on patient survival after liver transplantation. This retrospective cohort study (n = 3148) used data on liver transplantation in Iran (2004-2019). A generalized additive model with spatial effects and non-linear effects of age and Model for End-Stage Liver Disease (MELD) score variables by penalized spline was used. The majority of patients were male (63.3%), with a mean (SD) age of 42.65 (13.31) and a mean (SD) MELD score of 24.43 (6.72). The 1, 5, and 10-year survival rates were 88.2%, 84.6%, and 82.5% respectively. The non-linear effect showed a steeper slope of the age effect on the hazard of death after the age of 50 (p < 0.05), and the MELD score had a direct but non-linear relationship with the hazard of death (p < 0.05). In the spatial pattern, the provinces with a greater distance from the transplant center had significantly fewer old patients than other provinces. Also, more distant provinces with an older transplant age had higher post-transplant mortality rates. Our study showed that it is better to take age and MELD score into account in postoperative care. The spatial pattern of mortality risk reflects inequalities in access to transplantation and public health services after transplantation.

Do Organizational Characteristics of Lung Procurement Operations Matter: The Association Between Transplant Center Centrality and Volume With Total Ischemic Time

BACKGROUND

To understand the association of 2 organizational characteristics of transplant center (TXC), volume and closeness centrality, with total ischemic time for deceased donor lung transplants in conjunction with the removal of donation service area (DSA) lung allocation policy. The organization of donor procurements has received increased attention since DSA was removed from allocation policy. Consistent with network theories of organization, organizational characteristics of a TXC could affect procurement efficiency, as volume and closeness centrality (measuring how connected a TXC is within the Organ Procurement and Transplantation Network) could be associated with total ischemic time. These associations could have changed because of the removal of DSA from allocation policy.

METHODS

We conducted a retrospective, pooled cross-sectional study of total ischemic time for nonperfused deceased donor lung transplants (n = 9281) between 2015 and 2019, using within-between regression.

RESULTS

Higher volume TXCs exhibited lower total ischemic times after the removal of DSA from lung allocation policy (P = 0.011); however, all TXCs that had increased volumes, after the removal of DSA from lung allocation policy, exhibited higher levels of total ischemic time (P ≤ 0.001). Before the removal of DSA, TXCs that had increased volumes exhibited lower levels of ischemic time (P ≤ 0.001). Both within and between closeness centrality exhibited u-shaped associations with total ischemic time (P = 0.012; P = 0.006) and the effect of closeness centrality on total ischemic time was different after DSA removal (P < 0.001).

CONCLUSIONS

Organizational characteristics were associated with the efficiency of deceased organ procurements. The effects on total ischemic time were dependent on whether DSA was used for lung allocation.

Association of Transit Time With Cold Ischemic Time in Kidney Transplantation

This cross-sectional study examines the association between transit time and cold ischemic time for adult, deceased kidney transplant donors.

A Simulation-Based Optimization Model to Study the Impact of Multiple-Region Listing and Information Sharing on Kidney Transplant Outcomes

More than 8000 patients on the waiting list for kidney transplantation die or become ineligible to receive transplants due to health deterioration. At the same time, more than 4000 recovered kidneys from deceased donors are discarded each year in the United States. This paper develops a simulation-based optimization model that considers several crucial factors for a kidney transplantation to improve kidney utilization. Unlike most proposed models, the presented optimization model incorporates details of the offering process, the deterioration of patient health and kidney quality over time, the correlation between patients’ health and acceptance decisions, and the probability of kidney acceptance. We estimate model parameters using data obtained from the United Network of Organ Sharing (UNOS) and the Scientific Registry of Transplant Recipients (SRTR). Using these parameters, we illustrate the power of the simulation-based optimization model using two related applications. The former explores the effects of encouraging patients to pursue multiple-region waitlisting on post-transplant outcomes. Here, a simulation-based optimization model lets the patient select the best regions to be waitlisted in, given their demand-to-supply ratios. The second application focuses on a system-level aspect of transplantation, namely the contribution of information sharing on improving kidney discard rates and social welfare. We investigate the effects of using modern information technology to accelerate finding a matching patient to an available donor organ on waitlist mortality, kidney discard, and transplant rates. We show that modern information technology support currently developed by the United Network for Organ Sharing (UNOS) is essential and can significantly improve kidney utilization.

Successful Implementation of Unmanned Aircraft Use for Delivery of a Human Organ for Transplantation

OBJECTIVE

To understand and overcome the challenges associated with moving life-urgent payloads using unmanned aircraft.

BACKGROUND DATA

Organ transportation has not been substantially innovated in the last 60 years. Unmanned aircraft systems (UAS; ie, drones) have the potential to reduce system inefficiencies and improve access to transplantation. We sought to determine if UASs could successfully be integrated into the current system of organ delivery.

METHODS

A multi-disciplinary team was convened to design and build an unmanned aircraft to autonomously carry a human organ. A kidney transplant recipient was enrolled to receive a drone-shipped kidney.

RESULTS

A uniquely designed organ drone was built. The aircraft was flown 44 times (total of 7.38 hours). Three experimental missions were then flown in Baltimore City over 2.8 miles. For mission #1, no payload was carried. In mission #2, a payload of ice, saline, and blood tubes (3.8 kg, 8.4 lbs) was flown. In mission #3, a human kidney for transplant (4.4 kg, 9.7 lbs) was successfully flown by a UAS. The organ was transplanted into a 44-year-old female with a history of hypertensive nephrosclerosis and anuria on dialysis for 8 years. Between postoperative days (POD) 1 and 4, urine increased from 1.0 L to 3.6 L. Creatinine decreased starting on POD 3, to an inpatient nadir of 6.9 mg/dL. The patient was discharged on POD 4.

CONCLUSIONS

Here, we completed the first successful delivery of a human organ using unmanned aircraft. This study brought together multidisciplinary resources to develop, build, and test the first organ drone system, through which we performed the first transplant of a drone transported kidney. These innovations could inform not just transplantation, but other areas of medicine requiring life-saving payload delivery as well.

The impact of kidney donor profile index on delayed graft function and transplant outcomes: A single-center analysis

INTRODUCTION

Renal transplant outcomes result from a combination of factors. Traditionally, donor factors were summarized by classifying kidneys as extended criteria or standard criteria. In 2014, the nomenclature changed to describe donor factors with the kidney donor profile index (KDPI). We aim to evaluate the relationship between KDPI and delayed graft function (DGF), and the impact KDPI on transplant outcomes for both donor after cardiac death (DCD) and donor after brain death (DBD).

METHODS

An IRB-approved single-center retrospective chart review was performed from January 1999 to July 2013. The patients were divided into six groups: DBD KDPI ≤60, DBD KPDI 61-84, DBD KDPI ≥85, DCD KDPI ≤60, DCD KPDI 61-84, and DCD KDPI ≥85. Rates of DGF, patient survival, and graft survival were examined among groups.

RESULTS

A total of 2161 kidney transplants were included. DGF rates increased, and graft and patient survival decreased with increasing KDPI (P < .001). DCD kidneys had higher DGF rates than their DBD counterparts (P < .001). In DCD kidneys, a higher KDPI score did not significantly affect the DGF rates (P > .302). There was no significant difference in graft or patient survival in all-comers when comparing DCD and DBD kidneys with equivalent KDPIs (P > .317). Patients with DGF across all categories demonstrated worse graft half-lives.

CONCLUSION

The KDPI system is an accurate predictor of donor contributions to transplant outcomes. Recipients of DBD kidneys experience an increase in the rate of DGF as their KDPI increases. DCD kidneys have higher DGF rates than their DBD counterparts with similar KDPIs. Patients with documented post-transplant DGF had between 3- and 5-year shorter graft half-lives when compared to recipients that did not experience DGF. Initiatives to reduce the rate of DGF could provide a significant impact on graft survival and result in a reduction in the number of patients requiring retransplant.

An Initial Investigation of Unmanned Aircraft Systems (UAS) and Real-Time Organ Status Measurement for Transporting Human Organs

Organ transportation has yet to be substantially innovated. If organs could be moved by drone, instead of ill-timed commercial aircraft or expensive charter flights, lifesaving organs could be transplanted more quickly. A modified, six-rotor UAS was used to model situations relevant to organ transportation. To monitor the organ, we developed novel technologies that provided the real-time organ status using a wireless biosensor combined with an organ global positioning system. Fourteen drone organ missions were performed. Temperatures remained stable and low (2.5 °C). Pressure changes (0.37-0.86 kPa) correlated with increased altitude. Drone travel was associated with less vibration (<0.5 G) than was observed with fixed-wing flight (>2.0 G). Peak velocity was 67.6 km/h (42 m/h). Biopsies of the kidney taken prior to and after organ shipment revealed no damage resulting from drone travel. The longest flight was 3.0 miles, modeling an organ flight between two inner city hospitals. Organ transportation may be an ideal use-case for drones. With the development of faster, larger drones, long-distance drone organ shipment may result in substantially reduced cold ischemia times, subsequently improved organ quality, and thousands of lives saved.