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Stehlik, Josef

https://orcid.org/0000-0002-7362-0513

Mayo Clinic

University of Utah

Citations 3

Clinical Outcomes With Normothermic Pulsatile Organ Perfusion in Heart Transplantation: A Report From the OCS Heart Perfusion Registry
Stehlik, Josef , Farr, Maryjane , Mehra, Mandeep R. , Schroder, Jacob N. , D’Alessandro, David A. , Pal, Jay D. , Villavicencio, Mauricio A. , Gruber, Peter J. , Couper, Gregory S., Shudo, Yasuhiro , Patel, Parag C. , Daneshmand, Mani A. , Klein, Liviu , Shah, Ashish S. , Skipper, Eric, Esmailian, F., Goldstein, Daniel J. , Ohira, Suguru , Kaczorowski, David, Takeda, Koji , Malyala, R., Haft, Jonathan W., Sun, Benjamin , Kilic, Arman , Anyanwu, Anelechi, Williams, Celeste T. , Kai, Masashi , Sulemanjee, Nasir , Funamoto, Masaki , Salerno, Christopher T. , Durham, Lucian A. , Shaffer, Andrew , Zhou, Xiang , Milano, Carmelo A. , Farr, Maryjane A , Goldstein, Daniel , Lozonschi, Lucian , Takeda, Koji , Meyer, Dan M , Sun, Benjamin C , Pretorius, Victor , Pham, Duc T , Kai, Masashi , Sulemanjee, Nasir Z , Funamoto, Masaki , Durham, Lucian A , Shaffer, Andrew , Zafar, Farhan , Pinney, Sean P , Milano, Carmelo A , Mehra, Mandeep R , Lozonschi, Lucian , Pretorius, Victor , Itoh, Akinobu , Ikonomidis, John S.

Circulation | March 7, 2025 | Volume: 151 | Issue: 13 | Pages: 896-909

10.1161/circulationaha.124.071743 Get It

BACKGROUND: A preservation system, the Organ Care System (OCS; TransMedics) uses normothermic pulsatile perfusion during organ transport for heart transplantation. This system has demonstrated favorable outcomes in hearts recovered from extended-criteria donors after brain death (DBD) and donors after circulatory death (DCD). METHODS: The OCS Heart Perfusion Registry collects data on US heart transplantations using the OCS, static cold storage (SCS), or thoracoabdominal normothermic regional perfusion (NRP) and donor hearts recovered from DBD or DCD donors. We analyzed donor and recipient characteristics and posttransplantation outcomes in patients transplanted with OCS donor hearts (either DBD or DCD) compared with SCS hearts, and with OCS hearts from DCD donors compared with those recovered with NRP followed by SCS. Propensity score matching was used in survival analyses to adjust for differences among recipient characteristics. RESULTS: Between 2021 and 2023, 3225 consecutive heart transplantations enrolled from 56 centers were analyzed in the Heart Perfusion Registry. The OCS was used in 854 of 3225 heart transplantations (26.4%), among which 340 (39.8%) were DBD and 514 (60.2%) were DCD donors, whereas 2174 DBD donors were recovered with SCS and another 197 DCD donors with NRP techniques. The OCS-DBD group experienced a greater number of organ offer refusals before final acceptance (13 versus 6; Wilcoxon rank sum, P <0.001) and a longer transport distance (667 miles versus 232 miles; Wilcoxon rank sum, P <0.001) compared with SCS-DBD. Survival at 12 months was similar between the 2 groups (89.9% for OCS-DBD versus 90.6% for SCS-DBD; marginal Cox model, P =0.54). Among the OCS-DCD and SCS-DBD groups, survival at 12 months was also similar (91.0% versus 92.5%, respectively; marginal Cox model, P =0.32). The OCS-DCD and NRP-DCD groups demonstrated similar survival (91.0% versus 91.7%, respectively; log rank, P =0.63), although the transport distance was longer in OCS-DCD compared with DCD with NRP followed by SCS (400 miles versus 223 miles; Wilcoxon rank sum, P <0.001). By 2023, 90% of all OCS donor management and recovery was performed with dedicated organ recovery teams. CONCLUSIONS: We demonstrate that real-world implementation of the OCS for DBD donors (using predominantly a dedicated recovery team) is associated with expanded donor criteria, longer transport distance, and excellent posttransplantation outcomes. In OCS-DCD donors, outcomes parallel those of donors recovered with NRP-DCD and compare favorably with DBD donor organs.
Prediction model for cardiac allograft vasculopathy: Comparison of three multivariable methods
Kransdorf, E. , Loghmanpour, Natasha A., Kanwar, Manreet , Temkit, M’hamed , Stehlik, Josef , Kransdorf, Evan P , Temkit, M'hamed H, Kanwar, Manreet K

Clinical Transplantation | February 9, 2017 | Volume: 31 | Issue: 4 | Pages: No page available

10.1111/ctr.12925 Get It

AbstractBackgroundCardiac allograft vasculopathy (CAV) remains an important cause of graft failure after heart transplantation (HT). Although many risk factors for CAV have been identified, there are no clinical prediction models that enable clinicians to determine each recipient's risk of CAV.MethodsWe studied a cohort of 14 328 heart transplant recipients whose data were reported to the International Society for Heart and Lung Transplantation Registry between 2000 and 2010. The cohort was divided into training (75%) and test (25%) sets. Multivariable modeling was performed in the test set using variables available at the time of heart transplant using three methods: (i) stepwise Cox proportional hazard, (ii) regularized Cox proportional hazard, and (iii) Bayesian network.ResultsCardiac allograft vasculopathy developed in 4259 recipients (29.7%) at a median time of 3.0 years after HT. The regularized Cox proportional hazard model yielded the optimal performance and was also the most parsimonious. We deployed this model as an Internet‐based risk calculator application.ConclusionsWe have developed a clinical prediction model for assessing a recipient's risk of CAV using variables available at the time of HT. Application of this model may allow clinicians to determine which recipients will benefit from interventions to reduce the risk of development and progression of CAV.