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Development and Validation of a Risk Score Predicting Death Without Transplant in Adult Heart Transplant Candidates | Surgery | JAMA

This study develops and validates a multivariable prediction model to rank order adult heart transplant candidates by medical urgency.

National institutes of healthUnited statesWilliamf parkerUniversity of chicagoBlood instituteR foundation for statistical computingUs department of healthTransplantation networkSecurity administrationNational instituteUniversity of chicago biological sciences divisionGreenwall foundationNational institute of diabetesDepartment of defenseBoehringer ingelheimNational heart

Updating allocation algorithms could help donor hearts reach the transplant patients who need them most

UChicago Medicine researchers led the development of a new risk score for prioritizing heart transplant candidates based on medical urgency, incorporating objec

United statesAnoop mayampurathCarine jasseronKevinc zhangKevina lazenbyNikhil narangJonathan grinsteinRichard dorentMarkn belkinWilliamf parkerKirank khushKevin zhangMatthewm churpekUniversity of chicago medicinePublic healthChicago medicine

Revamped Allocation Algorithms May Boost Heart Transplant Success

Revamped Allocation Algorithms May Boost Heart Transplant Success
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United statesMatthewm churpekMarkn belkinAnoop mayampurathKevina lazenbyCarine jasseronKevinc zhangNikhil narangWilliamf parkerJonathan grinsteinRichard dorentKevin zhangKirank khushUniversity of chicago medicinePublic healthChicago medicine

Updating allocation algorithms could help donor hearts reach the transplant patients who need them most

UChicago Medicine researchers led the development of a new risk score for prioritizing heart transplant candidates based on medical urgency, incorporating objec

United statesKevin zhangMatthewm churpekWilliamf parkerKirank khushKevina lazenbyRichard dorentKevinc zhangAnoop mayampurathMarkn belkinNikhil narangJonathan grinsteinCarine jasseronUniversity of chicago medicinePublic healthChicago medicine