Showing papers by "Sommer E. Gentry published in 2021"

TL;DR: In this paper, a multivariable Cox model was developed to predict survival up to 90 days after liver transplant registration in the US national registry from January 2016 through December 2018, where all candidates registered on the liver transplant wait list were included.

TL;DR: In this article, the authors used the Kaplan-Meier model to calculate 90-day without-transplant survival for men and women, separately at each MELD-Na.

TL;DR: In this paper, the authors compared the effect of the liver allocation system on adjusted deceased donor transplant and offer rates across Pediatric End-Stage Liver Disease (PELD) and Model for End-stage Liver disease (MELD) categories and types of exception statuses.

TL;DR: Using Scientific Registry of Transplant Recipients data from 2016‐2019, an integer program is used to design unique, heterogeneous circles with sizes between 100 and 500 nm that reduced supply/demand ratio variation across transplant centers and found that 40% of circles could be 250 nm or smaller, while reducing supply/ demand ratio variation more than homogeneous circles.

TL;DR: In this article, the authors used an adjusted Kaplan-Meier model to avoid unrealistic assumptions and multiple observations per person instead of just the observation at listing, and calculated without-transplant survival probabilities for each MELD score (and status 1A).

TL;DR: In February 2020, the Organ Procurement and Transplantation Network replaced donor service area‐based allocation of livers with acuity circles, a system based on three homogeneous circles around each donor hospital.

TL;DR: In this article, the authors used a bias-corrected Kaplan-Meier model to calculate the survival of status 1A candidates and to determine their life expectancy without a transplant.

TL;DR: In this article, the liver-simulated allocation model (LSAM) is used to predict the decision to accept or decline a liver for transplant for both adult and pediatric patients.

TL;DR: In this article, the authors used multilevel Poisson regression to model mortality risk in first-time waitlisted candidates from 120 centers and calculated a "MELD correction factor" using each center's random intercept and bMELD coefficient.