Faculty Bibliography

Racial and ethnic disparities persist in access to the liver transplantation (LT) waiting list; however, there is limited knowledge about underlying system-level factors that may be responsible for these disparities. Given the complex nature of LT candidate evaluation, a human factors and systems engineering approach may provide insights. We recruited participants from the LT teams (coordinators, advanced practice providers, physicians, social workers, dieticians, pharmacists, leadership) at two major LT centers. From December 2020 to July 2021, we performed ethnographic observations (participant-patient appointments, committee meetings) and semistructured interviews (N = 54 interviews, 49 observation hours). Based on findings from this multicenter, multimethod qualitative study combined with the Systems Engineering Initiative for Patient Safety 2.0 (a human factors and systems engineering model for health care), we created a conceptual framework describing how transplant work system characteristics and other external factors may improve equity in the LT evaluation process. Participant perceptions about listing disparities described external factors (e.g., structural racism, ambiguous national guidelines, national quality metrics) that permeate the LT evaluation process. Mechanisms identified included minimal transplant team diversity, implicit bias, and interpersonal racism. A lack of resources was a common theme, such as social workers, transportation assistance, non-English-language materials, and time (e.g., more time for education for patients with health literacy concerns). Because of the minimal data collection or center feedback about disparities, participants felt uncomfortable with and unadaptable to unwanted outcomes, which perpetuate disparities. We proposed transplant center-level solutions (i.e., including but not limited to training of staff on health equity) to modifiable barriers in the clinical work system that could help patient navigation, reduce disparities, and improve access to care. Our findings call for an urgent need for transplant centers, national societies, and policy makers to focus efforts on improving equity (tailored, patient-centered resources) using the science of human factors and systems engineering.

BACKGROUND:Solid organ transplant recipients (SOTRs) are less likely to mount an antibody response to SARS-CoV-2 mRNA vaccines. Understanding risk factors for impaired vaccine response can guide strategies for antibody testing and additional vaccine dose recommendations. METHODS:Using a nationwide observational cohort of 1031 SOTRs, we created a machine learning model to explore, identify, rank, and quantify the association of 19 clinical factors with antibody responses to 2 doses of SARS-CoV-2 mRNA vaccines. External validation of the model was performed using a cohort of 512 SOTRs at Houston Methodist Hospital. RESULTS:Mycophenolate mofetil use, a shorter time since transplant, and older age were the strongest predictors of a negative antibody response, collectively contributing to 76% of the model's prediction performance. Other clinical factors, including transplanted organ, vaccine type (mRNA-1273 versus BNT162b2), sex, race, and other immunosuppressants, showed comparatively weaker associations with an antibody response. This model showed moderate prediction performance, with an area under the receiver operating characteristic curve of 0.79 in our cohort and 0.67 in the external validation cohort. An online calculator based on our prediction model is available at http://transplantmodels.com/covidvaccine/. CONCLUSIONS:Our machine learning model helps understand which transplant patients need closer follow-up and additional doses of vaccine to achieve protective immunity. The online calculator based on this model can be incorporated into transplant providers' practice to facilitate patient-centric, precision risk stratification and inform vaccination strategies among SOTRs.

Donation after circulatory determination of death (DCDD) has increased organ donation rates in the US over the past decade within an established legal framework, which is consistent with and supports individual and family decisions regarding organ donation in the context of end-of-life care. A new application, controlled DCDD donation utilizing thoracoabdominal normothermic regional perfusion (NRP) protocols (cDCDD-NRP), provides the opportunity to maximize a donation decision by recovering additional organs for transplant, including the heart, and to limit the detrimental impact of warm ischemic time by perfusing organs in situ following the declaration of circulatory death. In this viewpoint, we narrate our rationale for why cDCDD-NRP is consistent within the existing legal framework for organ donation in the United States and recommend no changes to the Uniform Determination of Death Act.

Heterologous vaccination ("mixing platforms") for the third (D3) dose of SARS-CoV-2 vaccine is a potential strategy to improve antibody responses in solid organ transplant recipients (SOTRs), but data are mixed regarding potential differential immunogenicity. We assessed for differences in immunogenicity and tolerability of homologous (BNT162b2 or mRNA-1273; D3-mRNA) versus heterologous (Ad.26.COV2.S; D3-JJ) D3 among 377 SARS-CoV-2-infection naïve SOTRs who remained seronegative after two mRNA vaccines. We measured anti-spike titers and used weighted Poisson regression to evaluate seroconversion and development of high-titers, comparing D3-JJ to D3-mRNA, at 1-, 3-, and 6 month post-D3. 1-month post-D3, seroconversion (63% vs. 52%, p = .3) and development of high-titers (29% vs. 25%, p = .7) were comparable between D3-JJ and D3-mRNA recipients. 3 month post-D3, D3-JJ recipients were 1.4-fold more likely to seroconvert (80% vs. 57%, weighted incidence-rate-ratio: wIRR = _1.10 1.40_1.77 , p = .006) but not more likely to develop high-titers (27% vs. 22%, wIRR = _0.44 0.92_1.93 , p = .8). 6 month post-D3, D3-JJ recipients were 1.41-fold more likely to seroconvert (88% vs. 59%, wIRR = _1.04 1.41_1.93 , p = .029) and 2.63-fold more likely to develop high-titers (59% vs. 21%, wIRR = _1.38 2.63_5.00 , p = .003). There was no differential signal in alloimmune events or reactogenicity between platforms. SOTRs without antibody response after two mRNA vaccines may derive benefit from heterologous Ad.26.COV2.S D3.

UNLABELLED:Automation of deceased donor referrals with standardized clinical triggers allows organ procurement organizations to be rapidly aware of medically eligible potential donors without the need for manual reporting and subjective decision-making of otherwise very busy hospital staff. In October 2018, 3 Texas hospitals (pilot hospitals) began using an automated referral system; our goal was to evaluate the impact of this system on eligible donor referral. METHODS/UNASSIGNED:We studied ventilated referrals (n = 28 034) in a single organ procurement organization from January 2015 to March 2021. We estimated the change in referral rate in the 3 pilot hospitals due to the automated referral system using a difference-in-differences analysis with Poisson regression. RESULTS/UNASSIGNED:). CONCLUSIONS/UNASSIGNED:Following deployment of an automated referral system that did not require any actions by the referring hospital, referrals, authorizations, and organ donors increased substantially in the 3 pilot hospitals. Broader deployment of automated referral systems may lead to increases in the deceased donor pool.