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The volume of biomedical knowledge is growing exponentially and much of this knowledge is represented in computer executable formats, such as models, algorithms, and programmatic code. There is a growing need to apply this knowledge to improve health in Learning Health Systems, health delivery organizations, and other settings. However, most organizations do not yet have the infrastructure required to consume and apply computable knowledge, and national policies and standards adoption are not sufficient to ensure that it is discoverable and used safely and fairly, nor is there widespread experience in the process of knowledge implementation as clinical decision support. The Mobilizing Computable Biomedical Knowledge (MCBK) community was formed in 2016 to address these needs. This report summarizes the main outputs of the third annual MCBK public meeting, which was held virtually from June 30 to July 1, 2020 and brought together over 200 participants from various domains to frame and address important dimensions for mobilizing CBK. The rapid response to COVID-19 has necessitated infrastructural development and reorientation in order to safely meet patient care needs. A qualitative case study was constructed within a larger ethnographic field study. Document collection and fieldnotes and recordings from nonparticipant observation of network activities were compiled and chronologically ordered to chart the network's response to changes in epilepsy care resulting from COVID-19 and the rapid transition to telemedicine. The network's response to COVID-19 was characterized by a predisposition to action, the role of sharing as both a group practice and shared value, and the identification of improvement science as the primary contribution of the group within the larger epilepsy community's response to COVID-19. The findings are interpreted as an example of how group culture can shape action via a transparent and mundane shared infrastructure. The case of one multi-stakeholder epilepsy Learning Network provides an example of the use of infrastructure that is shaped by the group's culture. These findings contribute to the development of a social theory of infrastructure within Learning Health Systems. The case of one multi-stakeholder epilepsy Learning Network provides an example of the use of infrastructure that is shaped by the group's culture. These findings contribute to the development of a social theory of infrastructure within Learning Health Systems. Organizational transformations have focused on creating and fulfilling value for customers, leveraging advanced technologies. Transforming public health (PH) faces an interesting challenge. The value created (preventive practices) to fulfill policy makers' desire to reduce healthcare costs is realized by several external partners with varying goals and is practiced by the public (value in use), which often places low priority on prevention. This paper uses value lens to argue that PH transformation strategy must align the goals of all stakeholders involved. This may include allowing partners and the public to contextualize the preventive practices to see the value in near term and as relevant. It also means extending the number of partners PH uses and helping them connect with the public to seek shared alignment in shared goals of value fulfillment and value-in-use. Using lessons from Covid-19 and PH experience with partners in four different sectors business, healthcare, public and community, the paper illustrates how PH transformation strategy can be implemented going forward. We conclude the paper with five distinct directions for future research to create and sustain value using the framework of learning health systems. We conclude the paper with five distinct directions for future research to create and sustain value using the framework of learning health systems. Simultaneous liver-kidney (SLK) and simultaneous heart-kidney (SHK) transplantation currently utilize 6% of deceased donor kidneys in the United States. To what extent residual kidney function accounts for apparent kidney allograft survival is unknown. We examined all adult SLK and SHK transplants in the United States during 1995-2014. We considered the duration of dialysis preceding SLK or SHK (≥90 d, 1-89 d, or none) as a proxy of residual kidney function. https://www.selleckchem.com/Bcl-2.html We used multinomial logistic regression to estimate the difference in the adjusted likelihood of 6- and 12-month apparent kidney allograft failure between the no dialysis versus ≥90 days dialysis groups. Of 4875 SLK and 848 SHK recipients, 1775 (36%) SLK and 449 (53%) SHK recipients received no dialysis before transplant. The likelihood of apparent kidney allograft failure was 1%-3% lower at 12 months in SLK and SHK recipients who did not require pretransplant dialysis relative to recipients who required ≥90 days of pretransplant dialysis. Among 3978 SLK recipients who survived to 1 year, no pretransplant dialysis was associated with a lower risk of apparent kidney allograft failure over a median follow-up of 5.7 years (adjusted hazard ratio 0.73 [0.55-0.96]). Patients with residual kidney function at the time of multiorgan transplantation are less likely to have apparent failure of the kidney allograft. Whether residual kidney function facilitates function of the allograft or whether some SLK and SHK recipients have 3 functional kidneys is unknown. Sustained kidney function after SLK and SHK transplants does not necessarily indicate successful MOT. Patients with residual kidney function at the time of multiorgan transplantation are less likely to have apparent failure of the kidney allograft. Whether residual kidney function facilitates function of the allograft or whether some SLK and SHK recipients have 3 functional kidneys is unknown. Sustained kidney function after SLK and SHK transplants does not necessarily indicate successful MOT. Donor-derived cell-free DNA (dd-cfDNA) is a useful biomarker of rejection that originates from allograft cells undergoing injury. Plasma levels <1% in kidney transplant recipients have a high negative predictive value for active allograft rejection. The utility of this biomarker in kidney transplant recipients receiving immune checkpoint inhibitor therapy is unknown. We describe a case in which serial dd-cfDNA monitoring facilitated the use of immune checkpoint inhibitor therapy, which is known to be associated with high rates of rejection, in a kidney transplant recipient with metastatic cancer. A 72-y-old man with end-stage kidney disease secondary to autosomal dominant polycystic kidney disease underwent living unrelated kidney transplant in December 2010. His immunosuppression regimen included tacrolimus, mycophenolate, and prednisone. In July 2017, he presented with metastatic cutaneous squamous cell carcinoma. After his disease progressed through radiation therapy and cetuximab, he received pembrolizumab (antiprogrammed cell death protein 1).
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