17 research outputs found
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Computational models are an essential tool for the design, characterization,
and discovery of novel materials. Hard computational tasks in materials science
stretch the limits of existing high-performance supercomputing centers,
consuming much of their simulation, analysis, and data resources. Quantum
computing, on the other hand, is an emerging technology with the potential to
accelerate many of the computational tasks needed for materials science. In
order to do that, the quantum technology must interact with conventional
high-performance computing in several ways: approximate results validation,
identification of hard problems, and synergies in quantum-centric
supercomputing. In this paper, we provide a perspective on how quantum-centric
supercomputing can help address critical computational problems in materials
science, the challenges to face in order to solve representative use cases, and
new suggested directions.Comment: 60 pages, 14 figures; comments welcom
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Wait Time Advantage for Transplant Candidates With HIV Who Accept Kidneys From Donors With HIV Under the HOPE Act.
BACKGROUND: Kidney transplant (KT) candidates with HIV face higher mortality on the waitlist compared with candidates without HIV. Because the HIV Organ Policy Equity (HOPE) Act has expanded the donor pool to allow donors with HIV (D + ), it is crucial to understand whether this has impacted transplant rates for this population. METHODS: Using a linkage between the HOPE in Action trial (NCT03500315) and Scientific Registry of Transplant Recipients, we identified 324 candidates listed for D + kidneys (HOPE) compared with 46 025 candidates not listed for D + kidneys (non-HOPE) at the same centers between April 26, 2018, and May 24, 2022. We characterized KT rate, KT type (D + , false-positive [FP; donor with false-positive HIV testing], D - [donor without HIV], living donor [LD]) and quantified the association between HOPE enrollment and KT rate using multivariable Cox regression with center-level clustering; HOPE was a time-varying exposure. RESULTS: HOPE candidates were more likely male individuals (79% versus 62%), Black (73% versus 35%), and publicly insured (71% versus 52%; P < 0.001). Within 4.5 y, 70% of HOPE candidates received a KT (41% D + , 34% D - , 20% FP, 4% LD) versus 43% of non-HOPE candidates (74% D - , 26% LD). Conversely, 22% of HOPE candidates versus 39% of non-HOPE candidates died or were removed from the waitlist. Median KT wait time was 10.3 mo for HOPE versus 60.8 mo for non-HOPE candidates ( P < 0.001). After adjustment, HOPE candidates had a 3.30-fold higher KT rate (adjusted hazard ratio = 3.30, 95% confidence interval, 2.14-5.10; P < 0.001). CONCLUSIONS: Listing for D + kidneys within HOPE trials was associated with a higher KT rate and shorter wait time, supporting the expansion of this practice for candidates with HIV
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Wait Time Advantage for Transplant Candidates With HIV Who Accept Kidneys From Donors With HIV Under the HOPE Act
Kidney transplant (KT) candidates with HIV face higher mortality on the waitlist compared with candidates without HIV. Because the HIV Organ Policy Equity (HOPE) Act has expanded the donor pool to allow donors with HIV (D + ), it is crucial to understand whether this has impacted transplant rates for this population.
Using a linkage between the HOPE in Action trial (NCT03500315) and Scientific Registry of Transplant Recipients, we identified 324 candidates listed for D + kidneys (HOPE) compared with 46 025 candidates not listed for D + kidneys (non-HOPE) at the same centers between April 26, 2018, and May 24, 2022. We characterized KT rate, KT type (D + , false-positive [FP; donor with false-positive HIV testing], D - [donor without HIV], living donor [LD]) and quantified the association between HOPE enrollment and KT rate using multivariable Cox regression with center-level clustering; HOPE was a time-varying exposure.
HOPE candidates were more likely male individuals (79% versus 62%), Black (73% versus 35%), and publicly insured (71% versus 52%; P < 0.001). Within 4.5 y, 70% of HOPE candidates received a KT (41% D + , 34% D - , 20% FP, 4% LD) versus 43% of non-HOPE candidates (74% D - , 26% LD). Conversely, 22% of HOPE candidates versus 39% of non-HOPE candidates died or were removed from the waitlist. Median KT wait time was 10.3 mo for HOPE versus 60.8 mo for non-HOPE candidates ( P < 0.001). After adjustment, HOPE candidates had a 3.30-fold higher KT rate (adjusted hazard ratio = 3.30, 95% confidence interval, 2.14-5.10; P < 0.001).
Listing for D + kidneys within HOPE trials was associated with a higher KT rate and shorter wait time, supporting the expansion of this practice for candidates with HIV
Recommended from our members
Wait Time Advantage for Transplant Candidates With HIV Who Accept Kidneys From Donors With HIV Under the HOPE Act
BACKGROUNDKidney transplant (KT) candidates with HIV face higher mortality on the waitlist compared with candidates without HIV. Because the HIV Organ Policy Equity (HOPE) Act has expanded the donor pool to allow donors with HIV (D+), it is crucial to understand whether this has impacted transplant rates for this population.METHODSUsing a linkage between the HOPE in Action trial (NCT03500315) and Scientific Registry of Transplant Recipients, we identified 324 candidates listed for D+ kidneys (HOPE) compared with 46 025 candidates not listed for D+ kidneys (non-HOPE) at the same centers between April 26, 2018, and May 24, 2022. We characterized KT rate, KT type (D+, false-positive [FP; donor with false-positive HIV testing], D- [donor without HIV], living donor [LD]) and quantified the association between HOPE enrollment and KT rate using multivariable Cox regression with center-level clustering; HOPE was a time-varying exposure.RESULTSHOPE candidates were more likely male individuals (79% versus 62%), Black (73% versus 35%), and publicly insured (71% versus 52%; P < 0.001). Within 4.5 y, 70% of HOPE candidates received a KT (41% D+, 34% D-, 20% FP, 4% LD) versus 43% of non-HOPE candidates (74% D-, 26% LD). Conversely, 22% of HOPE candidates versus 39% of non-HOPE candidates died or were removed from the waitlist. Median KT wait time was 10.3 mo for HOPE versus 60.8 mo for non-HOPE candidates (P < 0.001). After adjustment, HOPE candidates had a 3.30-fold higher KT rate (adjusted hazard ratio = 3.30, 95% confidence interval, 2.14-5.10; P < 0.001).CONCLUSIONSListing for D+ kidneys within HOPE trials was associated with a higher KT rate and shorter wait time, supporting the expansion of this practice for candidates with HIV