The Accuracy of Nonstandardized MELD/PELD Score Exceptions in the Pediatric Liver Allocation System.

BACKGROUND: In the United States, over half of pediatric candidates receive exceptions and status upgrades that increase their allocation model of end-stage liver disease/pediatric end-stage liver disease (MELD/PELD) score above their laboratory MELD/PELD score. We determined whether these "nonstandardized" MELD/PELD exceptions accurately depict true pretransplant mortality risk. METHODS: Using data from the Scientific Registry of Transplant Recipients, we identified pediatric candidates (<18 y of age) with chronic liver failure added to the waitlist between June 2016 and September 2021 and estimated all-cause pretransplant mortality with mixed-effects Cox proportional hazards models that treated allocation MELD/PELD and exception status as time-dependent covariates. We also estimated concordance statistics comparing the performance of laboratory MELD/PELD with allocation MELD/PELD. We then compared the proportion of candidates with exceptions before and after the establishment of the National Liver Review Board. RESULTS: Out of 2026 pediatric candidates listed during our study period, 403 (19.9%) received an exception within a week of listing and 1182 (58.3%) received an exception before delisting. Candidates prioritized by their laboratory MELD/PELD scores had an almost 9 times greater risk of pretransplant mortality compared with candidates who received the same allocation score from an exception (hazard ratio 8.69; 95% confidence interval, 4.71-16.03; P < 0.001). The laboratory MELD/PELD score without exceptions was more accurate than the allocation MELD/PELD score with exceptions (Harrell's c-index 0.843 versus 0.763). The proportion of patients with an active exception at the time of transplant decreased significantly after the National Liver Review Board was implemented (67.4% versus 43.4%, P < 0.001). CONCLUSIONS: Nonstandardized exceptions undermine the rank ordering of pediatric candidates with chronic liver failure.

The Accuracy of Initial U.S. Heart Transplant Candidate Rankings.

BACKGROUND: The U.S. heart allocation system ranks candidates with only 6 treatment-based categorical "statuses" and ignores many objective patient characteristics. OBJECTIVES: This study sought to determine the effectiveness of the standard 6-status ranking system and several novel prediction models in identifying the most urgent heart transplant candidates. METHODS: The primary outcome was death before receipt of a heart transplant. The accuracy of the 6-status system was evaluated using Harrell's C-index and log-rank tests of Kaplan-Meier estimated survival by status for candidates listed postpolicy (November 2018 to March 2020) in the Scientific Registry of Transplant Recipients data set. The authors then developed Cox proportional hazards models and random survival forest models using prepolicy data (2010-2017). The predictor variables included age, diagnosis, laboratory measurements, hemodynamics, and supportive treatment at the time of listing. The performance of these models was compared with the candidate's 6-status ranking in the postpolicy data. RESULTS: Since policy implementation, the 6-status ranking at listing has had moderate ability to rank-order candidates (C-index: 0.67). Statuses 4 and 6 had no significant difference in survival (P = 0.80), and status 5 had lower survival than status 4 (P < 0.001). Novel multivariable prediction models derived with prepolicy data ranked candidates correctly more often than the 6-status rankings (Cox proportional hazards model C-index: 0.76; random survival forest model C-index: 0.74). Objective physiologic measurements, such as glomerular filtration rate, had high variable importance. CONCLUSIONS: The treatment-based 6-status heart allocation system has only moderate ability to rank-order candidates by medical urgency. Predictive models that incorporate physiologic measurements can more effectively rank-order heart transplant candidates by urgency.

Association of Zip Code Vaccination Rate With COVID-19 Mortality in Chicago, Illinois.

Importance: There has been large geographic inequity in vaccination coverage across Chicago, Illinois, with higher vaccination rates in zip codes with residents who predominantly have high incomes and are White. Objective: To determine the association between inequitable zip code-level vaccination coverage and COVID-19 mortality in Chicago. Design, Setting, and Participants: This retrospective cohort study used Chicago Department of Public Health vaccination and mortality data and Cook County Medical Examiner mortality data from March 1, 2020, through November 6, 2021, to assess the association of COVID-19 mortality with zip code-level vaccination rates. Data were analyzed from June 1, 2021, to April 13, 2022. Exposures: Zip code-level first-dose vaccination rates before the Alpha and Delta waves of COVID-19. Main Outcomes and Measures: The primary outcome was deaths from COVID-19 during the Alpha and Delta waves. The association of a marginal increase in zip code-level vaccination rate with weekly mortality rates was estimated with a mixed-effects Poisson regression model, and the total number of preventable deaths in the least vaccinated quartile of zip codes was estimated with a linear difference-in-difference design. Results: The study population was 2 686 355 Chicago residents in 52 zip codes (median [IQR] age 34 [32-38] years; 1 378 658 [51%] women; 773 938 Hispanic residents [29%]; 783 916 non-Hispanic Black residents [29%]; 894 555 non-Hispanic White residents [33%]). Among residents in the least vaccinated quartile, 80% were non-Hispanic Black, compared with 8% of residents identifying as non-Hispanic Black in the most vaccinated quartile (P < .001). After controlling for age distribution and recovery from COVID-19, a 10-percentage point increase in zip code-level vaccination 6 weeks before the peak of the Alpha wave was associated with a 39% lower relative risk of death from COVID-19 (incidence rate ratio [IRR], 0.61 [95% CI, 0.52-0.72]). A 10-percentage point increase in zip code vaccination rate 6 weeks before the peak of the Delta wave was associated with a 24% lower relative risk of death (IRR, 0.76 [95% CI, 0.66-0.87]). The difference-in-difference estimate was that 119 Alpha wave deaths (72% [95% CI, 63%-81%]) and 108 Delta wave deaths (75% [95% CI, 66%-84%]) might have been prevented in the least vaccinated quartile of zip codes if it had had the vaccination coverage of the most vaccinated quartile. Conclusions and Relevance: These findings suggest that low zip code-level vaccination rates in Chicago were associated with more deaths during the Alpha and Delta waves of COVID-19 and that inequitable vaccination coverage exacerbated existing racial and ethnic disparities in COVID-19 deaths.

An updated estimate of posttransplant survival after implementation of the new donor heart allocation policy.

The Organ Procurement and Transplant Network (OPTN) implemented a new heart allocation policy on October 18, 2018. Published estimates of lower posttransplant survival under the new policy in cohorts with limited follow-up may be biased by informative censoring. Using the Scientific Registry of Transplant Recipients, we used the Kaplan-Meier method to estimate 1-year posttransplant survival for pre-policy (November 1, 2016, to October 31, 2017) and post-policy cohorts (November 1, 2018, to October 31, 2019) with follow-up through March 2, 2021. We adjusted for changes in recipient population over time with a multivariable Cox proportional hazards model. To demonstrate the effect of inadequate follow-up on post-policy survival estimates, we repeated the analysis but only included follow-up through October 31, 2019. Transplant programs transplanted 2594 patients in the pre-policy cohort and 2761 patients in the post-policy cohort. With follow-up through March 2, 2021, unadjusted 1-year posttransplant survival was 90.6% (89.5%-91.8%) in the pre-policy cohort and 90.8% (89.7%-91.9%) in the post-policy cohort (adjusted HR = 0.93 [0.77-1.12]). Ignoring follow-up after October 31, 2019, the post-policy estimate was biased downward (1-year: 82.2%). When estimated with adequate follow-up, 1-year posttransplant survival under the new heart allocation policy was not significantly different.

Molecular dynamics and charge transport in organic semiconductors: a classical approach to modeling electron transfer.

Organic photovoltaics (OPVs) are a promising carbon-neutral energy conversion technology, with recent improvements pushing power conversion efficiencies over 10%. A major factor limiting OPV performance is inefficiency of charge transport in organic semiconducting materials (OSCs). Due to strong coupling with lattice degrees of freedom, the charges form polarons, localized quasi-particles comprised of charges dressed with phonons. These polarons can be conceptualized as pseudo-atoms with a greater effective mass than a bare charge. We propose that due to this increased mass, polarons can be modeled with Langevin molecular dynamics (LMD), a classical approach with a computational cost much lower than most quantum mechanical methods. Here we present LMD simulations of charge transfer between a pair of fullerene molecules, which commonly serve as electron acceptors in OSCs. We find transfer rates consistent with experimental measurements of charge mobility, suggesting that this method may provide quantitative predictions of efficiency when used to simulate materials on the device scale. Our approach also offers information that is not captured in the overall transfer rate or mobility: in the simulation data, we observe exactly when and why intermolecular transfer events occur. In addition, we demonstrate that these simulations can shed light on the properties of polarons in OSCs. Much remains to be learned about these quasi-particles, and there are no widely accepted methods for calculating properties such as effective mass and friction. Our model offers a promising approach to exploring mass and friction as well as providing insight into the details of polaron transport in OSCs.

Exciton size and quantum transport in nanoplatelets.

Two-dimensional nanoplatelets (NPLs) are an exciting class of materials with promising optical and energy transport properties. The possibility of efficient energy transport between nanoplatelets raises questions regarding the nature of energy transfer in these thin, laterally extended systems. A challenge in understanding exciton transport is the uncertainty regarding the size of the exciton. Depending on the material and defects in the nanoplatelet, an exciton could plausibly extend over an entire plate or localize to a small region. The variation in possible exciton sizes raises the question how exciton size impacts the efficiency of transport between nanoplatelet structures. Here, we explore this issue using a quantum master equation approach. This method goes beyond the assumptions of Förster theory to allow for quantum mechanical effects that could increase energy transfer efficiency. The model is extremely flexible in describing different systems, allowing us to test the effect of varying the spatial extent of the exciton. We first discuss qualitative aspects of the relationship between exciton size and transport and then conduct simulations of exciton transport between NPLs for a range of exciton sizes and environmental conditions. Our results reveal that exciton size has a strong effect on energy transfer efficiency and suggest that manipulation of exciton size may be useful in designing NPLs for energy transport.

Predictive a priori pressure-dependent kinetics.

The ability to predict the pressure dependence of chemical reaction rates would be a great boon to kinetic modeling of processes such as combustion and atmospheric chemistry. This pressure dependence is intimately related to the rate of collision-induced transitions in energy E and angular momentum J. We present a scheme for predicting this pressure dependence based on coupling trajectory-based determinations of moments of the E,J-resolved collisional transfer rates with the two-dimensional master equation. This completely a priori procedure provides a means for proceeding beyond the empiricism of prior work. The requisite microcanonical dissociation rates are obtained from ab initio transition state theory. Predictions for the CH4 = CH3 + H and C2H3 = C2H2 + H reaction systems are in excellent agreement with experiment.

Coherent transport and energy flow patterns in photosynthesis under incoherent excitation.

Long-lived coherences have been observed in photosynthetic complexes after laser excitation, inspiring new theories regarding the extreme quantum efficiency of photosynthetic energy transfer. Whether coherent (ballistic) transport occurs in nature and whether it improves photosynthetic efficiency remain topics of debate. Here, we use a nonequilibrium Green's function analysis to model exciton transport after excitation from an incoherent source (as opposed to coherent laser excitation). We find that even with an incoherent source, the rate of environmental dephasing strongly affects exciton transport efficiency, suggesting that the relationship between dephasing and efficiency is not an artifact of coherent excitation. The Green's function analysis provides a clear view of both the pattern of excitonic fluxes among chromophores and the multidirectionality of energy transfer that is a feature of coherent transport. We see that even in the presence of an incoherent source, transport occurs by qualitatively different mechanisms as dephasing increases. Our approach can be generalized to complex synthetic systems and may provide a new tool for optimizing synthetic light harvesting materials.

Inhomogeneous dephasing masks coherence lifetimes in ensemble measurements.

An open question at the forefront of modern physical sciences is what role, if any, quantum effects may play in biological sensing and energy transport mechanisms. One area of such research concerns the possibility of coherent energy transport in photosynthetic systems. Spectroscopic evidence of long-lived quantum coherence in photosynthetic light-harvesting pigment protein complexes (PPCs), along with theoretical modeling of PPCs, has indicated that coherent energy transport might boost efficiency of energy transport in photosynthesis. Accurate assessment of coherence lifetimes is crucial for modeling the extent to which quantum effects participate in this energy transfer, because such quantum effects can only contribute to mechanisms proceeding on timescales over which the coherences persist. While spectroscopy is a useful way to measure coherence lifetimes, inhomogeneity in the transition energies across the measured ensemble may lead to underestimation of coherence lifetimes from spectroscopic experiments. Theoretical models of antenna complexes generally model a single system, and direct comparison of single system models to ensemble averaged experimental data may lead to systematic underestimation of coherence lifetimes, distorting much of the current discussion. In this study, we use simulations of the Fenna-Matthews-Olson complex to model single complexes as well as averaged ensembles to demonstrate and roughly quantify the effect of averaging over an inhomogeneous ensemble on measured coherence lifetimes. We choose to model the Fenna-Matthews-Olson complex because that system has been a focus for much of the recent discussion of quantum effects in biology, and use an early version of the well known environment-assisted quantum transport model to facilitate straightforward comparison between the current model and past work. Although ensemble inhomogeneity is known to lead to shorter lifetimes of observed oscillations (simply inhomogeneous spectral broadening in the time domain), this important fact has been left out of recent discussions of spectroscopic measurements of energy transport in photosynthesis. In general, these discussions have compared single-system theoretical models to whole-ensemble laboratory measurements without addressing the effect of inhomogeneous dephasing. Our work addresses this distinction between single system and ensemble averaged observations, and shows that the ensemble averaging inherent in many experiments leads to an underestimation of coherence lifetimes in individual systems.