Pediatric donor heart acceptance practices in the United States: What is really being considered?

BACKGROUND: Recent studies demonstrate high offer decline and organ non-utilization rates are associated with increased pediatric heart transplant waitlist mortality. We sought to determine which donor, candidate, and offer specific variables most importantly influenced these decisions using only data available at the time of each offer. METHODS: Retrospective review of pediatric (<18 years) heart donor offers made to pediatric candidates in the United States between 2010 and 2020. In addition to standard donor, candidate, and offer data available in UNOS, we extracted objective and qualitative valvar and myocardial function data from all available donor echocardiogram reports. RESULTS: During the study period, 5625 pediatric donor hearts produced 30 156 offers to 4905 unique candidates, of which 88.7% of all offers were declined and 39.2% of organs were not utilized by pediatric waitlisted candidates. Of the 60.8% utilized hearts, 89.7% had a 'cumulatively' normal echocardiogram at the time of offer acceptance; 62.9% of hearts not utilized for a pediatric candidate also had a cumulatively normal final echocardiogram. Random forest and logistic regression modeling demonstrated good predictive performance (AUROC ≥0.83) of likelihood to accept when utilizing donor, candidate, and offer specific variables. SHAP variable importance scores demonstrated number of prior offer declines and candidate institution's prior year acceptance rates as the two most important variables influencing offer decisions. CONCLUSIONS: Behavioral economics appear to play a significant role in pediatric heart transplant candidate institutions' acceptance practices, even when considering the arguably healthier pediatric donor population. Removal of prior institution's decisions from DonorNet may help increase donor utilization.

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.46 ppm.

We present the first results of the Fermilab National Accelerator Laboratory (FNAL) Muon g-2 Experiment for the positive muon magnetic anomaly a_{µ}≡(g_{µ}-2)/2. The anomaly is determined from the precision measurements of two angular frequencies. Intensity variation of high-energy positrons from muon decays directly encodes the difference frequency ω_{a} between the spin-precession and cyclotron frequencies for polarized muons in a magnetic storage ring. The storage ring magnetic field is measured using nuclear magnetic resonance probes calibrated in terms of the equivalent proton spin precession frequency ω[over ˜]_{p}^{'} in a spherical water sample at 34.7 °C. The ratio ω_{a}/ω[over ˜]_{p}^{'}, together with known fundamental constants, determines a_{µ}(FNAL)=116 592 040(54)×10^{-11} (0.46 ppm). The result is 3.3 standard deviations greater than the standard model prediction and is in excellent agreement with the previous Brookhaven National Laboratory (BNL) E821 measurement. After combination with previous measurements of both µ^{+} and µ^{-}, the new experimental average of a_{µ}(Exp)=116 592 061(41)×10^{-11} (0.35 ppm) increases the tension between experiment and theory to 4.2 standard deviations.

First Observation of P-odd γ Asymmetry in Polarized Neutron Capture on Hydrogen.

We report the first observation of the parity-violating gamma-ray asymmetry A_{γ}^{np} in neutron-proton capture using polarized cold neutrons incident on a liquid parahydrogen target at the Spallation Neutron Source at Oak Ridge National Laboratory. A_{γ}^{np} isolates the ΔI=1, ^{3}S_{1}→^{3}P_{1} component of the weak nucleon-nucleon interaction, which is dominated by pion exchange and can be directly related to a single coupling constant in either the DDH meson exchange model or pionless effective field theory. We measured A_{γ}^{np}=[-3.0±1.4(stat)±0.2(syst)]×10^{-8}, which implies a DDH weak πNN coupling of h_{π}^{1}=[2.6±1.2(stat)±0.2(syst)]×10^{-7} and a pionless EFT constant of C^{^{3}S_{1}→^{3}P_{1}}/C_{0}=[-7.4±3.5(stat)±0.5(syst)]×10^{-11} MeV^{-1}. We describe the experiment, data analysis, systematic uncertainties, and implications of the result.