Safely Expanding the Liver Donor Pool by Utilization of Organs from Donation after Circulatory Death with Comparable Results to Donation After Brain Death, a Large Single-Center Experience.

BACKGROUND: Use of livers donated after circulatory death (DCD) is one way to expand the donor pool. Our center has aggressively incorporated use of DCD liver grafts into practice. We examined our center and national outcomes as well as national DCD liver utilization. METHODS: Liver transplants performed at our center and nationally from 11/2016 through 9/2020 were compared. Primary outcomes were patient and graft survival, and national DCD liver utilization. RESULTS: For our center, DCD and donation after brain death (DBD) donors were similar except DCD donors were younger (37 vs 40 years; p < 0.05). Recipient Na-MELD (20 vs 24; p < 0.0001) and cold ischemia time (4.63 vs 5.18 h; p < 0.05) were lower in DCD recipients. There were no significant differences in 1-year patient and graft survival between DCD and DBD liver recipients locally. Nationally, there was a difference in 1-year graft survival year (89.4% vs 92.4%, p < 0.0001) but patient survival was similar between groups. The proportion of DCD livers recovered and transplanted widely varied among organ procurement organizations (OPOs) and transplant centers. CONCLUSIONS: Similar outcomes for DCD and DBD liver recipients should encourage centers and OPOs nationwide to expand utilization of DCD livers.

Donation After Circulatory Death Yields Survival Rates Similar to Donation After Brain Death Liver Transplant, Which Effectively Expands the Donor Pool.

OBJECTIVES: Liver allograft shortage has necessitated greater use of donations after circulatory death. Limited data are available to compare recipients' health care utilization for donation after circulatory death versus brain death. MATERIALS AND METHODS: Liver transplant data for our center from November 2016 until May 2019 were obtained (208 donations after brain death and 39 after circulatory death). We excluded patients <18 years old and multiorgan transplants; for cost data only, we also excluded retransplants. Primary outcome was recipients' health care utilization in donation after circulatory death versus brain death and included index admission length of stay, readmissions, and charges from transplant to 6 months. Secondary outcomes were patient and graft survival. RESULTS: Donors from circulatory death were younger than donors from brain death (median age 32 vs 40 years; P < .01). Recipient body mass index (31.23 vs 29.38 kg/m2), Model for End-Stage Liver Disease score (17 vs 19), portal vein thrombosis (15.8% vs 18.0%), length of stay (7 vs 8 days), and 30-, 90-, and 180-day posttransplant index admissions were not significantly different. Charges for index admission were equivalent for donation after circulatory death ($370771) and brain death ($374272) (P = .01). Charges for readmissions at 30 and 180 days were not significantly different (P = .80 and P = .19, respectively). Rates for graft failure (10.3% vs 4.8%; P = .08) and recipient death (10.3% vs 3.8%; P = .17) at 6 months posttransplant were similar. CONCLUSIONS: Donation after circulatory death versus brain death liver transplant recipients had similar lengths of stay and equivalent index admission charges. Graft and patient survival and charges from transplant to 6 months were similar. Donation after circulatory death liver allografts provide a safe, costequivalent donor pool expansion after careful donorrecipient selection.

Unmasking Arrhythmogenic Hubs of Reentry Driving Persistent Atrial Fibrillation for Patient-Specific Treatment.

Background Atrial fibrillation (AF) driver mechanisms are obscured to clinical multielectrode mapping approaches that provide partial, surface-only visualization of unstable 3-dimensional atrial conduction. We hypothesized that transient modulation of refractoriness by pharmacologic challenge during multielectrode mapping improves visualization of hidden paths of reentrant AF drivers for targeted ablation. Methods and Results Pharmacologic challenge with adenosine was tested in ex vivo human hearts with a history of AF and cardiac diseases by multielectrode and high-resolution subsurface near-infrared optical mapping, integrated with 3-dimensional structural imaging and heart-specific computational simulations. Adenosine challenge was also studied on acutely terminated AF drivers in 10 patients with persistent AF. Ex vivo, adenosine stabilized reentrant driver paths within arrhythmogenic fibrotic hubs and improved visualization of reentrant paths, previously seen as focal or unstable breakthrough activation pattern, for targeted AF ablation. Computational simulations suggested that shortening of atrial refractoriness by adenosine may (1) improve driver stability by annihilating spatially unstable functional blocks and tightening reentrant circuits around fibrotic substrates, thus unmasking the common reentrant path; and (2) destabilize already stable reentrant drivers along fibrotic substrates by accelerating competing fibrillatory wavelets or secondary drivers. In patients with persistent AF, adenosine challenge unmasked hidden common reentry paths (9/15 AF drivers, 41±26% to 68±25% visualization), but worsened visualization of previously visible reentry paths (6/15, 74±14% to 34±12%). AF driver ablation led to acute termination of AF. Conclusions Our ex vivo to in vivo human translational study suggests that transiently altering atrial refractoriness can stabilize reentrant paths and unmask arrhythmogenic hubs to guide targeted AF driver ablation treatment.

Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping.

BACKGROUND: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypothesized that application of machine learning to electrogram frequency spectra may accurately automate driver detection by MEM and add some objectivity to the interpretation of MEM findings. METHODS: Temporally and spatially stable single AF drivers were mapped simultaneously in explanted human atria (n=11) by subsurface near-infrared optical mapping (NIOM; 0.3 mm2 resolution) and 64-electrode MEM (higher density or lower density with 3 and 9 mm2 resolution, respectively). Unipolar MEM and NIOM recordings were processed by Fourier transform analysis into 28 407 total Fourier spectra. Thirty-five features for machine learning were extracted from each Fourier spectrum. RESULTS: Targeted driver ablation and NIOM activation maps efficiently defined the center and periphery of AF driver preferential tracks and provided validated annotations for driver versus nondriver electrodes in MEM arrays. Compared with analysis of single electrogram frequency features, averaging the features from each of the 8 neighboring electrodes, significantly improved classification of AF driver electrograms. The classification metrics increased when less strict annotation, including driver periphery electrodes, were added to driver center annotation. Notably, f1-score for the binary classification of higher-density catheter data set was significantly higher than that of lower-density catheter (0.81±0.02 versus 0.66±0.04, P<0.05). The trained algorithm correctly highlighted 86% of driver regions with higher density but only 80% with lower-density MEM arrays (81% for lower-density+higher-density arrays together). CONCLUSIONS: The machine learning model pretrained on Fourier spectrum features allows efficient classification of electrograms recordings as AF driver or nondriver compared with the NIOM gold-standard. Future application of NIOM-validated machine learning approach may improve the accuracy of AF driver detection for targeted ablation treatment in patients.

Impaired neuronal sodium channels cause intranodal conduction failure and reentrant arrhythmias in human sinoatrial node.

Mechanisms for human sinoatrial node (SAN) dysfunction are poorly understood and whether human SAN excitability requires voltage-gated sodium channels (Nav) remains controversial. Here, we report that neuronal (n)Nav blockade and selective nNav1.6 blockade during high-resolution optical mapping in explanted human hearts depress intranodal SAN conduction, which worsens during autonomic stimulation and overdrive suppression to conduction failure. Partial cardiac (c)Nav blockade further impairs automaticity and intranodal conduction, leading to beat-to-beat variability and reentry. Multiple nNav transcripts are higher in SAN vs atria; heterogeneous alterations of several isoforms, specifically nNav1.6, are associated with heart failure and chronic alcohol consumption. In silico simulations of Nav distributions suggest that INa is essential for SAN conduction, especially in fibrotic failing hearts. Our results reveal that not only cNav but nNav are also integral for preventing disease-induced failure in human SAN intranodal conduction. Disease-impaired nNav may underlie patient-specific SAN dysfunctions and should be considered to treat arrhythmias.

Human Atrial Fibrillation Drivers Resolved With Integrated Functional and Structural Imaging to Benefit Clinical Mapping.

OBJECTIVES: This study sought to improve atrial fibrillation (AF) driver identification by integrating clinical multielectrode mapping with driver fingerprints defined by high-resolution ex vivo 3-dimensional (3D) functional and structural imaging. BACKGROUND: Clinical multielectrode mapping of AF drivers suffers from variable contact, signal processing, and structural complexity within the 3D human atrial wall, raising questions on the validity of such drivers. METHODS: Sustained AF was mapped in coronary-perfused explanted human hearts (n = 11) with transmural near-infrared optical mapping (∼0.3 mm2 resolution). Simultaneously, custom FIRMap catheters (∼9 × 9 mm2 resolution) mapped endocardial and epicardial surfaces, which were analyzed by Focal Impulse and Rotor Mapping activation and Rotational Activity Profile (Abbott Labs, Chicago, Illinois). Functional maps were integrated with contrast-enhanced cardiac magnetic resonance imaging (∼0.1 mm3 resolution) analysis of 3D fibrosis architecture. RESULTS: During sustained AF, near-infrared optical mapping identified 1 to 2 intramural, spatially stable re-entrant AF drivers per heart. Driver targeted ablation affecting 2.2 ± 1.1% of the atrial surface terminated and prevented AF. Driver regions had significantly higher phase singularity density and dominant frequency than neighboring nondriver regions. Focal Impulse and Rotor Mapping had 80% sensitivity to near-infrared optical mapping-defined driver locations (16 of 20), and matched 14 of 20 driver visualizations: 10 of 14 re-entries seen with Rotational Activity Profile; and 4 of 6 breakthrough/focal patterns. Focal Impulse and Rotor Mapping detected 1.1 ± 0.9 false-positive rotational activity profiles per recording, but these regions had lower intramural contrast-enhanced cardiac magnetic resonance imaging fibrosis than did driver regions (14.9 ± 7.9% vs. 23.2 ± 10.5%; p < 0.005). CONCLUSIONS: The study revealed that both re-entrant and breakthrough/focal AF driver patterns visualized by surface-only clinical multielectrodes can represent projections of 3D intramural microanatomic re-entries. Integration of multielectrode mapping and 3D fibrosis analysis may enhance AF driver detection, thereby improving the efficacy of driver-targeted ablation.