BACKGROUND Sensitized heart transplant candidates are evaluated for donor-specific anti-HLA IgG antibody (DSA) by Luminex single-antigen bead (SAB) testing (SAB-IgG) to determine donor suitability and help predict a positive complement-dependent cytotoxicity crossmatch (CDC-XM) by virtual crossmatching (VXM). However, SAB testing used for VXM does not correlate perfectly with CDC-XM results and individual transplant programs have center-specific permissible thresholds to predict crossmatch positivity. A novel Luminex SAB-based assay detecting C1q-binding HLA antibodies (SAB-C1q) contributes functional information to SAB testing, but the relationship between SAB strength and complement-binding ability is unclear. METHODS In this retrospective study, we identified 15 pediatric and adult heart allograft candidates with calculated panel-reactive antibody (cPRA) >50% by SAB-IgG and compared conventional SAB-IgG results with SAB-C1q testing. RESULTS Pre- and post-transplant DSA by SAB-C1q correlated with DSA by SAB-IgG and also with CDC-XM results and early post-transplant endomyocardial biopsy findings. Individual HLA antibodies by SAB-IgG in undiluted sera correlated poorly with SAB-C1q; however, when sera were diluted 1:16, SAB-IgG results were well correlated with SAB-C1q. In some sera, HLA antibodies with low mean fluorescent intensity (MFI) by SAB-IgG exhibited high SAB-C1q MFIs for the same HLA antigens. Diluting or heat-treating these sera increased SAB-IgG MFI, consistent with SAB-C1q results. In 13 recipients, SAB-C1q–positive DSA was associated with positive CDC-XM and with early clinical post-transplant antibody-mediated rejection (cAMR). CONCLUSIONS Risk assessment for positive CDC-XM and early cAMR in sensitized heart allograft recipients are correlated with SAB-C1q reactivity.

Perioperative morbidity and mortality adversely affects short-term survival in ACHDR. ACHDR who survive the first post-transplant year have equivalent or better long-term survival than NCR.

Background New-onset heart failure (HF) is associated with poor prognosis and high healthcare utilization. Early identification of patients at increased risk incident-HF may allow for focused allocation of preventative care resources. Health information exchange (HIE) data span the entire spectrum of clinical care, but there are no HIE-based clinical decision support tools for diagnosis of incident-HF. We applied machine-learning methods to model the one-year risk of incident-HF from the Maine statewide-HIE. Methods and results We included subjects aged ≥ 40 years without prior HF ICD9/10 codes during a three-year period from 2015 to 2018, and incident-HF defined as assignment of two outpatient or one inpatient code in a year. A tree-boosting algorithm was used to model the probability of incident-HF in year two from data collected in year one, and then validated in year three. 5,668 of 521,347 patients (1.09%) developed incident-HF in the validation cohort. In the validation cohort, the model c-statistic was 0.824 and at a clinically predetermined risk threshold, 10% of patients identified by the model developed incident-HF and 29% of all incident-HF cases in the state of Maine were identified. Conclusions Utilizing machine learning modeling techniques on passively collected clinical HIE data, we developed and validated an incident-HF prediction tool that performs on par with other models that require proactively collected clinical data. Our algorithm could be integrated into other HIEs to leverage the EMR resources to provide individuals, systems, and payors with a risk stratification tool to allow for targeted resource allocation to reduce incident-HF disease burden on individuals and health care systems.

Cardiac allograft vasculopathy (CAV) is a major risk factor influencing graft loss and patient survival following orthotopic heart transplant. Allograft vasculopathy is a multifactorial process, which includes both immunologic and non-immunologic mechanisms. Given the non-immunological risk factors for vasculopathy, particularly hyperlipidemia, it is intuitive that reducing a patient's LDL would help attenuate the disease process. Multiple studies have shown benefits with the use of statin therapy. However, current heart transplant guidelines do not give a specific recommendation as to what LDL goal should be achieved in this patient population. This study is a retrospective cohort analysis designed to determine the relative risk of developing cardiac allograft vasculopathy with respect to different LDL goals. Median LDL level of <100 mg/dL was shown to significantly reduce the risk of developing cardiac allograft vasculopathy. Twelve of 37 patients with an LDL ≥100 mg/dL (32.4%) developed CAV vs 25 of 157 patients (15.9%) with an LDL <100 mg/dL (P = .021). Furthermore, a delay in to time to cardiac allograft vasculopathy was seen when a median LDL concentration of <100 mg/dL was achieved. This benefit was not extended when a goal concentration of <70 mg/dL was targeted.

RAP and LVGLS at the first annual evaluation provide complementary prognostic information in predicting 5-year outcome after HT.