Immune response, phenotyping and molecular graft surveillance in kidney transplant recipients following severe acute respiratory syndrome coronavirus 2 vaccination.

BACKGROUND: Understanding immunogenicity and alloimmune risk following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination in kidney transplant recipients is imperative to understanding the correlates of protection and to inform clinical guidelines. METHODS: We studied 50 kidney transplant recipients following SARS-CoV-2 vaccination and quantified their anti-spike protein antibody, donor-derived cell-free DNA (dd-cfDNA), gene expression profiling (GEP), and alloantibody formation. RESULTS: Participants were stratified using nucleocapsid testing as either SARS-CoV-2-naïve or experienced prior to vaccination. One of 34 (3%) SARS-CoV-2 naïve participants developed anti-spike protein antibodies. In contrast, the odds ratio for the association of a prior history of SARS-CoV-2 infection with vaccine response was 18.3 (95% confidence interval 3.2, 105.0, p < 0.01). Pre- and post-vaccination levels did not change for median dd-cfDNA (0.23% vs. 0.21% respectively, p = 0.13), GEP scores (9.85 vs. 10.4 respectively, p = 0.45), calculated panel reactive antibody, de-novo donor specific antibody status, or estimated glomerular filtration rate. CONCLUSIONS: SARS-CoV-2 vaccines do not appear to trigger alloimmunity in kidney transplant recipients. The degree of vaccine immunogenicity was associated most strongly with a prior history of SARS-CoV-2 infection.

High levels of donor-derived cell-free DNA in a case of graft-versus-host-disease following liver transplantation.

The diagnosis of graft-versus-host-disease (GVHD) after solid organ transplantation is made difficult by its variable clinical presentation and lack of sensitive and specific biomarkers to evaluate the immune state of transplant recipients. Emerging noninvasive diagnostic techniques like the quantification of donor-derived cell-free DNA (dd-cfDNA) for surveillance may improve the current standard-of-care. Herein, we report the use of this methodology in a patient with GVHD and corresponding levels of dd-cfDNA without any evidence of graft injury. Correlation of dd-cfDNA levels with the clinical course and its novel application here could lead to improvements in the rapid diagnosis of GVHD and in monitoring of response to treatment.

Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy.

Epilepsy diagnosis can be costly, time-consuming, and not uncommonly inaccurate. The reference standard diagnostic monitoring is continuous video-electroencephalography (EEG) monitoring, ideally capturing all events or concordant interictal discharges. Automating EEG data review would save time and resources, thus enabling more people to receive reference standard monitoring and also potentially heralding a more quantitative approach to therapeutic outcomes. There is substantial research into the automated detection of seizures and epileptic activity from EEG. However, automated detection software is not widely used in the clinic, and despite numerous published algorithms, few methods have regulatory approval for detecting epileptic activity from EEG. This study reports on a deep learning algorithm for computer-assisted EEG review. Deep convolutional neural networks were trained to detect epileptic discharges using a preexisting dataset of over 6000 labelled events in a cohort of 103 patients with idiopathic generalized epilepsy (IGE). Patients underwent 24-hour ambulatory outpatient EEG, and all data were curated and confirmed independently by two epilepsy specialists (Seneviratne et al., 2016). The resulting automated detection algorithm was then used to review diagnostic scalp EEG for seven patients (four with IGE and three with events mimicking seizures) to validate performance in a clinical setting. The automated detection algorithm showed state-of-the-art performance for detecting epileptic activity from clinical EEG, with mean sensitivity of >95% and corresponding mean false positive rate of 1 detection per minute. Importantly, diagnostic case studies showed that the automated detection algorithm reduced human review time by 80%-99%, without compromising event detection or diagnostic accuracy. The presented results demonstrate that computer-assisted review can increase the speed and accuracy of EEG assessment and has the potential to greatly improve therapeutic outcomes. This article is part of the Special Issue "NEWroscience 2018".

Transition of Renal Patients Using AlloSure Into Community Kidney Care (TRACK): Protocol for Long-Term Allograft Surveillance in Renal Transplant Recipients.

BACKGROUND: Patients with end-stage kidney disease require complex and expensive medical management. Kidney transplantation remains the treatment of choice for end-stage kidney disease and is considered superior to all other modalities of renal replacement therapy or dialysis. However, access to kidney transplant is limited by critical supply and demand, making it extremely important to ensure longevity of transplanted kidneys. This is prevented through lifelong immunosuppression, with caution not to overly suppress the immune system, resulting in toxicity and harm. Transition of care to community nephrologists after initial kidney transplantation and monitoring at a transplant center is an important process to ensure delivery of effective and patient-centric care closer to home. Once transplanted, laborious surveillance of the immune system and monitoring for potential rejection and injury are undertaken through an armamentarium of screening modalities. Posttransplant surveillance for kidney function and injury remains key to follow-up care. While kidney function, quantified by estimated glomerular filtration rate and serum creatinine, and kidney injury, measured by proteinuria and hematuria, are standard biomarkers used to monitor injury and rejection posttransplant, they have recently been demonstrated to be inferior in performance to that of AlloSure (CareDx Inc, Brisbane, CA) circulating donor-derived, cell-free DNA (dd-cfDNA). OBJECTIVE: The outcomes and methods of monitoring renal transplant recipients posttransplant have remained stagnant over the past 15 years. The aim of this study is to consider intensive surveillance using AlloSure dd-cfDNA in an actively managed protocol, assessing whether it increases long-term allograft survival in kidney transplant recipients compared with current standard clinical care in community nephrology. METHODS: The study protocol will acquire data from a phase IV observational trial to assess a cohort of renal transplant patients managed using AlloSure dd-cfDNA and patient care managers versus 1000 propensity-matched historic controls using United Network for Organ Sharing U.S. Scientific Registry of Transplant Recipients data. Data will be managed in a centralized electronic data server. The primary outcome will be superior allograft survival, as a composite of return to dialysis, retransplant, death due to allograft failure, and death with a functional graft (infection, malignancy, and cardiovascular death). The secondary endpoints will assess improved kidney function through decline in estimated glomerular filtration rate and immune activity through development of donor-specific antibodies. RESULTS: The total sample is anticipated to be 3500 (2500 patients managed with AlloSure dd-cfDNA and 1000 propensity-matched controls). Active enrollment began in November 2020. CONCLUSIONS: Based on a significant literature base, we believe implementing the surveillance of dd-cfDNA in the kidney transplant population will have a positive impact on graft survival. Through early identification of rejection and facilitating timely intervention, prolongation of allograft survival versus those not managed by dd-cfDNA surveillance protocol should be superior. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25941.

Review article: Isolated proximal tibiofibular joint dislocation.

Proximal tibiofibular joint (PTFJ) dislocations are relatively rare injuries and this paper provides an up-to-date review and practical management approach for the assessment and management of these cases. Isolated PTFJ dislocations are a rare injury, accounting for less than 1% of all knee injuries. Thus, there does not appear to be a clear consensus on definitive management and post-reduction care in the literature. This paper provides a review of the literature, anatomical analysis of the PTFJ in the dislocated state, and a technique for reduction. In the majority of cases, PTFJ dislocations are an injury that can be identified with simple imaging modalities and treated in the ED with manipulation under procedural sedation.