Résumé
Introduction: Although cardiac allograft vasculopathy (CAV) remains one of the leading causes of graft failure after heart transplantation (HTx), simultaneous thrombosis of multiple epicardial coronary arteries (CA) is an uncommon finding. Case Report: A 43-year-old male patient with non-ischemic dilated cardiomyopathy underwent successful HTx in 2019. The first two years after HTx were uneventful, surveillance endomyocardial biopsies (EMB) did not reveal any rejection episodes, coronary CTA revealed only minimal non-calcified CA plaques. The patient was admitted to hospital due to fever and chest pain in 2021. Immunosuppressive therapy consisted of tacrolimus, mycophenolate-mofetil and methylprednisolone. ECG verified sinus rhythm. Laboratory test revealed elevated hsTroponin T, NT-proBNP and CRP levels. Cytomegalovirus, SARS-CoV-2-virus and hemoculture testing was negative. Several high-titre donor-specific HLA class I and II antibodies (DSAs;including complement-binding DQ7) could have been detected since 2020. Echocardiography confirmed mildly decreased left ventricular systolic function and apical hypokinesis. EMB verified mild cellular and antibody-mediated rejection (ABMR) according to ISHLT grading criteria. Cardiac MRI revealed inferobasal and apical myocardial infarction (MI);thus, an urgent coronary angiography was performed. This confirmed thrombotic occlusions in all three main epicardial CAs and in first diagonal CA. As revascularization was not feasible, antithrombotic therapy with acetylsalicylic acid, clopidogrel and enoxaparin was started for secondary prevention. Tests for immune system disorders, thrombophilia and cancer were negative. Patient suddenly died ten days after admission. Necropsy revealed intimal proliferation in all three main epicardial CAs, endothelitis, thrombosis, chronic pericoronary fat inflammation, fat necrosis, and subacute MI. CA vasculitis owing to persistent high-titre DSAs, chronic ABMR and acute cellular and antibody-mediated rejection led to multivessel CA thrombosis and acute multiple MI. ABMR after HTx may be underdiagnosed with traditional pathological methods. Pathologies affecting coronary vasculature of HTx patients with DSAs, unique manifestations of CAV lesions and occlusive thrombosis of non-stenotic, non-atherosclerotic lesions should be emphasized.Copyright © 2023
Résumé
Heart transplant (HTX) recipients are prone to develop serious symptoms after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their vaccination is often ineffective. In this high-volume single center study, we aimed to examine the seroconversion rates achieved with various types and doses of SARS-CoV-2 vaccines and assessed factors influencing vaccine immunogenicity and predictors of severe SARS-CoV-2 infection. 229 HTX recipients were enrolled at a university clinic. Type of the first two doses of vaccine included mRNA, vector and inactivated vaccines as well. We carried out analyses on seroconversion after the second and third doses of vaccination and on severity of coronavirus disease 2019 (COVID-19). Anti-SARS-CoV-2 IgG levels were measured with Elecsys immunoassay (Roche). Effect of the first two vaccine doses was studied on patients who did not suffer SARS-CoV-2 infection before antibody measurement (n=175). Seroconversion after the third vaccine was analysed among seronegative patients after two doses (n=53). Predictors for severe infection defined as pneumonia, hospitalization or death was assessed in all HTX recipients who had COVID-19 (n=92). Logistic regression was applied for further analyses. 62% of the recipients became seropositive after the second vaccination. Longer time between HTX and vaccination (OR: 2.35, 95% CI: 1.28 - 4.49, p=0.007) and mRNA type of vaccine (OR: 4.83, 95% CI: 1.33 - 17.5, p=0.012) were predictors of seroconversion. 58% of the non-responsive patients became seropositive after receiving the third vaccine. Male sex increased the chance of IgG production after the third dose (OR: 5.65, 95% CI: 1.61 - 22.7, p=0.009). Clinical course of SARS-CoV-2 infection was severe in 32%. Of all parameters assessed, only seropositivity was proven to have a protective effect against severe infection (OR: 0.12, 95% CI: 0.02 - 0.64, p=0.019). Longer time since HTX, mRNA vaccine type and male sex promoted seroconversion after SARS-CoV-2 vaccination in HTX recipients. Seropositivity was proven to be protective against severe SARS-CoV-2 infection in single center cohort. Routine screening of HTX patients for anti-SARS-COV-2 antibodies may help to identify patients at risk for severe infection requiring addtional measures of anti-SARS-CoV-2 protection. [ FROM AUTHOR] Copyright of Journal of Heart & Lung Transplantation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
Résumé
Background High rate of people infected with SARS-CoV-2 and their contacts in Cologne, Germany required innovative tools for notification, monitoring and reporting. The digital tool for COVID19 (DiKoMa) provides self-service symptom diaries allowing (a) the stratification for prioritized telephone contact by the health authority and (b) training a machine learning (ML) model that predicts infections with prevailing dominant variant (PDV) from early symptom profiles (SP). Methods Pseudononymized SP covering the first week of diary recordings were included for training (16646 index, 11582 contacts). A balanced random forest (BRF) model was trained to differentiate early predictive symptom patterns of different PDV and contact persons. Model evaluation was performed using sex and age stratified cross validation (CV), the model was validated on SP recorded from days 1 and 6. Results From 03/20 to 02/22, 90478 indeces and 75444 contact persons reported symptoms and health status, covering 46% and 42% of all reported cases, respectively. Diaries contained between 1-52 entries (566791, median 2). Daily analysis of entries, prioritized according to age, prevalent co-morbidities and detoriation of symptoms allowed risk adjusted follow up even during phases with high case notification rates. The top 5 predictive factors of the BRF were immunization, cough, dysgeusia and dysnosmia, fatigue, and sniffles to differentiate infection between wildtype, three PDV and contact persons (CV AUC 80.6%, Validation AUC 77.1%). Conclusions The use of digital symptom diary surveillance helps to provide appropriate medical support for patients on a large scale. Machine learning shows potential for symptom based risk assessment to differentiate PDV for future outbreaks and can thus become a valuable tool alongside specific laboratory diagnostics. Key messages • Digital symptom diaries are a powerful and widely accepted tool to attend COVID19 patients in isolation. They allow risk stratification for follow up and are a low-threshold service. • Machine learning supports index case identification by symptom analysis and can thus become a valuable tool alongside specific laboratory diagnostics.