Citations

Background. Risk factors, virological parameters, and outcomes associated with HHV-6 viremia in high-risk donor CMV-seropositive and recipient CMV-seronegative (D+R–) liver transplant recipients in the current era are incompletely defined. Methods. The study population consisted of patients in the preemptive therapy (PET) arm of a randomized, controlled trial of PET versus valganciclovir prophylaxis for CMV prevention in D+R– liver transplant recipients. Weekly blood samples through 100 d in the PET group were tested for HHV-6 viremia using a real-time quantitative polymerase chain reaction. Assessments included virological characteristics and relationship with CMV, risk factors, and impact of HHV-6 viremia with outcomes through 12 mo posttransplant. Results. HHV-6 viremia at any level developed in 42% (40 of 96). Older patient age (P = 0.03), longer hospitalization (P = 0.015), and ICU stay at transplantation (P = 0.029) were significantly associated with high-grade viremia. Concurrent HHV-6 and CMV viremia was associated with earlier onset of HHV-6 viremia (P = 0.004), higher HHV-6 area under the curve (P = 0.043), and higher peak HHV-6 viral load (P = 0.006) versus HHV-6 viremia alone. High-grade viremia was independently associated with biopsy-proven rejection within 12 mo (P = 0.045) posttransplant. Conclusions. Among D+R– liver transplant recipients receiving valganciclovir as PET, high-grade HHV-6 viremia was associated with increased age and critical illness in ICU at time of transplant and was independently associated with allograft rejection.

Abstract Within COVID-19 there is an urgent unmet need to predict at the time of hospital admission which COVID-19 patients will recover from the disease, and how fast they recover to deliver personalized treatments and to properly allocate hospital resources so that healthcare systems do not become overwhelmed. To this end, we have combined clinically salient CT imaging data synergistically with laboratory testing data in an integrative machine learning model to predict organ-specific recovery of patients from COVID-19. We trained and validated our model in 285 patients on each separate major organ system impacted by COVID-19 including the renal, pulmonary, immune, cardiac, and hepatic systems. To greatly enhance the speed and utility of our model, we applied an artificial intelligence method to segment and classify regions on CT imaging, from which interpretable data could be directly fed into the predictive machine learning model for overall recovery. Across all organ systems we achieved validation set area under the receiver operator characteristic curve (AUC) values for organ-specific recovery ranging from 0.80 to 0.89, and significant overall recovery prediction in Kaplan-Meier analyses. This demonstrates that the synergistic use of an artificial intelligence (AI) framework applied to CT lung imaging and a machine learning model that integrates laboratory test data with imaging data can accurately predict the overall recovery of COVID-19 patients from baseline characteristics.

AbstractOne of the many challenges that has befallen the Infectious Diseases and Graduate Medical Education communities during the coronavirus disease 2019 (COVID-19) pandemic is the maintenance of continued effective education and training of the future leaders of our field. With the remarkable speed and innovation that has characterized the responses to this pandemic, educators everywhere have adapted existing robust and safe learning environments to meet the needs of our learners. This paper will review distinct aspects of education and training of the Infectious Diseases fellows we believe the COVID-19 pandemic has impacted most, including mentoring, didactics, and wellness. We anticipate that several strategies developed in this context and described herein will help to inform training and best practices during the pandemic and beyond.

Background: Vascular aging is associated with cognitive decline. Aortic stiffness is a hallmark of vascular aging. We tested the hypothesis that greater aortic stiffness is associated with a faster rate of cognitive decline over 5 years among older adults. Methods: A prospective cohort study at the 5th (2011-2013) and 6th (2016-2017) examinations of the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) was conducted to quantify the association between baseline aortic stiffness and cognitive decline over 5 years. A total of 4639 participants (mean age: 75 years, 41% men, 22% Black) with baseline measures of aortic stiffness and cognitive function were included in the analysis. Aortic stiffness was measured as carotid-femoral pulse wave velocity (cfPWV) using the Omron VP-1000 Plus device and analyzed continuously per 1 standard deviation meter/second (3.20 m/s). Elevated aortic stiffness was defined as the upper 25th percentile of cfPWV (13.39 m/s). Cognitive function was based on ten neuropsychological tests across multiple domains of cognition, including memory, executive function/processing speed, and language. A global cognitive performance factor score was estimated based on all cognitive tests at both visits. Multivariable linear regression was used to examine the associations of each standard deviation (SD) increment in cfPWV and elevated cfPWV with annual cognitive decline over 5 years. Interactions with baseline cognitive status were assessed. To account for attrition (35% over 5 years), multiple imputation by chained equations was used to impute missing global cognitive performance factor scores at visit 6. Results: Each 1 SD increase in cfPWV was associated with 0.008 SD (Beta (β)=-0.008, 95% confidence interval (CI): -0.010, -0.003) annual rate of decline in cognitive function after adjustment for age, sex, education, race-center and ApoE4. With additional adjustment for ever smoking, total weekly physical activity time, mean arterial pressure, diabetes, and body mass index, each SD higher cfPWV was associated with 0.005 SD (β=-0.005, 95% CI: -0.010, -0.001) annual rate of decline in cognitive function. Elevated cfPWV was associated with 0.015 SD (β=-0.015, 95% CI: -0.024, -0.005) annual decline in cognitive function, and with 0.010 SD (β=-0.010, 95% CI: -0.020, 0.0001) annual decline after additional adjustment. Conclusion: Higher aortic stiffness is associated with the rate of decline in global cognitive function among community-dwelling older adults. The hemodynamic sequelae of aortic stiffening may contribute to cognitive decline among older adults.

Abstract BACKGROUND Intravenous (IV) alteplase with mechanical thrombectomy has been found to be superior to alteplase alone in select patients with intracranial large vessel occlusion. Current guidelines discourage the use of antiplatelet agents or heparin for 24 h following alteplase. However, their use is often necessary in certain circumstances during thrombectomy procedures. OBJECTIVE To study the safety and outcomes in patients who received blood thinning medications for thrombectomy after IV Tissue-Type plasminogen activator (tPA). METHODS This is a multicenter retrospective review of the use of antiplatelet agents and/or heparin in patients within 24 h following tPA administration. Patient demographics, comorbidities, bleeding complications, and discharge outcomes were collected. RESULTS A series of 88 patients at 9 centers received antiplatelet medications and/or heparin anticoagulation following IV alteplase for revascularization procedures requiring stenting. The mean National Institutes of Health Stroke Scale (NIHSS) on admission was 14.6. Reasons for use of a stent included internal carotid artery occlusion in 74% of patients. Thrombolysis in cerebral infarction (TICI) 2b-3 revascularization was accomplished in 90% of patients. The rate of symptomatic intracranial hemorrhage (sICH) was 8%; this was not significantly different than the sICH rate for a matched group of patients not receiving antiplatelets or heparin during the same time frame. Functional independence at 90 d (modified Rankin Scale 0-2) was seen in 57.8% of patients. All-cause mortality was 12%. CONCLUSION The use of antiplatelet agents and heparin for stroke interventions following IV alteplase appears to be safe without significant increased risk of hemorrhagic complications in this group of patients when compared to control data and randomized controlled trials.

Background: An artificial intelligence (AI) algorithm applied to electrocardiography during sinus rhythm has recently been shown to detect concurrent episodic atrial fibrillation (AF). We sought to characterize the value of AI–enabled electrocardiography (AI-ECG) as a predictor of future AF and assess its performance compared with the CHARGE-AF score (Cohorts for Aging and Research in Genomic Epidemiology–AF) in a population-based sample. Methods: We calculated the probability of AF using AI-ECG, among participants in the population-based Mayo Clinic Study of Aging who had no history of AF at the time of the baseline study visit. Cox proportional hazards models were fit to assess the independent prognostic value and interaction between AI-ECG AF model output and CHARGE-AF score. C statistics were calculated for AI-ECG AF model output, CHARGE-AF score, and combined AI-ECG and CHARGE-AF score. Results: A total of 1936 participants with median age 75.8 (interquartile range, 70.4–81.8) years and median CHARGE-AF score 14.0 (IQR, 13.2–14.7) were included in the analysis. Participants with AI-ECG AF model output of >0.5 at the baseline visit had cumulative incidence of AF 21.5% at 2 years and 52.2% at 10 years. When included in the same model, both AI-ECG AF model output (hazard ratio, 1.76 per SD after logit transformation [95% CI, 1.51–2.04]) and CHARGE-AF score (hazard ratio, 1.90 per SD [95% CI, 1.58–2.28]) independently predicted future AF without significant interaction ( P =0.54). C statistics were 0.69 (95% CI, 0.66–0.72) for AI-ECG AF model output, 0.69 (95% CI, 0.66–0.71) for CHARGE-AF, and 0.72 (95% CI, 0.69–0.75) for combined AI-ECG and CHARGE-AF score. Conclusions: In the present study, both the AI-ECG AF model output and CHARGE-AF score independently predicted incident AF. The AI-ECG may offer a means to assess risk with a single test and without requiring manual or automated clinical data abstraction.

AbstractTau deposition is a key biological feature of Alzheimer’s disease that is closely related to cognitive impairment. However, it remains poorly understood why certain individuals may be more susceptible to tau deposition while others are more resistant. The recent availability of in vivo assessment of tau burden through positron emission tomography provides an opportunity to test the hypothesis that common genetic variants may influence tau deposition. We performed a genome-wide association study of tau-positron emission tomography on a sample of 754 individuals over age 50 (mean age 72.4 years, 54.6% men, 87.6% cognitively unimpaired) from the population-based Mayo Clinic Study of Aging. Linear regression was performed to test nucleotide polymorphism associations with AV-1451 (18F-flortaucipir) tau-positron emission tomography burden in an Alzheimer’s-signature composite region of interest, using an additive genetic model and covarying for age, sex and genetic principal components. Genome-wide significant associations with higher tau were identified for rs76752255 (P = 9.91 × 10−9, β = 0.20) in the tau phosphorylation regulatory gene PPP2R2B (protein phosphatase 2 regulatory subunit B) and for rs117402302 (P = 4.00 × 10−8, β = 0.19) near IGF2BP3 (insulin-like growth factor 2 mRNA-binding protein 3). The PPP2R2B association remained genome-wide significant after additionally covarying for global amyloid burden and cerebrovascular disease risk, while the IGF2BP3 association was partially attenuated after accounting for amyloid load. In addition to these discoveries, three single nucleotide polymorphisms within MAPT (microtubule-associated protein tau) displayed nominal associations with tau-positron emission tomography burden, and the association of the APOE (apolipoprotein E) ɛ4 allele with tau-positron emission tomography was marginally nonsignificant (P = 0.06, β = 0.07). No associations with tau-positron emission tomography burden were identified for other single nucleotide polymorphisms associated with Alzheimer’s disease clinical diagnosis in prior large case–control studies. Our findings nominate PPP2R2B and IGF2BP3 as novel potential influences on tau pathology which warrant further functional characterization. Our data are also supportive of previous literature on the associations of MAPT genetic variation with tau, and more broadly supports the inference that tau accumulation may have a genetic architecture distinct from known Alzheimer’s susceptibility genes, which may have implications for improved risk stratification and therapeutic targeting.