Citations

AbstractBackgroundBrain amyloid‐β (Aβ) is the pathological hallmark of Alzheimer’s disease (AD). In logistic disease models, Aβ accumulation is a sigmoid function of time‐since‐disease‐onset (TSDO) (figure 1). Previous positron emission tomography (PET)‐based models vary accumulation onset(t50) and duration(r) globally; capacity(K) and baseline(NS) regionally (Whittington2018). We confirm existing approaches and propose a more powerful ICA‐based approach to quantify disease severity and estimate TSDO.MethodWe used 1071 18F‐florbetapir standard uptake value ratio (SUVR) images from the ADNI‐2 study (adni.loni.usc.edu/data‐samples/data‐types/pet). Images were mapped into MNI space. Averages were extracted using the Harvard‐Oxford brain‐atlas. Whole‐brain tracer‐specific sigmoid parameters (Jack2013) obtained from the literature were used to estimate TSDO.Of 16 models of regional Aβ accumulation (each of the 4 regional sigmoid parameters varied either regionally or globally), the optimal Bayesian information criterion was found with global t50 and r, and regional NS and K (figure 1) with global values r = 6.16y and t50 = 4.10y.Linearised maps of NS and K were obtained by regressing the SUVR maps onto the global sigmoid. We also estimated these maps as independent components, using a 2‐component ICA on the SUVR maps. Both outcomes were used to quantify Aβ accumulation from SUVR images as weighting factors of the accumulation map.We compared the weights from the logistic model and the ICA model in ADNI, using effect size measured with Hedges' g between cognitively normal (CN), subjective memory complaints (SMC), mild cognitive impairment (EMCI/MCI/LMCI) and AD groups. We compared 3 longitudinal visits (N = 112) in the OASIS‐3 study (see www.oasis‐brains.org) with both methods, global SUVR and Centiloid (Klunk2015) using 11C‐PiB PET SUVR images.ResultMaps of accumulation capacity from both models had spatial correlation of 0.86 (figure 2); baseline maps had spatial correlation of 0.95. Hedges' g between ADNI groups was 2.25 for K, and 2.42 for ICA (1.46 for global SUVR). In OASIS‐3, Hedges' g between visits was 1.24 for K, 1.46 for ICA (global SUVR 0.15, Centiloid 0.4).ConclusionWe demonstrate that linear accumulation models can be used to quantify brain Aβ with PET; maps obtained by ICA yield larger effect sizes than the logistic method for differentiating groups and measuring changes between visits.

Objective: The purpose of this study was to describe management and outcomes from a contemporary cohort of children with Wilms tumor complicated by inferior vena caval thrombus. Background: The largest series of these patients was published almost 2 decades ago. Since then, neoadjuvant chemotherapy has been commonly used to manage these patients, and outcomes have not been reported. Methods: Retrospective review of 19 North American centers between 2009 and 2019. Patient and disease characteristics, management, and outcomes were investigated and analyzed. Results: Of 124 patients, 81% had favorable histology (FH), and 52% were stage IV. IVC thrombus level was infrahepatic in 53 (43%), intrahepatic in 32 (26%), suprahepatic in 14 (11%), and cardiac in 24 (19%). Neoadjuvant chemotherapy using a 3-drug regimen was administered in 82% and postresection radiation in 90%. Thrombus level regression was 45% overall, with suprahepatic level showing the best response (62%). Cardiopulmonary bypass (CPB) was potentially avoided in 67%. The perioperative complication rate was significantly lower after neoadjuvant chemotherapy [(25%) vs upfront surgery (55%); P=0.005]. CPB was not associated with higher complications [CPB (50%) vs no CPB (27%); P=0.08]. Two-year event-free survival was 93% and overall survival was 96%, higher in FH cases (FH 98% vs unfavorable histology/anaplastic 82%; P=0.73). Neither incomplete resection nor viable thrombus cells affected event-free survival or overall survival. Conclusions: Multimodal therapy resulted in excellent outcomes, even with advanced-stage disease and cardiac extension. Neoadjuvant chemotherapy decreased the need for CPB to facilitate resection. Complete thrombectomy may not always be necessary.

Accurate prediction of progression in subjects at risk of Alzheimer's disease is crucial for enrolling the right subjects in clinical trials. However, a prospective comparison of state-of-the-art algorithms for predicting disease onset and progression is currently lacking. We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of patient-specific biomarkers. On a limited, cross-sectional subset of the data emulating clinical trials, performance of the best algorithms at predicting clinical diagnosis decreased only slightly (2 percentage points) compared to the full longitudinal dataset. The submission system remains open via the website https://tadpole.grand-challenge.org, while TADPOLE SHARE (https://tadpole-share.github.io/) collates code for submissions. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials.

ABSTRACT Updated guidelines on the management of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) were released in 2021 by the American College of Rheumatology jointly with the Vasculitis Foundation and, subsequently, in 2022 by the European Alliance of Associations for Rheumatology. In addition, in 2021, the Kidney Disease: Improving Global Outcomes had released updated recommendations on the treatment of AAV with glomerulonephritis (AAV-GN). Kidney involvement is particularly relevant in microscopic polyangiitis and granulomatosis with polyangiitis, but is less frequent in eosinophilic granulomatosis with polyangiitis. The management of AAV-GN has been a focus for drug development and change over the past 10 years. Avoidance of progression to end-stage kidney disease (ESKD) or kidney failure is one of the main unmet needs in the management of AAV, with ESKD having a major impact on morbidity, health costs and mortality risk. Relevant changes in AAV-GN management are related to remission-induction treatment of patients with severe kidney disease, the use of glucocorticoids and avacopan, and remission-maintenance treatment. All the documents provide guidance in accordance with the evidence-based standard of care available at the time of their release. With our work we aim to (i) show the progress made and identify the differences between guidelines and recommendations, (ii) discuss the supporting rationale for those, and (iii) identify gaps in knowledge that could benefit from additional research and should be revised in subsequent updates.

Introduction Postcardiotomy veno-arterial extracorporeal membrane oxygenation (V-A-ECMO) is associated with significant mortality. Identification of patients at very high risk for death is elusive and the decision to initiate V-A-ECMO is based on clinical judgment. The prognostic impact of pre-V-A-ECMO arterial lactate level in these critically ill patients has been herein evaluated. Methods A systematic review was conducted to identify studies on postcardiotomy VA-ECMO for the present individual patient data meta-analysis. Results Overall, 1269 patients selected from 10 studies were included in this analysis. Arterial lactate level at V-A-ECMO initiation was increased in patients who died during the index hospitalization compared to those who survived (9.3 vs 6.6 mmol/L, p < 0.0001). Accordingly, in hospital mortality increased along quintiles of pre-V-A-ECMO arterial lactate level (quintiles: 1, 54.9%; 2, 54.9%; 3, 67.3%; 4, 74.2%; 5, 82.2%, p < 0.0001). The best cut-off for arterial lactate was 6.8 mmol/L (in-hospital mortality, 76.7% vs. 55.7%, p < 0.0001). Multivariable multilevel mixed-effect logistic regression model including arterial lactate level significantly increased the area under the receiver operating characteristics curve (0.731, 95% CI 0.702–0.760 vs 0.679, 95% CI 0.648–0.711, DeLong test p < 0.0001). Classification and regression tree analysis showed the in-hospital mortality was 85.2% in patients aged more than 70 years with pre-V-A-ECMO arterial lactate level ≥6.8 mmol/L. Conclusions Among patients requiring postcardiotomy V-A-ECMO, hyperlactatemia was associated with a marked increase of in-hospital mortality. Arterial lactate may be useful in guiding the decision-making process and the timing of initiation of postcardiotomy V-A-ECMO.

ImportanceTumor necrosis factor α (TNF) inhibitor–induced psoriasiform eruption is well recognized in adults, but few reports document this paradoxical effect in children.ObjectiveTo characterize the clinical features and the clinical time course of TNF inhibitor–induced psoriasiform eruptions in children.Design, Setting, and ParticipantsA multicenter retrospective case series of children younger than 18 years seen between January 1, 2000, and December 31, 2016, who developed a new-onset psoriasiform eruption while taking a TNF inhibitor for a nondermatologic disorder. Participating sites were members of the Pediatric Dermatology Research Alliance. Data were entered into a Research Electronic Data Capture database at the Mayo Clinic (ie, the coordinating center).ResultsPsoriasiform eruptions were identified in 103 TNF inhibitor–treated patients (median age, 13.8 years [IQR, 11.7-16.4 years]; 52 female patients [50%]; 57 White patients [55%]), with 67 patients (65%) treated with infliximab, 35 (34%) with adalimumab, and 1 (1%) with certolizumab pegol. Most patients had no personal history (101 [98%]) or family history of psoriasis (60 patients [58%]). Inflammatory bowel disease was the most common indication for treatment with TNF inhibitor (94 patients [91%]). The primary extracutaneous disease was under control in 95 patients (92%) who developed the eruption. Most patients (n = 85 [83%]) developed psoriasiform eruptions at multiple anatomic sites, with scalp involvement being most common (65 patients [63%]). Skin disease developed at a median of 14.5 months (IQR, 9-24 months) after TNF inhibitor initiation. To treat the psoriasiform eruption, topical steroidal and nonsteroidal medication was prescribed for all patients. Systemic therapy was added for 30 patients (29%): methotrexate for 24 patients (23%), oral corticosteroids for 8 patients (8%), and azathioprine for 1 patient (1%). For 26 patients (25%), suboptimal effectiveness with topical medications alone prompted discontinuation of the initial TNF inhibitor and a change to a second-line TNF inhibitor with cutaneous improvement in 23 patients (88%) by a median of 3 months (IQR, 2-4 months). Eight patients (31%) who started a second-line TNF inhibitor developed a subsequent TNF inhibitor–induced psoriasiform eruption at a median of 6 months (IQR, 4-8 months). Persistent skin disease in 18 patients (17%) prompted discontinuation of all TNF inhibitors; 11 patients changed to a non-TNF inhibitor systemic therapy, and 7 discontinued all systemic therapy.Conclusions and RelevanceIn this case series, paradoxical TNF inhibitor–induced psoriasiform eruptions were seen in children treated with TNF inhibitors for any indication, and there appears to be a class effect among the varying TNF inhibitors. The majority of these children were able to continue TNF inhibitor therapy with adequate skin-directed and other adjuvant therapies.

We identified seven age-associated extracellular matrix (ECM) proteins, i.e., COL1A1, COL6A1, COL6A2 COL14A1, FBLN2, LTBP4, and LUM with higher transcript and protein levels in human lung tissue with age. Extensive immunohistochemical analysis revealed significant age-associated differences for COL6A2 in whole tissue, parenchyma, airway wall, and vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in parenchyma. Our findings lay a new foundation for the investigation of ECM differences in age-associated chronic lung diseases.

Abstract Aims Recent studies have revealed a close connection between cellular metabolism and the chronic inflammatory process of atherosclerosis. While the link between systemic metabolism and atherosclerosis is well established, the implications of altered metabolism in the artery wall are less understood. Pyruvate dehydrogenase kinase (PDK)-dependent inhibition of pyruvate dehydrogenase (PDH) has been identified as a major metabolic step regulating inflammation. Whether the PDK/PDH axis plays a role in vascular inflammation and atherosclerotic cardiovascular disease remains unclear. Methods and results Gene profiling of human atherosclerotic plaques revealed a strong correlation between PDK1 and PDK4 transcript levels and the expression of pro-inflammatory and destabilizing genes. Remarkably, the PDK1 and PDK4 expression correlated with a more vulnerable plaque phenotype, and PDK1 expression was found to predict future major adverse cardiovascular events. Using the small-molecule PDK inhibitor dichloroacetate (DCA) that restores arterial PDH activity, we demonstrated that the PDK/PDH axis is a major immunometabolic pathway, regulating immune cell polarization, plaque development, and fibrous cap formation in Apoe−/− mice. Surprisingly, we discovered that DCA regulates succinate release and mitigates its GPR91-dependent signals promoting NLRP3 inflammasome activation and IL-1β secretion by macrophages in the plaque. Conclusions We have demonstrated for the first time that the PDK/PDH axis is associated with vascular inflammation in humans and particularly that the PDK1 isozyme is associated with more severe disease and could predict secondary cardiovascular events. Moreover, we demonstrate that targeting the PDK/PDH axis with DCA skews the immune system, inhibits vascular inflammation and atherogenesis, and promotes plaque stability features in Apoe−/− mice. These results point toward a promising treatment to combat atherosclerosis.