Characterization of AIM2 DNA-Binding Properties and Filament Formation

High levels of thrombin-activatable fibrinolysis inhibitor (TAFI) are a supposed risk factor for thrombosis. However, results from previous studies are conflicting.We assessed the absolute risk of venous and arterial thromboembolism in subjects with high TAFI levels (> 126 U/dl) versus subjects with normal levels, and the contribution of other concomitant thrombophilic defects. Relatives from four identical cohort studies in families with either deficiencies of antithrombin, protein C or protein S, prothrombin 202 1 OA, high factorVIII levels, or hyperhomocysteinemia were pooled. Probands were excluded. Of 1,940 relatives, 187 had high TAR levels. Annual incidences of venous thromboembolism were 0.23% in relatives with highTAFI levels versus 0.26% in relatives with normal TAFI levels (adjusted relative risk [RR] 0.8; 95% confidence interval [0], 0.5-1.3). For arterial thrombosis these were 0.3 1 % versus 0.23% (adjusted RR 1.4; 95% Cl, 0.9-2.2). High levels of factor VIII, IX and XI were observed more frequently in relatives with high TAR levels. Only high factor VIII levels were associated with an increased risk of venous and arterial thrombosis, independently of TAR levels. None of these concomitant defects showed interaction with high TAR levels. High TAR levels were not associated with an increased risk of venous and arterial thromboembolism in thrombophilic families

Improved cardiovascular risk prediction using targeted plasma proteomics in primary prevention.

AIMS: In the era of personalized medicine, it is of utmost importance to be able to identify subjects at the highest cardiovascular (CV) risk. To date, single biomarkers have failed to markedly improve the estimation of CV risk. Using novel technology, simultaneous assessment of large numbers of biomarkers may hold promise to improve prediction. In the present study, we compared a protein-based risk model with a model using traditional risk factors in predicting CV events in the primary prevention setting of the European Prospective Investigation (EPIC)-Norfolk study, followed by validation in the Progressione della Lesione Intimale Carotidea (PLIC) cohort. METHODS AND RESULTS: Using the proximity extension assay, 368 proteins were measured in a nested case-control sample of 822 individuals from the EPIC-Norfolk prospective cohort study and 702 individuals from the PLIC cohort. Using tree-based ensemble and boosting methods, we constructed a protein-based prediction model, an optimized clinical risk model, and a model combining both. In the derivation cohort (EPIC-Norfolk), we defined a panel of 50 proteins, which outperformed the clinical risk model in the prediction of myocardial infarction [area under the curve (AUC) 0.754 vs. 0.730; P < 0.001] during a median follow-up of 20 years. The clinically more relevant prediction of events occurring within 3 years showed an AUC of 0.732 using the clinical risk model and an AUC of 0.803 for the protein model (P < 0.001). The predictive value of the protein panel was confirmed to be superior to the clinical risk model in the validation cohort (AUC 0.705 vs. 0.609; P < 0.001). CONCLUSION: In a primary prevention setting, a proteome-based model outperforms a model comprising clinical risk factors in predicting the risk of CV events. Validation in a large prospective primary prevention cohort is required to address the value for future clinical implementation in CV prevention

Hepatitis C virus in hemophilia:Health-related quality of life after successful treatment in the sixth Hemophilia in the Netherlands study

INTRODUCTION: Persons with hemophilia and hepatitis C virus (HCV) infection have a lower health‐related quality of life (HRQoL) than those never HCV infected. However, it is unknown whether HRQoL after HCV eradication is comparable to individuals never HCV infected. We aimed to compare HRQoL between HCV‐cured and never chronically HCV‐infected persons with hemophilia. METHODS: All persons with hemophilia in the Netherlands were invited for a nationwide study conducted in 2018–2019. For the current analysis, participants born before 1992 with data on HRQoL and HCV status were included. HCV status was collected from medical records. HRQoL was measured by RAND‐36 questionnaire, with a minimally important difference set at 4.0 points. Multivariable linear regression was used to adjust for age, hemophilia severity, HIV status, and self‐reported joint impairment. RESULTS: In total, 486 persons were eligible; 180 were HCV cured and 306 never chronically HCV infected. Compared with those never HCV infected, HCV‐cured individuals were older (57 vs. 53 years), more often had severe hemophilia (67% vs. 21%), and reported more impaired joints (median 3 vs. 0). Compared with those never HCV infected, adjusted RAND‐36 domain scores of HCV‐cured individuals cured were lower on all RAND‐36 domains except Pain, ranging from a difference of 4.5 (95% CI, −8.8 to −0.3) for Physical functioning to 11.3 (95% CI, −19.4 to −3.1) for Role limitations due to physical problems. CONCLUSION: Despite effective HCV treatment, HRQoL of HCV‐cured persons with hemophilia is still lower than HRQoL of those never chronically HCV‐infected on all RAND‐36 domains. This implies that careful psychosocial follow‐up and support are indicated

Perioperative pharmacokinetic-guided factor VIII concentrate dosing in haemophilia (OPTI-CLOT trial):an open-label, multicentre, randomised, controlled trial

Background Dosing of replacement therapy with factor VIII concentrate in patients with haemophilia A in the perioperative setting is challenging. Underdosing and overdosing of factor VIII concentrate should be avoided to minimise risk of perioperative bleeding and treatment costs. We hypothesised that dosing of factor VIII concentrate on the basis of a patient's pharmacokinetic profile instead of bodyweight, which is standard treatment, would reduce factor VIII consumption and improve the accuracy of attained factor VIII levels. Methods In this open-label, multicentre, randomised, controlled trial (OPTI-CLOT), patients were recruited from nine centres in Rotterdam, Groningen, Utrecht, Nijmegen, The Hague, Leiden, Amsterdam, Eindhoven, and Maastricht in The Netherlands. Eligible patients were aged 12 years or older with severe or moderate haemophilia A (severe haemophilia was defined as factor VIII concentrations of Findings Between May 1, 2014, and March 1, 2020, 98 patients were assessed for eligibility and 66 were enrolled in the trial and randomly assigned to the pharmacokinetic-guided treatment group (34 [52%]) or the standard treatment group (32 [48%]). Median age was 49.1 years (IQR 35.0 to 62.1) and all participants were male. No difference was seen in consumption of factor VIII concentrate during the perioperative period between groups (mean consumption of 365 IU/kg [SD 202] in pharmacokinetic-guided treatment group vs 379 IU/kg [202] in standard treatment group; adjusted difference -6 IU/kg [95% CI -88 to 100]). Postoperative bleeding occurred in six (18%) of 34 patients in the pharmacokinetic-guided treatment group and three (9%) of 32 in the standard treatment group. One grade 4 postoperative bleeding event occurred, which was in one (3%) patient in the standard treatment group. No treatment-related deaths occurred. Interpretation Although perioperative pharmacokinetic-guided dosing is safe, it leads to similar perioperative factor VIII consumption when compared with standard treatment. However, pharmacokinetic-guided dosing showed an improvement in obtaining factor VIII concentrations within the desired perioperative factor VIII range. These findings provide support to further investigation of pharmacokinetic-guided dosing in perioperative haemophilia care. Copyright (C) 2021 Elsevier Ltd. All rights reserved

A CREDENCE Trial Substudy

Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.OBJECTIVES: The study compared the performance for detection and grading of coronary stenoses using artificial intelligence-enabled quantitative coronary computed tomography angiography (AI-QCT) analyses to core lab-interpreted coronary computed tomography angiography (CTA), core lab quantitative coronary angiography (QCA), and invasive fractional flow reserve (FFR). BACKGROUND: Clinical reads of coronary CTA, especially by less experienced readers, may result in overestimation of coronary artery disease stenosis severity compared with expert interpretation. AI-based solutions applied to coronary CTA may overcome these limitations. METHODS: Coronary CTA, FFR, and QCA data from 303 stable patients (64 ± 10 years of age, 71% male) from the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia) trial were retrospectively analyzed using an Food and Drug Administration-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. RESULTS: Disease prevalence was high, with 32.0%, 35.0%, 21.0%, and 13.0% demonstrating ≥50% stenosis in 0, 1, 2, and 3 coronary vessel territories, respectively. Average AI-QCT analysis time was 10.3 ± 2.7 minutes. AI-QCT evaluation demonstrated per-patient sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 94%, 68%, 81%, 90%, and 84%, respectively, for ≥50% stenosis, and of 94%, 82%, 69%, 97%, and 86%, respectively, for detection of ≥70% stenosis. There was high correlation between stenosis detected on AI-QCT evaluation vs QCA on a per-vessel and per-patient basis (intraclass correlation coefficient = 0.73 and 0.73, respectively; P < 0.001 for both). False positive AI-QCT findings were noted in in 62 of 848 (7.3%) vessels (stenosis of ≥70% by AI-QCT and QCA of <70%); however, 41 (66.1%) of these had an FFR of <0.8. CONCLUSIONS: A novel AI-based evaluation of coronary CTA enables rapid and accurate identification and exclusion of high-grade stenosis and with close agreement to blinded, core lab-interpreted quantitative coronary angiography. (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia [CREDENCE]; NCT02173275).proofepub_ahead_of_prin

The effect of scan and patient parameters on the diagnostic performance of AI for detecting coronary stenosis on coronary CT angiography

Publisher Copyright: © 2022 The AuthorsObjectives: To determine whether coronary computed tomography angiography (CCTA) scanning, scan preparation, contrast, and patient based parameters influence the diagnostic performance of an artificial intelligence (AI) based analysis software for identifying coronary lesions with ≥50% stenosis. Background: CCTA is a noninvasive imaging modality that provides diagnostic and prognostic benefit to patients with coronary artery disease (CAD). The use of AI enabled quantitative CCTA (AI-QCT) analysis software enhances our diagnostic and prognostic ability, however, it is currently unclear whether software performance is influenced by CCTA scanning parameters. Methods: CCTA and quantitative coronary CT (QCT) data from 303 stable patients (64 ± 10 years, 71% male) from the derivation arm of the CREDENCE Trial were retrospectively analyzed using an FDA-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. The algorithm's diagnostic performance measures (sensitivity, specificity, and accuracy) for detecting coronary lesions of ≥50% stenosis were determined based on concordance with QCA measurements and subsequently compared across scanning parameters (including scanner vendor, model, single vs dual source, tube voltage, dose length product, gating technique, timing method), scan preparation technique (use of beta blocker, use and dose of nitroglycerin), contrast administration parameters (contrast type, infusion rate, iodine concentration, contrast volume) and patient parameters (heart rate and BMI). Results: Within the patient cohort, 13% demonstrated ≥50% stenosis in 3 vessel territories, 21% in 2 vessel territories, 35% in 1 vessel territory while 32% had 400 mg/ml 95.2%; p = 0.0287) in the context of low injection flow rates. On a per patient basis there were no significant differences in AI diagnostic performance measures across all measured scanner, scan technique, patient preparation, contrast, and individual patient parameters. Conclusion: The diagnostic performance of AI-QCT analysis software for detecting moderate to high grade stenosis are unaffected by commonly used CCTA scanning parameters and across a range of common scanning, scanner, contrast and patient variables. Condensed abstract: An AI-enabled quantitative CCTA (AI-QCT) analysis software has been validated as an effective tool for the identification, quantification and characterization of coronary plaque and stenosis through comparison to blinded expert readers and quantitative coronary angiography. However, it is unclear whether CCTA screening parameters related to scanner parameters, scan technique, contrast volume and rate, radiation dose, or a patient's BMI or heart rate at time of scan affect the software's diagnostic measures for detection of moderate to high grade stenosis. AI performance measures were unaffected across a broad range of commonly encountered scanner, patient preparation, scan technique, intravenous contrast and patient parameters.publishersversionpublishe

Incremental prognostic value of hybrid [15O]H2O positron emission tomography-computed tomography: combining myocardial blood flow, coronary stenosis severity, and high-risk plaque morphology

AimsThis study sought to determine the prognostic value of combined functional testing using positron emission tomography (PET) perfusion imaging and anatomical testing using coronary computed tomography angiography (CCTA)-derived stenosis severity and plaque morphology in patients with suspected coronary artery disease (CAD).Methods and resultsIn this retrospective study, 539 patients referred for hybrid [15O]H2O PET-CT imaging because of suspected CAD were investigated. PET was used to determine myocardial blood flow (MBF), whereas CCTA images were evaluated for obstructive stenoses and high-risk plaque (HRP) morphology. Patients were followed up for the occurrence of all-cause death and non-fatal myocardial infarction (MI). During a median follow-up of 6.8 (interquartile range 4.8–7.8) years, 42 (7.8%) patients experienced events, including 23 (4.3%) deaths, and 19 (3.5%) MIs. Annualized event rates for normal vs. abnormal results of PET MBF, CCTA-derived stenosis, and HRP morphology were 0.6 vs. 2.1%, 0.4 vs. 2.1%, and 0.8 vs. 2.8%, respectively (P ConclusionPET-derived MBF, CCTA-derived stenosis severity, and HRP morphology were univariably associated with death and MI, whereas only stenosis severity and HRP morphology provided independent prognostic value.</div

Validity, reliability, and responsiveness of daily monitoring visual analog scales in MASK‐air®

Background: MASK-air® is an app that supports allergic rhinitis patients in disease control. Users register daily allergy symptoms and their impact on activities using visual analog scales (VASs). We aimed to assess the concurrent validity, reliability, and responsiveness of these daily VASs. Methods: Daily monitoring VAS data were assessed in MASK-air® users with allergic rhinitis. Concurrent validity was assessed by correlating daily VAS values with those of the EuroQol-5 Dimensions (EQ-5D) VAS, the Control of Allergic Rhinitis and Asthma Test (CARAT) score, and the Work Productivity and Activity Impairment Allergic Specific (WPAI-AS) Questionnaire (work and activity impairment scores). Intra-rater reliability was assessed in users providing multiple daily VASs within the same day. Test–retest reliability was tested in clinically stable users, as defined by the EQ-5D VAS, CARAT, or “VAS Work” (i.e., VAS assessing the impact of allergy on work). Responsiveness was determined in users with two consecutive measurements of EQ-5D-VAS or “VAS Work” indicating clinical change. Results: A total of 17,780 MASK-air® users, with 317,176 VAS days, were assessed. Concurrent validity was moderate–high (Spearman correlation coefficient range: 0.437–0.716). Intra-rater reliability intraclass correlation coefficients (ICCs) ranged between 0.870 (VAS assessing global allergy symptoms) and 0.937 (VAS assessing allergy symptoms on sleep). Test–retest reliability ICCs ranged between 0.604 and 0.878—“VAS Work” and “VAS asthma” presented the highest ICCs. Moderate/large responsiveness effect sizes were observed—the sleep VAS was associated with lower responsiveness, while the global allergy symptoms VAS demonstrated higher responsiveness. Conclusion: In MASK-air®, daily monitoring VASs have high intra-rater reliability and moderate–high validity, reliability, and responsiveness, pointing to a reliable measure of symptom loads

Development and validation of combined symptom-medication scores for allergic rhinitis*

Background Validated combined symptom-medication scores (CSMSs) are needed to investigate the effects of allergic rhinitis treatments. This study aimed to use real-life data from the MASK-air(R) app to generate and validate hypothesis- and data-driven CSMSs. Methods We used MASK-air(R) data to assess the concurrent validity, test-retest reliability and responsiveness of one hypothesis-driven CSMS (modified CSMS: mCSMS), one mixed hypothesis- and data-driven score (mixed score), and several data-driven CSMSs. The latter were generated with MASK-air(R) data following cluster analysis and regression models or factor analysis. These CSMSs were compared with scales measuring (i) the impact of rhinitis on work productivity (visual analogue scale [VAS] of work of MASK-air(R), and Work Productivity and Activity Impairment: Allergy Specific [WPAI-AS]), (ii) quality-of-life (EQ-5D VAS) and (iii) control of allergic diseases (Control of Allergic Rhinitis and Asthma Test [CARAT]). Results We assessed 317,176 days of MASK-air(R) use from 17,780 users aged 16-90 years, in 25 countries. The mCSMS and the factor analyses-based CSMSs displayed poorer validity and responsiveness compared to the remaining CSMSs. The latter displayed moderate-to-strong correlations with the tested comparators, high test-retest reliability and moderate-to-large responsiveness. Among data-driven CSMSs, a better performance was observed for cluster analyses-based CSMSs. High accuracy (capacity of discriminating different levels of rhinitis control) was observed for the latter (AUC-ROC = 0.904) and for the mixed CSMS (AUC-ROC = 0.820). Conclusion The mixed CSMS and the cluster-based CSMSs presented medium-high validity, reliability and accuracy, rendering them as candidates for primary endpoints in future rhinitis trials.Peer reviewe

Development and validation of combined symptom‐medication scores for allergic rhinitis*

Background: Validated combined symptom-medication scores (CSMSs) are needed to investigate the effects of allergic rhinitis treatments. This study aimed to use real-life data from the MASK-air® app to generate and validate hypothesis- and data-driven CSMSs. Methods: We used MASK-air® data to assess the concurrent validity, test-retest reliability and responsiveness of one hypothesis-driven CSMS (modified CSMS: mCSMS), one mixed hypothesis- and data-driven score (mixed score), and several data-driven CSMSs. The latter were generated with MASK-air® data following cluster analysis and regression models or factor analysis. These CSMSs were compared with scales measuring (i) the impact of rhinitis on work productivity (visual analogue scale [VAS] of work of MASK-air® , and Work Productivity and Activity Impairment: Allergy Specific [WPAI-AS]), (ii) quality-of-life (EQ-5D VAS) and (iii) control of allergic diseases (Control of Allergic Rhinitis and Asthma Test [CARAT]). Results: We assessed 317,176 days of MASK-air® use from 17,780 users aged 16-90 years, in 25 countries. The mCSMS and the factor analyses-based CSMSs displayed poorer validity and responsiveness compared to the remaining CSMSs. The latter displayed moderate-to-strong correlations with the tested comparators, high test-retest reliability and moderate-to-large responsiveness. Among data-driven CSMSs, a better performance was observed for cluster analyses-based CSMSs. High accuracy (capacity of discriminating different levels of rhinitis control) was observed for the latter (AUC-ROC = 0.904) and for the mixed CSMS (AUC-ROC = 0.820). Conclusion: The mixed CSMS and the cluster-based CSMSs presented medium-high validity, reliability and accuracy, rendering them as candidates for primary endpoints in future rhinitis trials