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Highlights: [•] The Al content is related with structural relaxation and damping capability. [•] Dynamic modulus is insensitive to the frequency especially for storage modulus. [•] Several internal-friction peaks are observed in the Al-free or Al-lean alloys. [•] The damping behavior is proposed to be strongly relied on the level of ordering. [Copyright &y& Elsevier]

Abstract: Titania film is coated on plasma nitrided 316L stainless steel by sol-gel method. Crystallization of titania as well as N loss and formation of Fe2O3 occurs during the annealing heat treatment. The titania film has short cracks within the grooves of plasma etched grain boundaries. With the increase of annealing temperature and duration, surface hardness of the samples is increased, but the toughness is decreased due to oxidization of the surface layer. The coating sample heat treated at 350 °C for 10 min and 450 °C for 10 min has better corrosion resistance than the nitrided stainless steel tested by the potentiodynamic polarization in 0.9% NaCl solution. Water contact angle of the titania film on the rough nitrided steel substrate decreases with UV irradiation treatment, reaching 17° after 3 h treatment. [Copyright &y& Elsevier]

Background: Global collaboration in cardio-oncology is needed to understand the prevalence of cancer therapy-related cardiovascular toxicity in different risk groups, practice settings, and geographic locations. There are limited data on the socioeconomic and racial/ethnic disparities that may impact access to care and outcomes. To address these gaps, we established the Global Cardio-Oncology Registry, a multinational, multicenter prospective registry., Methods: We assembled cardiologists and oncologists from academic and community settings to collaborate in the first Global Cardio-Oncology Registry. Subsequently, a survey for site resources, demographics, and intention to participate was conducted. We designed an online data platform to facilitate this global initiative., Results: A total of 119 sites responded to an online questionnaire on their practices and main goals of the registry: 49 US sites from 23 states and 70 international sites from 5 continents indicated a willingness to participate in the Global Cardio-Oncology Registry. Sites were more commonly led by cardiologists (85/119; 72%) and were more often university/teaching (81/119; 68%) than community based (38/119; 32%). The average number of cardio-oncology patients treated per month was 80 per site. The top 3 Global Cardio-Oncology Registry priorities in cardio-oncology care were breast cancer, hematologic malignancies, and patients treated with immune checkpoint inhibitors. Executive and scientific committees and specific committees were established. A pilot phase for breast cancer using Research Electronic Data Capture Cloud platform recently started patient enrollment., Conclusions: We present the structure for a global collaboration. Information derived from the Global Cardio-Oncology Registry will help understand the risk factors impacting cancer therapy-related cardiovascular toxicity in different geographic locations and therefore contribute to reduce access gaps in cardio-oncology care. Risk calculators will be prospectively derived and validated., Competing Interests: Disclosures Dr Teske has received speaker fees from Philips and Abbott; consulting from Nordic Pharma. Dr Neilan reports consulting from BMS, Abbvie, Sanofi, Genentech, Roche, and C4-Therapeutics; grant funding from BMS and AZ. Dr López-Fernández has received speaker fees from Philips, Janssen, and Incyte. Dr Szmit has received speaker fees from Amgen, Angelini, Astra Zeneca, Bayer, Bristol-Myers Squibb, Gilead, and Pfizer. Dr Guha is supported by American Heart Association-Strategically Focused Research Network Grant in Disparities in Cardio-Oncology (847740 and 863620). Dr Iakobishvili has received speaker fees from AstraZeneca, Boehringer Ingelheim, Novartis, Pfizer, Novo-Nordisk, and Bayer. Dr Sverdlov is supported by the National Heart Foundation of Australia Future Leader Fellowship (Award ID 106025) and reports research grants from the Medical Research Future Fund (Australia), NSW Health (Australia), Cancer Institute NSW (Australia), Hunter Medical Research Institute (Australia), Biotronik, RACE Oncology, Bristol Myer Squibb, Roche Diagnostics, and Vifor; and personal speaker fees from Novartis, Bayer, Bristol Myer Squibb, AstraZeneca, and Boehringer Ingelheim. The other authors report no conflicts.

Background: Stroke is a leading cause of death and disability worldwide. Atrial fibrillation (AF) is a common cause of stroke but may not be detectable at the time of stroke. We hypothesized that an AF polygenic risk score (PRS) can discriminate between cardioembolic stroke and noncardioembolic strokes., Methods: We evaluated AF and stroke risk in 26 145 individuals of European descent from the Stroke Genetics Network case-control study. AF genetic risk was estimated using 3 recently developed PRS methods (LDpred-funct-inf, sBayesR, and PRS-CS) and 2 previously validated PRSs. We performed logistic regression of each AF PRS on AF status and separately cardioembolic stroke, adjusting for clinical risk score (CRS), imputation group, and principal components. We calculated model discrimination of AF and cardioembolic stroke using the concordance statistic (c-statistic) and compared c-statistics using 2000-iteration bootstrapping. We also assessed reclassification of cardioembolic stroke with the addition of PRS to either CRS or a modified CHA 2 DS 2 -VASc score alone., Results: Each AF PRS was significantly associated with AF and with cardioembolic stroke after adjustment for CRS. Addition of each AF PRS significantly improved discrimination as compared with CRS alone ( P <0.01). When combined with the CRS, both PRS-CS and LDpred scores discriminated both AF and cardioembolic stroke (c-statistic 0.84 for AF; 0.74 for cardioembolic stroke) better than 3 other PRS scores ( P <0.01). Using PRS-CS PRS and CRS in combination resulted in more appropriate reclassification of stroke events as compared with CRS alone (event reclassification [net reclassification indices] + =14% [95% CI, 10%-18%]; nonevent reclassification [net reclassification indices] - =17% [95% CI, 15%-0.19%]) or the modified CHA 2 DS 2 -VASc score (net reclassification indices + =11% [95% CI, 7%-15%]; net reclassification indices - =14% [95% CI, 12%-16%]) alone., Conclusions: Addition of polygenic risk of AF to clinical risk factors modestly improves the discrimination of cardioembolic from noncardioembolic strokes, as well as reclassification of stroke subtype. Polygenic risk of AF may be a useful biomarker for identifying strokes caused by AF., Competing Interests: Disclosures Dr Xu has received sponsored research support from American Heart Association (AHA) and National Institutes of Health (NIH), and he reports a patent issued for Methods for diagnosing ischemia by detecting expression levels of genes. Dr Lunetta has received sponsored research support from NIH. Dr Anderson has received sponsored research support from AHA, Bayer AG, Massachusetts General Hospital, and NIH. Dr Ellinor has received sponsored research support from the NIH, AHA, European Union, Bayer AG, IBM Health, Bristol Myers Squibb, and Pfizer, and he has served on advisory boards or consulted for Bayer AG, MyoKardia, and Novartis. Dr Lubitz is a full-time employee of Novartis Institutes of BioMedical Research as of July 18, 2022. Dr Lubitz received research support from the NIH, AHA, Bayer AG, Bristol Myers Squibb, Pfizer, Boehringer Ingelheim, Fitbit, Medtronic, Premier, and IBM, and has consulted for Bristol Myers Squibb, Pfizer, Blackstone Life Sciences, and Invitae.

Background: Preexisting cardiovascular disease (CVD) is perceived as a risk factor for poor outcomes in patients with COVID-19. We sought to determine whether CVD is associated with in-hospital death and cardiovascular events in critically ill patients with COVID-19., Methods: This study used data from a multicenter cohort of adults with laboratory-confirmed COVID-19 admitted to intensive care units at 68 centers across the United States from March 1 to July 1, 2020. The primary exposure was CVD, defined as preexisting coronary artery disease, congestive heart failure, or atrial fibrillation/flutter. Myocardial injury on intensive care unit admission defined as a troponin I or T level above the 99th percentile upper reference limit of normal was a secondary exposure. The primary outcome was 28-day in-hospital mortality. Secondary outcomes included cardiovascular events (cardiac arrest, new-onset arrhythmias, new-onset heart failure, myocarditis, pericarditis, or stroke) within 14 days., Results: Among 5133 patients (3231 male [62.9%]; mean age 61 years [SD, 15]), 1174 (22.9%) had preexisting CVD. A total of 1178 (34.6%) died, and 920 (17.9%) had a cardiovascular event. After adjusting for age, sex, race, body mass index, history of smoking, and comorbidities, preexisting CVD was associated with a 1.15 (95% CI, 0.98-1.34) higher odds of death. No independent association was observed between preexisting CVD and cardiovascular events. Myocardial injury on intensive care unit admission was associated with higher odds of death (adjusted odds ratio, 1.93 [95% CI, 1.61-2.31]) and cardiovascular events (adjusted odds ratio, 1.82 [95% CI, 1.47-2.24]), regardless of the presence of CVD., Conclusions: CVD risk factors, rather than CVD itself, were the major contributors to outcomes in critically ill patients with COVID-19. The occurrence of myocardial injury, regardless of CVD, and its association with outcomes suggests it is likely due to multiorgan injury related to acute inflammation rather than exacerbation of preexisting CVD., Registration: NCT04343898; https://clinicaltrials.gov/ct2/show/NCT04343898.

Background: Novel targeted treatments increase the need for prompt hypertrophic cardiomyopathy (HCM) detection. However, its low prevalence (0.5%) and resemblance to common diseases present challenges that may benefit from automated machine learning-based approaches. We aimed to develop machine learning models to detect HCM and to differentiate it from other cardiac conditions using ECGs and echocardiograms, with robust generalizability across multiple cohorts., Methods: Single-institution HCM ECG models were trained and validated on external data. Multi-institution models for ECG and echocardiogram were trained on data from 3 academic medical centers in the United States and Japan using a federated learning approach, which enables training on distributed data without data sharing. Models were validated on held-out test sets for each institution and from a fourth academic medical center and were further evaluated for discrimination of HCM from aortic stenosis, hypertension, and cardiac amyloidosis. Last, automated detection was compared with manual interpretation by 3 cardiologists on a data set with a realistic HCM prevalence., Results: We identified 74 376 ECGs for 56 129 patients and 8392 echocardiograms for 6825 patients at the 4 academic medical centers. Although ECG models trained on data from each institution displayed excellent discrimination of HCM on internal test data (C statistics, 0.88-0.93), the generalizability was limited, most notably for a model trained in Japan and tested in the United States (C statistic, 0.79-0.82). When trained in a federated manner, discrimination of HCM was excellent across all institutions (C statistics, 0.90-0.96 and 0.90-0.96 for ECG and echocardiogram model, respectively), including for phenotypic subgroups. The models further discriminated HCM from hypertension, aortic stenosis, and cardiac amyloidosis (C statistics, 0.84, 0.83, and 0.88, respectively, for ECG and 0.93, 0.94, 0.85, respectively, for echocardiogram). Analysis of electrocardiography-echocardiography paired data from 11 823 patients from an external institution indicated a higher sensitivity of automated HCM detection at a given positive predictive value compared with cardiologists (0.98 versus 0.81 at a positive predictive value of 0.01 for ECG and 0.78 versus 0.59 at a positive predictive value of 0.24 for echocardiogram)., Conclusions: Federated learning improved the generalizability of models that use ECGs and echocardiograms to detect and differentiate HCM from other causes of hypertrophy compared with training within a single institution.

Gene therapy with LentiGlobin for sickle cell disease (bb1111, lovotibeglogene autotemcel) consists of autologous transplantation of a patient's hematopoietic stem cells transduced with the BB305 lentiviral vector that encodes the β A-T87Q -globin gene. Acute myeloid leukemia developed in a woman approximately 5.5 years after she had received LentiGlobin for sickle cell disease as part of the initial cohort (Group A) of the HGB-206 study. An analysis of peripheral-blood samples revealed that blast cells contained a BB305 lentiviral vector insertion site. The results of an investigation of causality indicated that the leukemia was unlikely to be related to vector insertion, given the location of the insertion site, the very low transgene expression in blast cells, and the lack of an effect on expression of surrounding genes. Several somatic mutations predisposing to acute myeloid leukemia were present after diagnosis, which suggests that patients with sickle cell disease are at increased risk for hematologic malignant conditions after transplantation, most likely because of a combination of risks associated with underlying sickle cell disease, transplantation procedure, and inadequate disease control after treatment. (Funded by Bluebird Bio.)., (Copyright © 2021 Massachusetts Medical Society.)

Background and Purpose- Digital subtraction angiography has been used as the gold standard to confirm successful aneurysmal obliteration after aneurysm clipping procedures using titanium or cobalt alloy clips. Computed tomographic angiography is a newer, less invasive imaging technique also used to confirm successful aneurysmal obliteration; however, its use compared with digital subtraction angiography remains controversial. Methods- A comprehensive literature search was conducted on Pubmed, EMBASE, and Cochrane databases through November 6, 2017, for studies that evaluated postclipping aneurysm obliteration with both computed tomographic angiography and digital subtraction angiography. Pooled sensitivity, specificity, positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were calculated using the bivariate random-effects model. Results- Out of 6916 studies, 13 studies met inclusion criteria for this meta-analysis. A total of 510 patients with 613 aneurysms were included. Compared with digital subtraction angiography, which detected 87 residual aneurysms, computed tomographic angiography detected 58 resulting in a pooled sensitivity of 69% (95% CI, 54%-81%) and a pooled specificity of 99% (95% CI, 97%-99%). This corresponded to LR+ of 55.5 (95% CI, 23.6-130.9) and LR- of 0.31 (95% CI, 0.20-0.48). Univariate meta-regression revealed that the pooled sensitivity was worse in prospective designs ( P interaction <0.05), and the pooled specificity was better in higher-quality studies and for postoperative aneurysm diameters of <2 mm ( P interaction <0.001 for both). Conclusions- This meta-analysis revealed that computed tomographic angiography had a favorable LR+ but not a favorable LR-. Thus, this imaging modality may be applicable to rule in, but not rule out, residual aneurysms after clipping.

Background: Interpretation of pediatric ECGs is limited by lack of accurate sex- and race-specific normal reference values obtained with modern technology for all ages. We sought to obtain contemporary digital ECG measurements in healthy children from North America, to evaluate the effects of sex and race, and to compare our results to commonly used published datasets., Methods: Digital ECGs (12-lead) were retrospectively collected for children ≤18 years old with normal echocardiograms at 19 centers in the Pediatric Heart Network. Patients were classified into 36 groups: 6 age, 2 sex, and 3 race (white, black, and other/mixed) categories. Standard intervals and amplitudes were measured; mean±SD and 2nd/98th percentiles were determined by age group, sex, and race. For each parameter, multivariable analysis, stratified by age, was conducted using sex and race as predictors. Parameters were compared with 2 large pediatric ECG data sets., Results: Among ECGs from 2400 children, significant differences were found by sex and race categories. The corrected QT interval in lead II was greater for girls compared with boys for age groups ≥3 years ( P ≤0.03) and for whites compared with blacks for age groups ≥12 years ( P <0.05). The R wave amplitude in V6 was greater for boys compared with girls for age groups ≥12 years ( P <0.001), for blacks compared with white or other race categories for age groups ≥3 years ( P ≤0.006), and greater compared with a commonly used public data set for age groups ≥12 years ( P <0.0001)., Conclusions: In this large, diverse cohort of healthy children, most ECG intervals and amplitudes varied by sex and race. These differences have important implications for interpreting pediatric ECGs in the modern era when used for diagnosis or screening, including thresholds for left ventricular hypertrophy., (© 2018 American Heart Association, Inc.)

Background: Although metabolomic profiling offers promise for the prediction of coronary heart disease (CHD), and metabolic risk factors are more strongly associated with CHD in women than men, limited data are available for women., Methods: We applied a liquid chromatography-tandem mass spectrometry metabolomics platform to measure 371 metabolites in a discovery set of postmenopausal women (472 incident CHD cases, 472 controls) with validation in an independent set of postmenopausal women (312 incident CHD cases, 315 controls)., Results: Eight metabolites, primarily oxidized lipids, were significantly dysregulated in cases after the adjustment for matching and CHD risk factors in both the discovery and validation data sets. One oxidized phospholipid, C34:2 hydroxy-phosphatidylcholine, remained associated with CHD after further adjustment for other validated metabolites. Subjects with C34:2 hydroxy-phosphatidylcholine levels in the highest quartile had a 4.7-fold increase in CHD odds in comparison with the lowest quartile; C34:2 hydroxy-phosphatidylcholine also significantly improved the area under the curve ( P <0.01) for CHD. The C34:2 hydroxy-phosphatidylcholine findings were replicated in a third replication data set of 980 men and women (230 cardiovascular events) with a stronger association observed in women., Conclusions: These data replicate known metabolite predictors, identify novel markers, and support the relationship between lipid oxidation and subsequent CHD., (© 2018 American Heart Association, Inc.)

Background: Published nomograms of pediatric echocardiographic measurements are limited by insufficient sample size to assess the effects of age, sex, race, and ethnicity. Variable methodologies have resulted in a wide range of Z scores for a single measurement. This multicenter study sought to determine Z scores for common measurements adjusted for body surface area (BSA) and stratified by age, sex, race, and ethnicity., Methods and Results: Data collected from healthy nonobese children ≤18 years of age at 19 centers with a normal echocardiogram included age, sex, race, ethnicity, height, weight, echocardiographic images, and measurements performed at the Core Laboratory. Z score models involved indexed parameters (X/BSA α ) that were normally distributed without residual dependence on BSA. The models were tested for the effects of age, sex, race, and ethnicity. Raw measurements from models with and without these effects were compared, and <5% difference was considered clinically insignificant because interobserver variability for echocardiographic measurements are reported as ≥5% difference. Of the 3566 subjects, 90% had measurable images. Appropriate BSA transformations (BSA α ) were selected for each measurement. Multivariable regression revealed statistically significant effects by age, sex, race, and ethnicity for all outcomes, but all effects were clinically insignificant based on comparisons of models with and without the effects, resulting in Z scores independent of age, sex, race, and ethnicity for each measurement., Conclusions: Echocardiographic Z scores based on BSA were derived from a large, diverse, and healthy North American population. Age, sex, race, and ethnicity have small effects on the Z scores that are statistically significant but not clinically important., (© 2017 American Heart Association, Inc.)