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Hereditary transthyretin (ATTRv) amyloidosis is a rare, adult-onset, progressive, multisystemic condition caused by TTR pathogenic variants. Reliable biomarkers are needed to allow early diagnosis and to monitor disease severity and progression. We measured serum concentrations of growth differentiation factor-15 (GDF-15) and uromodulin (Umod) in ATTRv patients to evaluate correlations with standard markers of disease severity (FAP stage and PND score). Blood samples were collected from 16 patients diagnosed with ATTRv amyloidosis and a verified TTR variant and from 26 healthy controls. ATTRv patients were stratified by clinical phenotype (neurologic vs. mixed), genotype (V30M vs. non-V30M), and disease severity. We found significantly higher levels of serum GDF-15 in ATTRv patients compared with controls. Mean serum Umod levels were significantly lower in patients with ATTRv than controls. A positive correlation was found between serum Umod and estimated glomerular filtration rate (eGFR), while an inverse correlation was found with cystatin C levels. Conversely, GDF-15 showed a negative correlation with eGFR, and a direct correlation with cystatin C levels. No correlation was demonstrated between GDF-15 or Umod levels and traditional cardiac biomarkers. The results identify alteration of serum levels of GDF-15 and Umod in ATTRv amyloidosis.

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BACKGROUND: Evidence about early cardiac mechanics abnormalities in patients with mitochondrial diseases (MDs) before overt cardiomyopathy is limited. METHODS: In this prospective study, we performed a comparative analysis of conventional and speckle tracking echocardiographic parameters between patients with genetically identified MDs and no overt cardiomyopathy vs controls matched for age, sex and cardiovascular risk factors. The Newcastle mitochondrial disease adult scale (NMDAS) was calculated, using a threshold of > 21 as indicator of high disease severity. RESULTS: We enrolled 24 MDs patients (50 % males, mean age 47.2 ± 14.3 years), the most prevalent mutation was the MT-TL1 m.3243A>G (37.5 %). In MDs patients all dimensional echocardiographic parameters were similar to controls. Conversely, albeit normal, Tissue Doppler septal systolic (p = 0.002) and early diastolic velocities (p = 0.016) were significantly lower and E/e' ratio was higher (p = 0.032) in MDs. Moreover, LV-GLS was significantly reduced in MDs as compared to their counterparties (20.2 ± 1.6 vs 22.6 ± 1.5, p < 0.001). Similarly, LA reservoir and conduit strain were significantly lower in MDs (31.7 ± 7.0 vs 35.9 ± 6.6, p = 0.038; 19.7 ± 5.6 vs 23.1 ± 6.0, p = 0.049 respectively), while LA contractile strain was similar between the two groups. Lower values of LV-GLS were observed in patients with NMDAS > 21 vs patients with NMDAS ≤ 21 (19.0 ± 1.2 vs 21.0 ± 1.3, p = 0.001). CONCLUSIONS: In patients with MDs and no overt cardiomyopathy Tissue Doppler and speckle tracking analysis unveil worse LV systolic and diastolic function indices as compared to controls. Reduced LV-GLS values were found especially in those with worse disease burden.

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AIMS: Lung ultrasound (LUS) is a sensitive tool to assess pulmonary congestion (PC). Few data are available on LUS-PC evaluation in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve implantation (TAVI). The aim of this study was to assess the prevalence and prognostic impact of LUS-PC in patients with severe AS before and after TAVI. METHODS AND RESULTS: We designed a single-centre prospective study in patients referred for TAVI for severe AS (ClinicalTrials.gov identification number: NCT05024942). All patients underwent echocardiography and LUS (according to a simplified 8-zone scanning protocol) the day before and within 72 h after the procedure. The primary endpoint was the composite of all-cause mortality, hospitalization for heart failure and urgent medical visits for worsening dyspnoea at 12-month follow-up. A total of 127 patients were enrolled (mean age 81.1 ± 5.8 years; 54.3% female). Pre-TAVI LUS-PC was documented in 65 patients (51%). After TAVI, the prevalence of LUS-PC significantly decreased as compared to pre-TAVI evaluation, being documented in only 28 patients (22% vs. 51%, p < 0.001) with a median B-lines score of 4 (interquartile range [IQR] 0-11) versus 11 (IQR 6-19) pre-TAVI (p < 0.001). During a median follow-up of 12 (12-17) months, 25 patients (19.6%) met the composite endpoint. On multivariable Cox regression analysis, pre-TAVI LUS-PC was independently associated with cardiovascular events (hazard ratio 2.764, 95% confidence interval 1.114-6.857; p = 0.028). CONCLUSIONS: Lung ultrasonography reveals a high prevalence of PC in patients with severe AS undergoing TAVI, which is significantly reduced by the procedure. Pre-TAVI PC, measured by LUS, is an independent predictor of 1-year clinical outcome.

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BACKGROUND: Fabry disease (FD) and transthyretin cardiac amyloidosis (TTR CA) are cardiomyopathies with hypertrophic phenotype that share several features, including left atrial (LA) enlargement and dysfunction, but direct comparative data are lacking. Aim of the present study was to perform a comparative analysis of LA remodelling between the two diseases. METHODS AND RESULTS: In this prospective study, a total of 114 patients (31 FD and 83 TTR CA) were included; all of them had left ventricular hypertrophy (LVH), defined as left ventricular (LV) wall thickness ≥ 12 mm. Despite similar degree of LVH, patients with TTR CA showed worse LV systolic and diastolic function. LA maximal volume index was not significantly different between the two groups (p = 0.084), while patients with TTR CA showed larger LA minimal volume index (p = 0.001). Moreover, all phases of LA mechanics were more impaired in the TTR CA group vs FD (reservoir: 6.9[4.2-15.5] vs 19.0[15.5-29.5], p < 0.001). After excluding patients with atrial fibrillation (AF), these differences remained clearly significant. In multivariable regression analyses, LA reservoir strain showed an independent correlation with TTR CA, controlling for demographic characteristics, AF and LV systolic and diastolic performance (p ≤ 0.001), whereas LV global longitudinal strain did not. Finally, among echocardiographic parameters, LA function demonstrated the highest accuracy in discriminating the two diseases. CONCLUSIONS: TTR CA is characterized by a more advanced LA structural and functional remodelling in comparison to patients with FD and similar degree of LVH. The association between TTR CA and LA dysfunction remains consistent after adjustment for potential confounders.

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In this paper, we evaluate the performance and analyze the explainability of machine learning models boosted by feature selection in predicting COVID-19-positive cases from self-reported information. In essence, this work describes a methodology to identify COVID-19 infections that considers the large amount of information collected by the University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS). More precisely, this methodology performs a feature selection stage based on the recursive feature elimination (RFE) method to reduce the number of input variables without compromising detection accuracy. A tree-based supervised machine learning model is then optimized with the selected features to detect COVID-19-active cases. In contrast to previous approaches that use a limited set of selected symptoms, the proposed approach builds the detection engine considering a broad range of features including self-reported symptoms, local community information, vaccination acceptance, and isolation measures, among others. To implement the methodology, three different supervised classifiers were used: random forests (RF), light gradient boosting (LGB), and extreme gradient boosting (XGB). Based on data collected from the UMD-CTIS, we evaluated the detection performance of the methodology for four countries (Brazil, Canada, Japan, and South Africa) and two periods (2020 and 2021). The proposed approach was assessed in terms of various quality metrics: F1-score, sensitivity, specificity, precision, receiver operating characteristic (ROC), and area under the ROC curve (AUC). This work also shows the normalized daily incidence curves obtained by the proposed approach for the four countries. Finally, we perform an explainability analysis using Shapley values and feature importance to determine the relevance of each feature and the corresponding contribution for each country and each country/year.

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As a slowly progressive form of hypertrophic cardiomyopathy (HCM), Anderson-Fabry disease (FD) resembles the phenotype of the most common sarcomeric forms, although significant differences in presentation and long-term progression may help determine the correct diagnosis. A variety of electrocardiographic and imaging features of FD cardiomyopathy have been described at different times in the course of the disease, and considerable discrepancies remain regarding the assessment of disease severity by individual physicians. Therefore, we here propose a practical staging of FD cardiomyopathy, in hopes it may represent the standard for cardiac evaluation and facilitate communication between specialized FD centres and primary care physicians. We identified 4 main stages of FD cardiomyopathy of increasing severity, based on available evidence from clinical and imaging studies: non-hypertrophic, hypertrophic - pre-fibrotic, hypertrophic - fibrotic, and overt dysfunction. Each stage is described and discussed in detail, following the principle that speaking a common language is critical when managing such complex patients in a multi-disciplinary and sometimes multi-centre setting.

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Cardiomyopathies and valvular heart diseases are typically considered distinct diagnostic categories with dedicated guidelines for their management. However, the interplay between these conditions is increasingly being recognized and they frequently coexist, as in the paradigmatic examples of dilated cardiomyopathy and hypertrophic cardiomyopathy, which are often complicated by the occurrence of mitral regurgitation. Moreover, cardiomyopathies and valvular heart diseases can have a shared aetiology because several genetic or acquired diseases can affect both the cardiac valves and the myocardium. In addition, the association between cardiomyopathies and valvular heart diseases has important prognostic and therapeutic implications. Therefore, a better understanding of their shared pathophysiological mechanisms, as well as of the prevalence and predisposing factors to their association, might lead to a different approach in the risk stratification and management of these diseases. In this Review, we discuss the different scenarios in which valvular heart diseases and cardiomyopathies coexist, highlighting the need for an improved classification and clustering of these diseases with potential repercussions in the clinical management and, particularly, personalized therapeutic approaches.

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Interpretability of neural networks (NNs) and their underlying theoretical behavior remain an open field of study even after the great success of their practical applications, particularly with the emergence of deep learning. In this work, NN2Poly is proposed: a theoretical approach to obtain an explicit polynomial model that provides an accurate representation of an already trained fully connected feed-forward artificial NN a multilayer perceptron (MLP). This approach extends a previous idea proposed in the literature, which was limited to single hidden layer networks, to work with arbitrarily deep MLPs in both regression and classification tasks. NN2Poly uses a Taylor expansion on the activation function, at each layer, and then applies several combinatorial properties to calculate the coefficients of the desired polynomials. Discussion is presented on the main computational challenges of this method, and the way to overcome them by imposing certain constraints during the training phase. Finally, simulation experiments as well as applications to real tabular datasets are presented to demonstrate the effectiveness of the proposed method.

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BACKGROUND: There is limited evidence on the risk stratification of cardiovascular outcomes in patients with Fabry disease (FD). OBJECTIVES: This study sought to classify FD patients into disease stages, based on the extent of the cardiac damage evaluated by echocardiography, and to assess their prognostic impact in a multicenter cohort. METHODS: Patients with FD from 5 Italian referral centers were categorized into 4 stages: stage 0, no cardiac involvement; stage 1, left ventricular (LV) hypertrophy (LV maximal wall thickness >12 mm); stage 2, left atrium (LA) enlargement (LA volume index >34 mL/m2); stage 3, ventricular impairment (LV ejection fraction <50% or E/e' ≥15 or TAPSE <17 mm). The study endpoint was the composite of all-cause death, hospitalization for heart failure, new-onset atrial fibrillation, major bradyarrhythmias or tachyarrhythmias, and ischemic stroke. RESULTS: A total of 314 patients were included. Among them, 174 (56%) were classified as stage 0, 41 (13%) as stage 1, 57 (18%) as stage 2 and 42 (13%) as stage 3. A progressive increase in the composite event rate at 8 years was observed with worsening stages of cardiac damage (log-rank P < 0.001). On multivariable Cox regression analysis, the staging was independently associated with the risk of cardiovascular events (HR: 2.086 per 1-stage increase; 95% CI: 1.487-2.927; P < 0.001). Notably, cardiac staging demonstrated a stronger and additive prognostic value, as compared with the degree of LV hypertrophy. CONCLUSIONS: In FD patients, a novel staging classification of cardiac damage, evaluated by echocardiography, is strongly associated with cardiovascular outcomes and may be helpful to refine risk stratification.

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BACKGROUND: In patients undergoing mitral valve surgery, restrictive suture annuloplasty (De Vega) for less-than-severe functional tricuspid regurgitation has been proven to be safe and effective. The aim of this study is to determine whether the adjunct of the plication of the posterior tricuspid leaflet with the same running suture (bicuspidized De Vega or "De Kay") is equally safe and effective. METHODS: Single center, retrospective study on patients submitted to suture repair of the tricuspid valve during mitral valve surgery, with either conventional or De Kay, between January 2014 and December 2020. Comparison was based on degree of residual tricuspid valve regurgitation and right ventricular assessment at discharge. RESULTS: Over the course of the study period, 255 patients undergoing mitral valve surgery had a dilated (>40 mm or >20 mm/m2) tricuspid valve annulus, with less-than-severe tricuspid regurgitation. Conventional De Vega was employed in 166 patients (65.1%) and De Kay in the remaining 89 (34.9%). At discharge the adjunct of postero-septal commissure plication has similar outcomes to the classic De Vega repair. It seems to preserve right ventricular function. CONCLUSIONS: De Kay repair guarantees the same tricuspidal regurgitation reduction as compared with conventional De Vega early after surgery.

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BACKGROUND: During the global pandemic crisis, various detection methods of COVID-19-positive cases based on self-reported information were introduced to provide quick diagnosis tools for effectively planning and managing healthcare resources. These methods typically identify positive cases based on a particular combination of symptoms, and they have been evaluated using different datasets. PURPOSE: This paper presents a comprehensive comparison of various COVID-19 detection methods based on self-reported information using the University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), a large health surveillance platform, which was launched in partnership with Facebook. METHODS: Detection methods were implemented to identify COVID-19-positive cases among UMD-CTIS participants reporting at least one symptom and a recent antigen test result (positive or negative) for six countries and two periods. Multiple detection methods were implemented for three different categories: rule-based approaches, logistic regression techniques, and tree-based machine-learning models. These methods were evaluated using different metrics including F1-score, sensitivity, specificity, and precision. An explainability analysis has also been conducted to compare methods. RESULTS: Fifteen methods were evaluated for six countries and two periods. We identify the best method for each category: rule-based methods (F1-score: 51.48% - 71.11%), logistic regression techniques (F1-score: 39.91% - 71.13%), and tree-based machine learning models (F1-score: 45.07% - 73.72%). According to the explainability analysis, the relevance of the reported symptoms in COVID-19 detection varies between countries and years. However, there are two variables consistently relevant across approaches: stuffy or runny nose, and aches or muscle pain. CONCLUSIONS: Regarding the categories of detection methods, evaluating detection methods using homogeneous data across countries and years provides a solid and consistent comparison. An explainability analysis of a tree-based machine-learning model can assist in identifying infected individuals specifically based on their relevant symptoms. This study is limited by the self-report nature of data, which cannot replace clinical diagnosis.

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The hypertrophic cardiomyopathy phenotype encompasses a heterogeneous spectrum of genetic and acquired diseases characterized by the presence of left ventricular hypertrophy in the absence of abnormal cardiac loading conditions. This "umbrella diagnosis" includes the "classic" hypertrophic cardiomyopathy (HCM), due to sarcomere protein gene mutations, and its phenocopies caused by intra- or extracellular deposits, such as Fabry disease (FD) and cardiac amyloidosis (CA). All these conditions share a wide phenotypic variability which results from the combination of genetic and environmental factors and whose pathogenic mediators are poorly understood so far. Accumulating evidence suggests that inflammation plays a critical role in a broad spectrum of cardiovascular conditions, including cardiomyopathies. Indeed, inflammation can trigger molecular pathways which contribute to cardiomyocyte hypertrophy and dysfunction, extracellular matrix accumulation, and microvascular dysfunction. Growing evidence suggests that systemic inflammation is a possible key pathophysiologic process potentially involved in the pathogenesis of cardiac disease progression, influencing the severity of the phenotype and clinical outcome, including heart failure. In this review, we summarize current knowledge regarding the prevalence, clinical significance, and potential therapeutic implications of inflammation in HCM and two of its most important phenocopies, FD and CA.

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AIMS: The aim of our study is to assess the ability of left atrial (LA) strain values to improve left ventricular and diastolic pressure (LVEDP) non-invasive estimation as compared with traditional echocardiographic indexes in the acute phase of Takotsubo syndrome (TTS) and to predict adverse in-hospital outcomes in this population. METHODS AND RESULTS: Consecutive TTS patients were prospectively enrolled. Left ventricular and diastolic pressure was measured at the time of catheterization. Transthoracic echocardiography was performed within 48 h from hospital admission. In-hospital complications (acute heart failure, death from any cause, and life-threatening arrhythmias) were collected. A total of 62 patients were analysed (72.2 ± 10.1 years, female 80%) and in-hospital complications occurred in 25 (40.3%). Left ventricular and diastolic pressure mean value was 24.53 ± 7.92 mmHg. Left atrial reservoir and pump strain values presented higher correlation with LVEDP (r -0.859, P < 0.001 and r -0.848, P < 0.001, respectively) in comparison with E/e ' ratio, left atrial volume index (LAVi), and tricuspid regurgitation (TR) peak velocity. In addition, at receiver-operating characteristic curve analysis, LA reservoir and pump strain resulted to be better predictors of LVEDP above the mean of our population [0.909 (95% CI 0.818-0.999, P < 0.001) and 0.889 (95% CI 0.789-0.988, P < 0.001)], respectively] as compared with E/e' ratio, LAVi, and TR peak velocity.Finally, LA reservoir strain resulted to be an independent predictor of worse in-hospital outcomes, together with LVEDP and left ventricular ejection fraction (all P < 0.001). CONCLUSION: In our study, lower LA reservoir and pump strain values were better predictors of LVEDP as compared with traditional echocardiographic indexes in the acute phase of TTS syndrome. Moreover, LA reservoir strain was an independent predictor of adverse in-hospital outcomes.

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Symptoms-based detection of SARS-CoV-2 infection is not a substitute for precise diagnostic tests but can provide insight into the likely level of infection in a given population. This study uses symptoms data collected in the Global COVID-19 Trends and Impact Surveys (UMD Global CTIS), and data on variants sequencing from GISAID. This work, conducted in January of 2022 during the emergence of the Omicron variant (subvariant BA.1), aims to improve the quality of infection detection from the available symptoms and to use the resulting estimates of infection levels to assess the changes in vaccine efficacy during a change of dominant variant; from the Delta dominant to the Omicron dominant period. Our approach produced a new symptoms-based classifier, Random Forest, that was compared to a ground-truth subset of cases with known diagnostic test status. This classifier was compared with other competing classifiers and shown to exhibit an increased performance with respect to the ground-truth data. Using the Random Forest classifier, and knowing the vaccination status of the subjects, we then proceeded to analyse the evolution of vaccine efficacy towards infection during different periods, geographies and dominant variants. In South Africa, where the first significant wave of Omicron occurred, a significant reduction of vaccine efficacy is observed from August-September 2021 to December 2021. For instance, the efficacy drops from 0.81 to 0.30 for those vaccinated with 2 doses (of Pfizer/BioNTech), and from 0.51 to 0.09 for those vaccinated with one dose (of Pfizer/BioNTech or Johnson & Johnson). We also extended the study to other countries in which Omicron has been detected, comparing the situation in October 2021 (before Omicron) with that of December 2021. While the reduction measured is smaller than in South Africa, we still found, for instance, an average drop in vaccine efficacy from 0.53 to 0.45 among those vaccinated with two doses. Moreover, we found a significant negative (Pearson) correlation of around - 0.6 between the measured prevalence of Omicron in several countries and the vaccine efficacy in those same countries. This prediction, in January of 2022, of the decreased vaccine efficacy towards Omicron is in line with the subsequent increase of Omicron infections in the first half of 2022.

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