Endocrine system dysfunction and chronic heart failure: a clinical perspective

Chronic heart failure (CHF) leads to an excess of urgent ambulatory visits, recurrent hospital admissions, morbidity, and mortality regardless of medical and non-medical management of the disease. This excess of risk may be attributable, at least in part, to comorbid conditions influencing the development and progression of CHF. In this perspective, the authors examined and described the most common endocrine disorders observed in patients with CHF, particularly in individuals with reduced ejection fraction, aiming to qualify the risks, quantify the epidemiological burden and discuss about the potential role of endocrine treatment. Thyroid dysfunction is commonly observed in patients with CHF, and sometimes it could be the consequence of certain medications (e.g., amiodarone). Male and female hypogonadism may also coexist in this clinical context, contributing to deteriorating the prognosis of these patients. Furthermore, growth hormone deficiency may affect the development of adult myocardium and predispose to CHF. Limited recommendation suggests to screen endocrine disorders in CHF patients, but it could be interesting to evaluate possible endocrine dysfunction in this setting, especially when a high suspicion coexists. Data referring to long-term safety and effectiveness of endocrine treatments in patients with CHF are limited, and their impact on several “hard” endpoints (such as hospital admission, all-cause, and cardiovascular mortality) are still poorly understood

The first 110,593 COVID-19 patients hospitalised in Lombardy: a regionwide analysis of case characteristics, risk factors and clinical outcomes

Objectives: To describe the monthly distribution of COVID-19 hospitalisations, deaths and case-fatality rates (CFR) in Lombardy (Italy) throughout 2020. Methods: We analysed de-identified hospitalisation data comprising all COVID-19-related admissions from 1 February 2020 to 31 December 2020. The overall survival (OS) from time of first hospitalisation was estimated using the Kaplan-Meier method. We estimated monthly CFRs and performed Cox regression models to measure the effects of potential predictors on OS. Results: Hospitalisation and death peaks occurred in March and November 2020. Patients aged ≥70 years had an up to 180 times higher risk of dying compared to younger patients [70–80: HR 58.10 (39.14–86.22); 80–90: 106.68 (71.01–160.27); ≥90: 180.96 (118.80–275.64)]. Risk of death was higher in patients with one or more comorbidities [1: HR 1.27 (95% CI 1.20–1.35); 2: 1.44 (1.33–1.55); ≥3: 1.73 (1.58–1.90)] and in those with specific conditions (hypertension, diabetes). Conclusion: Our data sheds light on the Italian pandemic scenario, uncovering mechanisms and gaps at regional health system level and, on a larger scale, adding to the body of knowledge needed to inform effective health service planning, delivery, and preparedness in times of crisis

Influence of Heart Rate on Left and Right Ventricular Longitudinal Strain in Patients with Chronic Heart Failure

Over the past years, a number of studies have demonstrated the relevance of strain assessed by two-dimensional speckle tracking echocardiography (STE) in evaluating ventricular function. The aim of this study was to analyze changes in left (LV) and right ventricular (RV) longitudinal strain associated with variations of heart rate (HR) in participants with and without chronic heart failure (CHF). We enrolled 45 patients, 38 of these diagnosed with CHF and carrying an implantable cardioverter defibrillator, and seven patients with pacemakers and without CHF. The frequency of atrial stimulation was increased to 90 beats/min and an echocardiogram was performed at each increase of 10 beats/min. Global LV and RV longitudinal strain (LVGLS and RVGLS, respectively) and RV free wall longitudinal strain (RVfwLS) were calculated at each HR. When analyzed as continuous variables, significant reductions in LVGLS were detected at higher HRs, whereas improvements in both RVGLS and RVfwLS were observed. Patients with a worsening of LVGLS (76% overall) were more likely to present lower baseline LV function. Only a few patients (18% for RVGLS and 16% for RVfwLS) exhibited HR-related deteriorations of RV strain measures, which was associated with lower levels of baseline RV function and higher pulmonary systolic pressures. Finally, 21 (47%) and 25 (56%) participants responded with improvements in RVGLS and RVfwLS, respectively. Our findings revealed heterogeneous RV and LV responses to increases in HR. These findings might ultimately be used to optimize cardiac functionality in patients diagnosed with CHF

Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples

Predictive models based on radiomics and machine-learning (ML) need large and annotated datasets for training, often difficult to collect. We designed an operative pipeline for model training to exploit data already available to the scientific community. The aim of this work was to explore the capability of radiomic features in predicting tumor histology and stage in patients with non-small cell lung cancer (NSCLC). We analyzed the radiotherapy planning thoracic CT scans of a proprietary sample of 47 subjects (L-RT) and integrated this dataset with a publicly available set of 130 patients from the MAASTRO NSCLC collection (Lung1). We implemented intra- and inter-sample cross-validation strategies (CV) for evaluating the ML predictive model performances with not so large datasets. We carried out two classification tasks: histology classification (3 classes) and overall stage classification (two classes: stage I and II). In the first task, the best performance was obtained by a Random Forest classifier, once the analysis has been restricted to stage I and II tumors of the Lung1 and L-RT merged dataset (AUC = 0.72 ± 0.11). For the overall stage classification, the best results were obtained when training on Lung1 and testing of L-RT dataset (AUC = 0.72 ± 0.04 for Random Forest and AUC = 0.84 ± 0.03 for linear-kernel Support Vector Machine). According to the classification task to be accomplished and to the heterogeneity of the available dataset(s), different CV strategies have to be explored and compared to make a robust assessment of the potential of a predictive model based on radiomics and ML

Unconstrained Hamiltonian formulation of General Relativity with thermo-elastic sources

A new formulation of the Hamiltonian dynamics of the gravitational field interacting with(non-dissipative) thermo-elastic matter is discussed. It is based on a gauge condition which allows us to encode the six degrees of freedom of the ``gravity + matter''-system (two gravitational and four thermo-mechanical ones), together with their conjugate momenta, in the Riemannian metric q_{ij} and its conjugate ADM momentum P^{ij}. These variables are not subject to constraints. We prove that the Hamiltonian of this system is equal to the total matter entropy. It generates uniquely the dynamics once expressed as a function of the canonical variables. Any function U obtained in this way must fulfil a system of three, first order, partial differential equations of the Hamilton-Jacobi type in the variables (q_{ij},P^{ij}). These equations are universal and do not depend upon the properties of the material: its equation of state enters only as a boundary condition. The well posedness of this problem is proved. Finally, we prove that for vanishing matter density, the value of U goes to infinity almost everywhere and remains bounded only on the vacuum constraints. Therefore the constrained, vacuum Hamiltonian (zero on constraints and infinity elsewhere) can be obtained as the limit of a ``deep potential well'' corresponding to non-vanishing matter. This unconstrained description of Hamiltonian General Relativity can be useful in numerical calculations as well as in the canonical approach to Quantum Gravity.Comment: 29 pages, TeX forma

Type 1 plasminogen activator inhibitor as a common risk factor for cancer and ischaemic vascular disease: the EPICOR study

OBJECTIVES: We examined the association of plasminogen activator inhibitor-1 (PAI-1) levels with colorectal cancer, breast cancer, acute coronary syndrome (ACS) and ischaemic stroke. DESIGN: Nested case-cohort study. SETTING: The European Prospective Investigation into Cancer and Nutrition-Italy cohort. PARTICIPANTS: A centre-stratified random sample of 850 participants (286 men, 564 women) was selected as subcohort and compared with 303 colorectal cancers, 617 breast cancers, 688 ACS and 158 ischaemic strokes, in a mean follow-up of 9.11 years. MAIN OUTCOMES AND MEASURES: Primary incident cases of colon cancer, breast cancer, ACS and ischaemic stroke. PAI-1 levels were measured in citrated plasma by ELISA. HR and 95% CI, adjusted by relevant confounders and stratified by centre, were estimated by a Cox regression model using Prentice method. RESULTS: Individuals in the highest compared with the lowest quartile of PAI-1 had significantly increased risk of colorectal cancer (RR=2.28; 95% CI 1.46 to 3.55; P for trend<0.0012), breast cancer (HR=1.70; 95% CI 1.21 to 2.39; p<0.0055), ACS (HR=2.57; 95% CI 1.75 to 3.77; p<0.001) and ischaemic stroke (HR=2.27; 95% CI 1.28 to 4.03; p<0.0017), after adjustment for sex and age. Additional adjustment for disease-specific confounders, insulin or other metabolic variables did not modify the associations. Risk of colon cancer was stronger for men and for whole and distal colon localisation. Risk for breast cancer was stronger in postmenopausal women. CONCLUSIONS: Our data provide the first evidence that elevated levels of PAI-1 are potential risk factors for colorectal and breast cancer and a common pathway for cancer and cardiovascular disease

A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events

Background: Recent evidence highlights the epidemiological value of blood DNA methylation (DNAm) as surrogate biomarker for exposure to risk factors for non-communicable diseases (NCD). DNAm surrogate of exposures predicts diseases and longevity better than self-reported or measured exposures in many cases. Consequently, disease prediction models based on blood DNAm surrogates may outperform current state-of-the-art prediction models. This study aims to develop novel DNAm surrogates for cardiovascular diseases (CVD) risk factors and develop a composite biomarker predictive of CVD risk. We compared the prediction performance of our newly developed risk score with the state-of-the-art DNAm risk scores for cardiovascular diseases, the ‘next-generation’ epigenetic clock DNAmGrimAge, and the prediction model based on traditional risk factors SCORE2. Results: Using data from the EPIC Italy cohort, we derived novel DNAm surrogates for BMI, blood pressure, fasting glucose and insulin, cholesterol, triglycerides, and coagulation biomarkers. We validated them in four independent data sets from Europe and the USA. Further, we derived a DNAmCVDscore predictive of the time-to-CVD event as a combination of several DNAm surrogates. ROC curve analyses show that DNAmCVDscore outperforms previously developed DNAm scores for CVD risk and SCORE2 for short-term CVD risk. Interestingly, the performance of DNAmGrimAge and DNAmCVDscore was comparable (slightly lower for DNAmGrimAge, although the differences were not statistically significant). Conclusions: We described novel DNAm surrogates for CVD risk factors useful for future molecular epidemiology research, and we described a blood DNAm-based composite biomarker, DNAmCVDscore, predictive of short-term cardiovascular events. Our results highlight the usefulness of DNAm surrogate biomarkers of risk factors in epigenetic epidemiology to identify high-risk populations. In addition, we provide further evidence on the effectiveness of prediction models based on DNAm surrogates and discuss methodological aspects for further improvements. Finally, our results encourage testing this approach for other NCD diseases by training and developing DNAm surrogates for disease-specific risk factors and exposures