Gastrointestinal bleeding associated to aortic valve stenosis (Heyde's syndrome): a case series and literature review.

Background: The association among aortic valve stenosis, gastrointestinal bleeding, and anaemia due to arteriovenous malformations, known as Heyde's syndrome (HS), is poorly understood and controversial. Recently, acquired Type 2A von Willebrand syndrome (vWS 2A) was shown to be the most likely aetiological mechanism of anaemia. Case summary: We report two cases of HS in whom the percutaneous replacement of the aortic valve was resolutive for iron deficiency anaemia. Discussion: Iron deficiency anaemia and aortic stenosis are a common association in the elderly, so much that frequently; in such cases, the correction of the valvulopathy is often excluded as pre-operative anaemia is associated with higher morbidity and mortality. From this perspective, the correct diagnosis of HS is crucial to guide the decision to correct valvulopathy, as valvular substitution is resolutive for both anaemic disorders and aortic stenosis.

Chest CT opportunistic biomarkers for phenotyping high-risk COVID-19 patients: a retrospective multicentre study.

OBJECTIVE: To assess the value of opportunistic biomarkers derived from chest CT performed at hospital admission of COVID-19 patients for the phenotypization of high-risk patients. METHODS: In this multicentre retrospective study, 1845 consecutive COVID-19 patients with chest CT performed within 72 h from hospital admission were analysed. Clinical and outcome data were collected by each center 30 and 80 days after hospital admission. Patients with unknown outcomes were excluded. Chest CT was analysed in a single core lab and behind pneumonia CT scores were extracted opportunistic data about atherosclerotic profile (calcium score according to Agatston method), liver steatosis (≤ 40 HU), myosteatosis (paraspinal muscle F < 31.3 HU, M < 37.5 HU), and osteoporosis (D12 bone attenuation < 134 HU). Differences according to treatment and outcome were assessed with ANOVA. Prediction models were obtained using multivariate binary logistic regression and their AUCs were compared with the DeLong test. RESULTS: The final cohort included 1669 patients (age 67.5 [58.5-77.4] yo) mainly men 1105/1669, 66.2%) and with reduced oxygen saturation (92% [88-95%]). Pneumonia severity, high Agatston score, myosteatosis, liver steatosis, and osteoporosis derived from CT were more prevalent in patients with more aggressive treatment, access to ICU, and in-hospital death (always p < 0.05). A multivariable model including clinical and CT variables improved the capability to predict non-critical pneumonia compared to a model including only clinical variables (AUC 0.801 vs 0.789; p = 0.0198) to predict patient death (AUC 0.815 vs 0.800; p = 0.001). CONCLUSION: Opportunistic biomarkers derived from chest CT can improve the characterization of COVID-19 high-risk patients. CLINICAL RELEVANCE STATEMENT: In COVID-19 patients, opportunistic biomarkers of cardiometabolic risk extracted from chest CT improve patient risk stratification. KEY POINTS: • In COVID-19 patients, several information about patient comorbidities can be quantitatively extracted from chest CT, resulting associated with the severity of oxygen treatment, access to ICU, and death. • A prediction model based on multiparametric opportunistic biomarkers derived from chest CT resulted superior to a model including only clinical variables in a large cohort of 1669 patients suffering from SARS- CoV2 infection. • Opportunistic biomarkers of cardiometabolic comorbidities derived from chest CT may improve COVID-19 patients' risk stratification also in absence of detailed clinical data and laboratory tests identifying subclinical and previously unknown conditions.

AI-SCoRE (artificial intelligence-SARS CoV2 risk evaluation): a fast, objective and fully automated platform to predict the outcome in COVID-19 patients.

PURPOSE: To develop and validate an effective and user-friendly AI platform based on a few unbiased clinical variables integrated with advanced CT automatic analysis for COVID-19 patients' risk stratification. MATERIAL AND METHODS: In total, 1575 consecutive COVID-19 adults admitted to 16 hospitals during wave 1 (February 16-April 29, 2020), submitted to chest CT within 72 h from admission, were retrospectively enrolled. In total, 107 variables were initially collected; 64 extracted from CT. The outcome was survival. A rigorous AI model selection framework was adopted for models selection and automatic CT data extraction. Model performances were compared in terms of AUC. A web-mobile interface was developed using Microsoft PowerApps environment. The platform was externally validated on 213 COVID-19 adults prospectively enrolled during wave 2 (October 14-December 31, 2020). RESULTS: The final cohort included 1125 patients (292 non-survivors, 26%) and 24 variables. Logistic showed the best performance on the complete set of variables (AUC = 0.839 ± 0.009) as in models including a limited set of 13 and 5 variables (AUC = 0.840 ± 0.0093 and AUC = 0.834 ± 0.007). For non-inferior performance, the 5 variables model (age, sex, saturation, well-aerated lung parenchyma and cardiothoracic vascular calcium) was selected as the final model and the extraction of CT-derived parameters was fully automatized. The fully automatic model showed AUC = 0.842 (95% CI: 0.816-0.867) on wave 1 and was used to build a 0-100 scale risk score (AI-SCoRE). The predictive performance was confirmed on wave 2 (AUC 0.808; 95% CI: 0.7402-0.8766). CONCLUSIONS: AI-SCoRE is an effective and reliable platform for automatic risk stratification of COVID-19 patients based on a few unbiased clinical data and CT automatic analysis.

Impact of clinical and subclinical coronary artery disease as assessed by coronary artery calcium in COVID-19.

BACKGROUND AND AIMS: The potential impact of coronary atherosclerosis, as detected by coronary artery calcium, on clinical outcomes in COVID-19 patients remains unsettled. We aimed to evaluate the prognostic impact of clinical and subclinical coronary artery disease (CAD), as assessed by coronary artery calcium score (CAC), in a large, unselected population of hospitalized COVID-19 patients undergoing non-gated chest computed tomography (CT) for clinical practice. METHODS: SARS-CoV 2 positive patients from the multicenter (16 Italian hospitals), retrospective observational SCORE COVID-19 (calcium score for COVID-19 Risk Evaluation) registry were stratified in three groups: (a) "clinical CAD" (prior revascularization history), (b) "subclinical CAD" (CAC >0), (c) "No CAD" (CAC = 0). Primary endpoint was in-hospital mortality and the secondary endpoint was a composite of myocardial infarction and cerebrovascular accident (MI/CVA). RESULTS: Amongst 1625 patients (male 67.2%, median age 69 [interquartile range 58-77] years), 31%, 57.8% and 11.1% had no, subclinical and clinical CAD, respectively. Increasing rates of in-hospital mortality (11.3% vs. 27.3% vs. 39.8%, p < 0.001) and MI/CVA events (2.3% vs. 3.8% vs. 11.9%, p < 0.001) were observed for patients with no CAD vs. subclinical CAD vs clinical CAD, respectively. The association with in-hospital mortality was independent of in-study outcome predictors (age, peripheral artery disease, active cancer, hemoglobin, C-reactive protein, LDH, aerated lung volume): subclinical CAD vs. No CAD: adjusted hazard ratio (adj-HR) 2.86 (95% confidence interval [CI] 1.14-7.17, p=0.025); clinical CAD vs. No CAD: adj-HR 3.74 (95% CI 1.21-11.60, p=0.022). Among patients with subclinical CAD, increasing CAC burden was associated with higher rates of in-hospital mortality (20.5% vs. 27.9% vs. 38.7% for patients with CAC score thresholds≤100, 101-400 and > 400, respectively, p < 0.001). The adj-HR per 50 points increase in CAC score 1.007 (95%CI 1.001-1.013, p=0.016). Cardiovascular risk factors were not independent predictors of in-hospital mortality when CAD presence and extent were taken into account. CONCLUSIONS: The presence and extent of CAD are associated with in-hospital mortality and MI/CVA among hospitalized patients with COVID-19 disease and they appear to be a better prognostic gauge as compared to a clinical cardiovascular risk assessment.

Coronary and total thoracic calcium scores predict mortality and provides pathophysiologic insights in COVID-19 patients.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has spread worldwide determining dramatic impacts on healthcare systems. Early identification of high-risk parameters is required in order to provide the best therapeutic approach. Coronary, thoracic aorta and aortic valve calcium can be measured from a non-gated chest computer tomography (CT) and are validated predictors of cardiovascular events and all-cause mortality. However, their prognostic role in acute systemic inflammatory diseases, such as COVID-19, has not been investigated. OBJECTIVES: The aim was to evaluate the association of coronary artery calcium and total thoracic calcium on in-hospital mortality in COVID-19 patients. METHODS: 1093 consecutive patients from 16 Italian hospitals with a positive swab for COVID-19 and an admission chest CT for pneumonia severity assessment were included. At CT, coronary, aortic valve and thoracic aorta calcium were qualitatively and quantitatively evaluated separately and combined together (total thoracic calcium) by a central Core-lab blinded to patients' outcomes. RESULTS: Non-survivors compared to survivors had higher coronary artery [Agatston (467.76 â€‹± â€‹570.92 vs 206.80 â€‹± â€‹424.13 â€‹mm2, p â€‹< â€‹0.001); Volume (487.79 â€‹± â€‹565.34 vs 207.77 â€‹± â€‹406.81, p â€‹< â€‹0.001)], aortic valve [Volume (322.45 â€‹± â€‹390.90 vs 98.27 â€‹± â€‹250.74 mm2, p â€‹< â€‹0.001; Agatston 337.38 â€‹± â€‹414.97 vs 111.70 â€‹± â€‹282.15, p â€‹< â€‹0.001)] and thoracic aorta [Volume (3786.71 â€‹± â€‹4225.57 vs 1487.63 â€‹± â€‹2973.19 mm2, p â€‹< â€‹0.001); Agatston (4688.82 â€‹± â€‹5363.72 vs 1834.90 â€‹± â€‹3761.25, p â€‹< â€‹0.001)] calcium values. Coronary artery calcium (HR 1.308; 95% CI, 1.046-1.637, p â€‹= â€‹0.019) and total thoracic calcium (HR 1.975; 95% CI, 1.200-3.251, p â€‹= â€‹0.007) resulted to be independent predictors of in-hospital mortality. CONCLUSION: Coronary, aortic valve and thoracic aortic calcium assessment on admission non-gated CT permits to stratify the COVID-19 patients in-hospital mortality risk.

Outcomes of idiopathic chronic large pericardial effusion.

OBJECTIVE: Aim of this paper is to evaluate the outcomes of 'idiopathic' chronic large pericardial effusions without initial evidence of pericarditis. METHODS: All consecutive cases of idiopathic chronic large pericardial effusions evaluated from 2000 to 2015 in three Italian tertiary referral centres for pericardial diseases were enrolled in a prospective cohort study. The term 'idiopathic' was applied to cases that performed a complete diagnostic evaluation to exclude a specific aetiology. A clinical and echocardiographic follow-up was performed every 3-6 months. RESULTS: 100 patients were included (mean age 61.3±14.6 years, 54 females, 44 patients were asymptomatic according to clinical evaluation) with a mean follow-up of 50 months. The baseline median size of the effusion (evaluated as the largest end-diastolic echo-free space) was 25 mm (IQR 8) and decreased to a mean value of 7 mm (IQR 19; p<0.0001) with complete regression in 39 patients at the end of follow-up. There were no new aetiological diagnoses. Adverse events were respectively: cardiac tamponade in 8 patients (8.0%), pericardiocentesis in 30 patients (30.0%), pericardial window in 12 cases (12.0%) and pericardiectomy in 3 patients (3.0%). Recurrence-free survival and complications-free survival was better in patients treated without interventions (log rank p=0.0038). CONCLUSIONS: The evolution of 'idiopathic' chronic large pericardial effusions is usually benign with reduction of the size of the effusion in the majority of cases, and regression in about 40% of cases. The risk of cardiac tamponade is 2.2%/year and recurrence/complications survival was better in patients treated conservatively without interventions.

Hemodynamic comparison between Trifecta and freestyle aortic valve during exercise in patients with small aortic root.

BACKGROUND: Patients with a small aortic annulus, that is ≤ 23 mm, constitute a challenge for the surgeon, because they are at high risk of patient-prosthesis mismatch. Stentless valves provide better hemodynamic performance at rest and during exercise than stented valves, and are advocated in this group of patients. A new-generation stented valve, the Trifecta (St. Jude), has recently become available with improved hemodynamics. The aim of this study was to compare the hemodynamic performance of Freestyle (Medtronic) and Trifecta at rest and during exercise in patients with a small aortic annulus. METHODS: From September 2012 to September 2014, 22 patients with a native aortic annulus ≤ 23 mm underwent ergometric stress testing one year after aortic valve replacement with either a Trifecta (12 patients) or a Freestyle (10 patients) bioprosthesis as part of a randomized study. RESULTS: The mean gradient at rest was 6.0 ± 2.3 mmHg for Trifecta and 4.3 ± 3.5 for Freestyle (p = 0.213). The mean gradient at peak of exercise was 9.7 ± 3.4 mmHg for Trifecta and 7.4 ± 5 mmHg for Freestyle (p = 0.243). No significant differences were found between the two prostheses regarding other hemodynamic parameters: effective orifice area, velocity index, and performance indexes. CONCLUSION: Both the stented Trifecta and stentless Freestyle prostheses provide excellent hemodynamic results during physical stress in patients with a small aortic annulus. Our study confirms that Trifecta implantation results in low gradients at rest and during exercise and that the performance of Trifecta is similar to that of a stentless valve.