Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems.

OBJECTIVE: We aimed to evaluate the effectiveness of utilizing artificial intelligence (AI) to quantify the extent of pneumonia from chest CT scans, and to determine its ability to predict clinical deterioration or mortality in patients admitted to the hospital with COVID-19 in comparison to semi-quantitative visual scoring systems. METHODS: A deep-learning algorithm was utilized to quantify the pneumonia burden, while semi-quantitative pneumonia severity scores were estimated through visual means. The primary outcome was clinical deterioration, the composite end point including admission to the intensive care unit, need for invasive mechanical ventilation, or vasopressor therapy, as well as in-hospital death. RESULTS: The final population comprised 743 patients (mean age 65  ±â€¯ 17 years, 55% men), of whom 175 (23.5%) experienced clinical deterioration or death. The area under the receiver operating characteristic curve (AUC) for predicting the primary outcome was significantly higher for AI-assisted quantitative pneumonia burden (0.739, p = 0.021) compared with the visual lobar severity score (0.711, p < 0.001) and visual segmental severity score (0.722, p = 0.042). AI-assisted pneumonia assessment exhibited lower performance when applied for calculation of the lobar severity score (AUC of 0.723, p = 0.021). Time taken for AI-assisted quantification of pneumonia burden was lower (38 ± 10 s) compared to that of visual lobar (328 ± 54 s, p < 0.001) and segmental (698 ± 147 s, p < 0.001) severity scores. CONCLUSION: Utilizing AI-assisted quantification of pneumonia burden from chest CT scans offers a more accurate prediction of clinical deterioration in patients with COVID-19 compared to semi-quantitative severity scores, while requiring only a fraction of the analysis time. ADVANCES IN KNOWLEDGE: Quantitative pneumonia burden assessed using AI demonstrated higher performance for predicting clinical deterioration compared to current semi-quantitative scoring systems. Such an AI system has the potential to be applied for image-based triage of COVID-19 patients in clinical practice.

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.

Computed tomography and nuclear medicine for the assessment of coronary inflammation: clinical applications and perspectives.

There is increasing evidence that in patients with atherosclerotic cardiovascular disease (ASCVD) under optimal medical therapy, a persisting dysregulation of the lipid and glucose metabolism, associated with adipose tissue dysfunction and inflammation, predicts a substantial residual risk of disease progression and cardiovascular events. Despite the inflammatory nature of ASCVD, circulating biomarkers such as high-sensitivity C-reactive protein and interleukins may lack specificity for vascular inflammation. As known, dysfunctional epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) produce pro-inflammatory mediators and promote cellular tissue infiltration triggering further pro-inflammatory mechanisms. The consequent tissue modifications determine the attenuation of PCAT as assessed and measured by coronary computed tomography angiography (CCTA). Recently, relevant studies have demonstrated a correlation between EAT and PCAT and obstructive coronary artery disease, inflammatory plaque status and coronary flow reserve (CFR). In parallel, CFR is well recognized as a marker of coronary vasomotor function that incorporates the haemodynamic effects of epicardial, diffuse and small-vessel disease on myocardial tissue perfusion. An inverse relationship between EAT volume and coronary vascular function and the association of PCAT attenuation and impaired CFR have already been reported. Moreover, many studies demonstrated that 18F-FDG PET is able to detect PCAT inflammation in patients with coronary atherosclerosis. Importantly, the perivascular FAI (fat attenuation index) showed incremental value for the prediction of adverse clinical events beyond traditional risk factors and CCTA indices by providing a quantitative measure of coronary inflammation. As an indicator of increased cardiac mortality, it could guide early targeted primary prevention in a wide spectrum of patients. In this review, we summarize the current evidence regarding the clinical applications and perspectives of EAT and PCAT assessment performed by CCTA and the prognostic information derived by nuclear medicine.

Use of cardiac imaging in chronic coronary syndromes: the EURECA Imaging registry.

BACKGROUND: The prospective, multicentre EURECA registry assessed the use of imaging and adoption of the European Society of Cardiology (ESC) Guidelines (GL) in patients with chronic coronary syndromes (CCS). METHODS: Between May 2019 and March 2020, 5156 patients were recruited in 73 centres from 24 ESC member countries. The adoption of GL recommendations was evaluated according to clinical presentation and pre-test probability (PTP) of obstructive coronary artery disease (CAD). RESULTS: The mean age of the population was 64 ± 11 years, 60% of patients were males, 42% had PTP >15%, 27% had previous CAD, and ejection fraction was <50% in 5%. Exercise ECG was performed in 32% of patients, stress imaging as the first choice in 40%, and computed tomography coronary angiography (CTCA) in 22%. Invasive coronary angiography (ICA) was the first or downstream test in 17% and 11%, respectively. Obstructive CAD was documented in 24% of patients, inducible ischaemia in 19%, and 13% of patients underwent revascularization. In 44% of patients, the overall diagnostic process did not adopt the GL. In these patients, referral to stress imaging (21% vs. 58%; P < 0.001) or CTCA (17% vs. 30%; P < 0.001) was less frequent, while exercise ECG (43% vs. 22%; P < 0.001) and ICA (48% vs. 15%; P < 0.001) were more frequently performed. The adoption of GL was associated with fewer ICA, higher proportion of diagnosis of obstructive CAD (60% vs. 39%, P < 0.001) and revascularization (54% vs. 37%, P < 0.001), higher quality of life, fewer additional testing, and longer times to late revascularization. CONCLUSIONS: In patients with CCS, current clinical practice does not adopt GL recommendations on the use of diagnostic tests in a significant proportion of patients. When the diagnostic approach adopts GL recommendations, invasive procedures are less frequently used and the diagnostic yield and therapeutic utility are superior.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks.

Purpose: Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease 2019 (COVID-19) patients but are not part of clinical routine because the required manual segmentation of lung lesions is prohibitively time consuming. We aim to automatically segment ground-glass opacities and high opacities (comprising consolidation and pleural effusion). Approach: We propose a new fully automated deep-learning framework for fast multi-class segmentation of lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional long short-term memory (ConvLSTM) networks. Utilizing the expert annotations, model training was performed using five-fold cross-validation to segment COVID-19 lesions. The performance of the method was evaluated on CT datasets from 197 patients with a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2, 68 unseen test cases, and 695 independent controls. Results: Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score of 0.89 ± 0.07 ; excellent correlations of 0.93 and 0.98 for ground-glass opacity (GGO) and high opacity volumes, respectively, were obtained. In the external testing set of 68 patients, we observed a Dice score of 0.89 ± 0.06 as well as excellent correlations of 0.99 and 0.98 for GGO and high opacity volumes, respectively. Computations for a CT scan comprising 120 slices were performed under 3 s on a computer equipped with an NVIDIA TITAN RTX GPU. Diagnostically, the automated quantification of the lung burden % discriminate COVID-19 patients from controls with an area under the receiver operating curve of 0.96 (0.95-0.98). Conclusions: Our method allows for the rapid fully automated quantitative measurement of the pneumonia burden from CT, which can be used to rapidly assess the severity of COVID-19 pneumonia on chest CT.

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.

Role of cardiac MRI in the diagnosis of immune checkpoint inhibitor-associated myocarditis.

Immune checkpoint inhibitor (ICI)-induced cardiotoxicity is a rare immune-related adverse event (irAE) characterized by a high mortality rate. From a pathological point of view, this condition can result from a series of causes, including binding of ICIs to target molecules on nonlymphocytic cells, cross-reaction of T lymphocytes against tumor antigens with off-target tissues, generation of autoantibodies and production of proinflammatory cytokines. The diagnosis of ICI-induced cardiotoxicity can be challenging, and cardiac magnetic resonance (CMR) represents the diagnostic tool of choice in clinically stable patients with suspected myocarditis. CMR is gaining a central role in diagnosis and monitoring of cardiovascular damage in cancer patients, and it is entering international cardiology and oncology guidelines. In this narrative review, we summarized the clinical aspects of ICI-associated myocarditis, highlighting its radiological aspects and proposing a novel algorithm for the use of CMR.

A case of myopericarditis recurrence after third dose of BNT162b2 vaccine against SARS-CoV-2 in a young subject: link or causality?

The rate of post-vaccine myocarditis is being studied from the beginning of the massive vaccination campaign against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a direct cause-effect relationship has been described, in most cases, the vaccine pathophysiological role is doubtful. Moreover, it is not quite as clear as having had a previous myocarditis could be a risk factor for a post-vaccine disease relapse. A 27-year-old man presented to the emergency department for palpitations and pericardial chest pain radiated to the upper left limb, on the 4th day after the third dose of BNT162b2 vaccine. He experienced a previous myocarditis 3 years before, with full recovery and no other comorbidities. Electrocardiogram showed normal atrioventricular conduction, incomplete right bundle branch block, and diffuse ST-segment elevation. A cardiac echo showed lateral wall hypokinesis with preserved ejection fraction. Troponin-T was elevated (160 ng/L), chest X-ray was normal, and the SARS-CoV-2 molecular buffer was negative. High-dose anti-inflammatory therapy with ibuprofen and colchicine was started; in the 3rd day high-sensitivity Troponin I reached a peak of 23000 ng/L. No heart failure or arrhythmias were observed. A cardiac magnetic resonance was performed showing normal biventricular systolic function and abnormal tissue characterization suggestive for acute non-ischaemic myocardial injury (increased native T1 and T2 values, increased signal intensity at T2-weighted images and late gadolinium enhancement, all findings with matched subepicardial distribution) at the level of mid to apical septal, anterior, and anterolateral walls. A left ventricular electroanatomic voltage mapping was negative (both unipolar and bipolar), while the endomyocardial biopsy showed a picture consistent with active myocarditis. The patient was discharged in good clinical condition, on bisoprolol 1.25 mg, ramipril 2.5 mg, ibuprofen 600 mg three times a day, colchicine 0.5 mg twice a day. We presented the case of a young man with history of previous myocarditis, admitted with a non-complicated acute myopericarditis relapse occurred 4 days after SARS-CoV-2 vaccination (3rd dose). Despite the observed very low incidence of cardiac complications following BNT162b2 administration, and the lack of a clear proof of a direct cause-effect relationship, we think that in our patient this link can be more than likely. In the probable need for additional SARS-CoV-2 vaccine doses in the next future, studies addressing the risk-benefit balance of this subset of patient are warranted. We described a multidisciplinary management of a case of myocarditis recurrence after the third dose of SARS-CoV-2 BNT162b2 vaccine.

Appropriateness criteria for the use of cardiac computed tomography, SIC-SIRM part 2: acute chest pain evaluation; stent and coronary artery bypass graft patency evaluation; planning of coronary revascularization and transcatheter valve procedures; cardiomyopathies, electrophysiological applications, cardiac masses, cardio-oncology and pericardial diseases evaluation.

In the past 20 years, cardiac computed tomography (CCT) has become a pivotal technique for the noninvasive diagnostic workup of coronary and cardiac diseases. Continuous technical and methodological improvements, combined with fast growing scientific evidence, have progressively expanded the clinical role of CCT. Randomized clinical trials documented the value of CCT in increasing the cost-effectiveness of the management of patients with acute chest pain presenting in the emergency department, also during the pandemic. Beyond the evaluation of stents and surgical graft patency, the anatomical and functional coronary imaging have the potential to guide treatment decision-making and planning for complex left main and three-vessel coronary disease. Furthermore, there has been an increasing demand to use CCT for preinterventional planning in minimally invasive procedures, such as transcatheter valve implantation and mitral valve repair. Yet, the use of CCT as a roadmap for tailored electrophysiological procedures has gained increasing importance to assure maximum success. In the meantime, innovations and advanced postprocessing tools have generated new potential applications of CCT from the simple coronary anatomy to the complete assessment of structural, functional and pathophysiological biomarkers of cardiac disease. In this complex and revolutionary scenario, it is urgently needed to provide an updated guide for the appropriate use of CCT in different clinical settings. This manuscript, endorsed by the Italian Society of Cardiology (SIC) and the Italian Society of Medical and Interventional Radiology (SIRM), represents the second of two consensus documents collecting the expert opinion of cardiologists and radiologists about current appropriate use of CCT.

Cardiac magnetic resonance imaging of myocarditis and pericarditis following COVID-19 vaccination: a multicenter collection of 27 cases.

OBJECTIVES: To assess clinical and cardiac magnetic resonance (CMR) imaging features of patients with peri-myocarditis following Coronavirus Disease 2019 (COVID-19) vaccination. METHODS: We retrospectively collected a case series of 27 patients who underwent CMR in the clinical suspect of heart inflammation following COVID-19 vaccination, from 16 large tertiary centers. Our patient's cohort was relatively young (36.6 ± 16.8 years), predominately included males (n = 25/27) with few comorbidities and covered a catchment area of approximately 8 million vaccinated patients. RESULTS: CMR revealed typical mid-subepicardial non-ischemic late gadolinium enhancement (LGE) in 23 cases and matched positively with CMR T2 criteria of myocarditis. In 7 cases, typical hallmarks of acute pericarditis were present. Short-term follow-up (median = 20 days) from presentation was uneventful for 25/27 patients and unavailable in two cases. CONCLUSIONS: While establishing a causal relationship between peri-myocardial inflammation and vaccine administration can be challenging, our clinical experience suggests that CMR should be performed for diagnosis confirmation and to drive clinical decision-making and follow-up. KEY POINTS: • Acute onset of dyspnea, palpitations, or acute and persisting chest pain after COVID-19 vaccination should raise the suspicion of possible myocarditis or pericarditis, and patients should seek immediate medical attention and treatment to help recovery and avoid complications. • In case of elevated troponin levels and/or relevant ECG changes, cardiac magnetic resonance should be considered as the best non-invasive diagnostic option to confirm the diagnosis of myocarditis or pericarditis and to drive clinical decision-making and follow-up.

Non-invasive coronary imaging in patients with COVID-19: A narrative review.

SARS-CoV-2 infection, responsible for COVID-19 outbreak, can cause cardiac complications, worsening outcome and prognosis. In particular, it can exacerbate any underlying cardiovascular condition, leading to atherosclerosis and increased plaque vulnerability, which may cause acute coronary syndrome. We review current knowledge on the mechanisms by which SARS-CoV-2 can trigger endothelial/myocardial damage and cause plaque formation, instability and deterioration. The aim of this review is to evaluate current non-invasive diagnostic techniques for coronary arteries evaluation in COVID-19 patients, such as coronary CT angiography and atherosclerotic plaque imaging, and their clinical implications. We also discuss the role of artificial intelligence, deep learning and radiomics in the context of coronary imaging in COVID-19 patients.

Cardiac Care of Non-COVID-19 Patients During the SARS-CoV-2 Pandemic: The Pivotal Role of CCTA.

Aim: The aim of this study is to evaluate the potential use of coronary CT angiography (CCTA) as the sole available non-invasive diagnostic technique for suspected coronary artery disease (CAD) during the coronavirus disease 2019 (COVID-19) pandemic causing limited access to the hospital facilities. Methods and Results: A consecutive cohort of patients with suspected stable CAD and clinical indication to non-invasive test was enrolled in a hub hospital in Milan, Italy, from March 9 to April 30, 2020. Outcome measures were obtained as follows: cardiac death, ST-elevation myocardial infarction (STEMI), non-ST-elevation myocardial infarction (NSTEMI), and unstable angina. All the changes in medical therapy following the result of CCTA were annotated. A total of 58 patients with a mean age of 64 ± 11 years (36 men and 22 women) were enrolled. CCTA showed no CAD in 14 patients (24.1%), non-obstructive CAD in 30 (51.7%) patients, and obstructive CAD in 14 (24.1%) patients. Invasive coronary angiography (ICA) was considered deferrable in 48 (82.8%) patients. No clinical events were recorded after a mean follow-up of 376.4 ± 32.1 days. Changes in the medical therapy were significantly more prevalent in patients with vs. those without CAD at CCTA. Conclusion: The results of the study confirm the capability of CCTA to safely defer ICA in the majority of symptomatic patients and to correctly identify those with critical coronary stenoses necessitating coronary revascularization. This characteristic could be really helpful especially when the hospital resources are limited.

Coronary calcium score as a predictor of outcomes in the hypertensive Covid-19 population: results from the Italian (S) Core-Covid-19 Registry.

Hypertension is associated with more severe disease and adverse outcomes in COVID-19 patients. Recent investigations have indicated that hypertension might be an independent predictor of outcomes in COVID-19 patients regardless of other cardiovascular and noncardiovascular comorbidities. We explored the significance of coronary calcifications in 694 hypertensive patients in the Score-COVID registry, an Italian multicenter study conducted during the first pandemic wave in the Western world (March-April 2020). A total of 1565 patients admitted with RNA-PCR-positive nasopharyngeal swabs and chest computed tomography (CT) at hospital admission were included in the study. Clinical outcomes and cardiovascular calcifications were analyzed independently by a research core lab. Hypertensive patients had a different risk profile than nonhypertensive patients, with more cardiovascular comorbidities. The deceased hypertensive patients had a greater coronary calcification burden at the level of the anterior descending coronary artery. Hypertension status and the severity cutoffs of coronary calcifications were used to stratify the clinical outcomes. For every 100-mm3 increase in coronary calcium volume, hospital mortality in hypertensive patients increased by 8%, regardless of sex, age, diabetes, creatinine, and lung interstitial involvement. The coronary calcium score contributes to stratifying the risk of complications in COVID-19 patients. Cardiovascular calcifications appear to be a promising imaging marker for providing pathophysiological insight into cardiovascular risk factors and COVID-19 outcomes.

Reduction of cardiac imaging tests during the COVID-19 pandemic: The case of Italy. Findings from the IAEA Non-invasive Cardiology Protocol Survey on COVID-19 (INCAPS COVID).

BACKGROUND: In early 2020, COVID-19 massively hit Italy, earlier and harder than any other European country. This caused a series of strict containment measures, aimed at blocking the spread of the pandemic. Healthcare delivery was also affected when resources were diverted towards care of COVID-19 patients, including intensive care wards. AIM OF THE STUDY: The aim is assessing the impact of COVID-19 on cardiac imaging in Italy, compare to the Rest of Europe (RoE) and the World (RoW). METHODS: A global survey was conducted in May-June 2020 worldwide, through a questionnaire distributed online. The survey covered three periods: March and April 2020, and March 2019. Data from 52 Italian centres, a subset of the 909 participating centres from 108 countries, were analyzed. RESULTS: In Italy, volumes decreased by 67% in March 2020, compared to March 2019, as opposed to a significantly lower decrease (p < 0.001) in RoE and RoW (41% and 40%, respectively). A further decrease from March 2020 to April 2020 summed up to 76% for the North, 77% for the Centre and 86% for the South. When compared to the RoE and RoW, this further decrease from March 2020 to April 2020 in Italy was significantly less (p = 0.005), most likely reflecting the earlier effects of the containment measures in Italy, taken earlier than anywhere else in the West. CONCLUSIONS: The COVID-19 pandemic massively hit Italy and caused a disruption of healthcare services, including cardiac imaging studies. This raises concern about the medium- and long-term consequences for the high number of patients who were denied timely diagnoses and the subsequent lifesaving therapies and procedures.

Impact of COVID-19 on the imaging diagnosis of cardiac disease in Europe.

OBJECTIVES: We aimed to explore the impact of the COVID-19 pandemic on cardiac diagnostic testing and practice and to assess its impact in different regions in Europe. METHODS: The online survey organised by the International Atomic Energy Agency Division of Human Health collected information on changes in cardiac imaging procedural volumes between March 2019 and March/April 2020. Data were collected from 909 centres in 108 countries. RESULTS: Centres in Northern and Southern Europe were more likely to cancel all outpatient activities compared with Western and Eastern Europe. There was a greater reduction in total procedure volumes in Europe compared with the rest of the world in March 2020 (45% vs 41%, p=0.003), with a more marked reduction in Southern Europe (58%), but by April 2020 this was similar in Europe and the rest of the world (69% vs 63%, p=0.261). Regional variations were apparent between imaging modalities, but the largest reductions were in Southern Europe for nearly all modalities. In March 2020, location in Southern Europe was the only independent predictor of the reduction in procedure volume. However, in April 2020, lower gross domestic product and higher COVID-19 deaths were the only independent predictors. CONCLUSION: The first wave of the COVID-19 pandemic had a significant impact on care of patients with cardiac disease, with substantial regional variations in Europe. This has potential long-term implications for patients and plans are required to enable the diagnosis of non-COVID-19 conditions during the ongoing pandemic.

The hidden interplay between sex and COVID-19 mortality: the role of cardiovascular calcification.

Recent clinical and demographical studies on COVID-19 patients have demonstrated that men experience worse outcomes than women. However, in most cases, the data were not stratified according to gender, limiting the understanding of the real impact of gender on outcomes. This study aimed to evaluate the disaggregated in-hospital outcomes and explore the possible interactions between gender and cardiovascular calcifications. Data was derived from the sCORE-COVID-19 registry, an Italian multicentre registry that enrolled COVID-19 patients who had undergone a chest computer tomography scan on admission. A total of 1683 hospitalized patients (mean age 67±14 years) were included. Men had a higher prevalence of cardiovascular comorbidities, a higher pneumonia extension, more coronary calcifications (63% vs.50.9%, p<0.001), and a higher coronary calcium score (391±847 vs. 171±479 mm3, p<0.001). Men experienced a significantly higher mortality rate (24.4% vs. 17%, p=0.001), but the death event tended to occur earlier in women (15±7 vs. 8±7 days, p= 0.07). Non-survivors had a higher coronary, thoracic aorta, and aortic valve calcium score. Female sex, a known independent predictor of a favorable outcome in SARS-CoV2 infection, was not protective in women with a coronary calcification volume greater than 100 mm3. There were significant differences in cardiovascular comorbidities and vascular calcifications between men and women with SARS-CoV2 pneumonia. The differences in outcomes can be at least partially explained by the different cardiovascular profiles. However, women with poor outcomes had the same coronary calcific burden as men. The presumed favorable female sex bias in COVID-19 must therefore be reviewed in the context of comorbidities, especially cardiovascular ones.

Modeling the cardiac response to hemodynamic changes associated with COVID-19: a computational study.

Emerging studies address how COVID-19 infection can impact the human cardiovascular system. This relates particularly to the development of myocardial injury, acute coronary syndrome, myocarditis, arrhythmia, and heart failure. Prospective treatment approach is advised for these patients. To study the interplay between local changes (reduced contractility), global variables (peripheral resistances, heart rate) and the cardiac function, we considered a lumped parameters computational model of the cardiovascular system and a three-dimensional multiphysics model of cardiac electromechanics. Our mathematical model allows to simulate the systemic and pulmonary circulations, the four cardiac valves and the four heart chambers, through equations describing the underlying physical processes. By the assessment of conventionally relevant parameters of cardiac function obtained through our numerical simulations, we propose a computational model to effectively reveal the interactions between the cardiac and pulmonary functions in virtual subjects with normal and impaired cardiac function at baseline affected by mild or severe COVID-19.

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.