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.

Symptoms-to-emergency-call timing delay in acute coronary syndrome before and during COVID-19: independent predictors and their impact on mortality.

BACKGROUND: The COVID-19 pandemic severely impacted global health. The aim of this study was to compare predictors of symptoms-to-emergency-call timing delay in Acute Coronary Syndrome (ACS) and their impact on mortality before and during the COVID-19 outbreak. METHODS: We collected sociodemographic, clinical data, procedural features, pre-admission and intra-hospital outcomes of consecutive patients admitted for ACS in seventeen Italian centers from March to April 2018, 2019, and 2020. RESULTS: In 2020, a 32.92% reduction in ACS admissions was observed compared to 2018 and 2019. Unstable angina, typical and atypical symptoms, and intermittent angina were identified as significant predictors of symptoms-to-emergency-call timing delay before and during the COVID-19 pandemic (p<0.005 for all the items). Differently from 2018-2019, during the pandemic, hypertension and dyspnea (p=0.002 versus [vs] p=0.490 and p=0.001 vs p=0.761 for 2018-2019 and 2020, respectively) did not result as predictors of delay in symptoms-to-emergency-call timing. Among these predictors, only the atypical symptoms (HR 3.36; 95% CI 1.172 - 9.667, p=0.024) in 2020 and the dyspnea (HR 2.64; 95% CI 1.345 - 5.190, p=0.005) in 2018-2019 resulted significantly associated with higher mortality. Finally, the family attendance at the onset of the symptoms resulted in a reduction in symptoms-to-emergency-call timing (in 2020 p<0.001; CI -1710.73; -493.19) and in a trend of reduced mortality (HR 0.31; 95% CI 0.089 - 1.079, p=0.066) in 2020. CONCLUSIONS: During the COVID-19 outbreak, atypical symptoms and family attendance at ACS onset were identified, respectively, as adverse and favorable predictors of symptoms-to-emergencycall timing delay and mortality.

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.

The Incidence and Impact of In-Hospital Bleeding in Patients with Acute Coronary Syndrome during the COVID-19 Pandemic.

BACKGROUND: The COVID-19 pandemic increased the complexity of the clinical management and pharmacological treatment of patients presenting with an Acute Coronary Syndrome (ACS). AIM: to explore the incidence and prognostic impact of in-hospital bleeding in patients presenting with ACS before and during the COVID-19 pandemic. METHODS: We evaluated in-hospital Thrombolysis In Myocardial Infarction (TIMI) major and minor bleeding among 2851 patients with ACS from 17 Italian centers during the first wave of the COVID-19 pandemic (i.e., March-April 2020) and in the same period in the previous two years. RESULTS: The incidence of in-hospital TIMI major and minor bleeding was similar before and during the COVID-19 pandemic. TIMI major or minor bleeding was associated with a significant threefold increase in all-cause mortality, with a similar prognostic impact before and during the COVID-19 pandemic. CONCLUSIONS: the incidence and clinical impact of in-hospital bleeding in ACS patients was similar before and during the COVID-19 pandemic. We confirmed a significant and sizable negative prognostic impact of in-hospital bleeding in ACS patients.

Impact of COVID-19 pandemic on in-hospital outcomes for patients with acute coronary syndrome: a propensity-weighted, multicentre study

Aims Coronavirus disease 19 (COVID-19) pandemic has dramatically changed the management and the prognosis of patients experiencing acute coronary syndrome (ACS). Several scientific societies have highlighted the need for dedicated paths to deliver better and faster care to improve outcomes. Nevertheless, data depicting the impact of COVID-19 pandemic on ACS in Italy are still poor. To perform a propensity weighted analysis on a multicentre Italian registry involving patients with ACS managed before vs. during COVID-19 pandemic, taking into account baseline patients characteristics, clinical presentation, procedural aspects, and in-hospital outcomes (death, bleeding, stent thrombosis, myocardial infarction, stroke/transient ischaemic attack, mechanical complication, and arrhythmic complication). Methods and results We included all consecutive patients who have suffered from ACS during two periods before (March/April 2018, March/April 2019) vs. the period of COVID-19 pandemic (March/April 2020). A generalized boosted non-parsimonious regression was used to estimate the propensity scores of having an ACS in 2020 (year of COVID-19) vs. 2018/2019 using an average treatment effect and balancing for all baseline confounders. We included 2851 patients admitted to hospital with ACS in 17 Italian centres: 1079 (37.8%) during 2018, 1056 (37.0%) in 2019, and 716 (25.1%) during the first COVID-19 wave of 2020. Seventy (2.5%) patients had a positive swab for SARS-CoV-2 at admission. During 2020 there were higher time-to-emergency-call (P = 0.028) and less diagnosis of unstable angina (P = 0.029) and MINOCA (P = 0.004);none of the admission symptoms differ significantly across the years (P > 0.05) except for fever that was more prevalent in 2020 (P < 0.001). Patients suffering from ACS had lower admission EF (P = 0.006). After PS weighting, multivariate Cox regression analysis showed age (P < 0.001), night admission (P = 0.017), cardiocirculatory arrest before cath-lab (P = 0.041), worst Killip class (P = 0.039), admission EF (P = 0.026), and need for left-ventricle mechanical support (P = 0.011) as independent predictors of in-hospital death. After propensity weighted analysis none of the in-hospital outcomes differed significantly across the years of investigation (all P > 0.05). Conclusions During COVID-19 pandemic in Italy the characteristics and management of ACS was slightly different than the past. However, the rates of ‘hard’, in-hospital outcomes (e.g. deaths) are almost similar to the past, suggesting appropriate care and well-organized emergency-paths for ACS.

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.

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.

The Combination of Chest Computed Tomography and Standard Electrocardiogram Provides Prognostic Information and Pathophysiological Insights in COVID-19 Pneumonia.

AIMS: Several studies have unveiled the great heterogeneity of COVID-19 pneumonia. Identification of the "vascular phenotype" (involving both pulmonary parenchyma and its circulation) has prognostic significance. Our aim was to explore the combined role of chest computed tomography (CT) scan and electrocardiogram (ECG) at hospital admission in predicting short-term prognosis and to draw pathophysiological insights. METHODS AND RESULTS: We analyzed the chest CT scan and ECG performed at admission in 151 consecutive COVID-19 patients admitted between 20 March and 4 April 2020. All-cause mortality within 30 days was the primary endpoint. Median age was 71 years (IQR: 62-76). Severe pneumonia was present in 25 (17%) patients, and 121 (80%) had abnormal ECG. During a median follow-up of 7 days (IQR: 4-13), 54 (36%) patients died. Deceased patients had more severe pneumonia than survivors did (80% vs. 64%, p = 0.044). ECG in deceased patients showed more frequently atrial fibrillation/flutter (17% vs. 6%, p = 0.039) and acute right ventricular (RV) strain (35% vs. 10%, p < 0.001), suggesting the "vascular phenotype". ECG signs of acute RV strain (HR 2.46, 95% CIs 1.36-4.45, p = 0.0028) were independently associated with all-cause mortality in multivariable analysis, and in the likelihood ratio test, showed incremental prognostic value over chest CT scan, age, and C-reactive protein. CONCLUSIONS: Combining chest CT scan and ECG data improves risk stratification in COVID-19 pneumonia by identifying a distinctive phenotype with both parenchymal and vascular damage of the lung. Patients with severe pneumonia at chest CT scan plus ECG signs of acute RV strain have an extremely poor short-term prognosis.

Epidemiological findings on interventional cardiology procedures during the COVID-19 pandemic: A multi-center study.

BACKGROUND: The rates of in-hospital mortality following percutaneous interventional procedures (PIP) during the COVID-19 pandemic period compared to the non-pandemic period has not been reported so far. METHODS: We retrospectively enrolled all consecutive patients admitted for PIP across five centers from February 2020 to May 2020. RESULTS: A total of 4092 PIP were performed during the reference periods. The total number of procedures dropped from 2380 to 1712 (28.0% reduction). Overall in-hospital mortality increased from 1.1% in 2019, to 2.6% in 2020 (63% relative increase). CONCLUSION: During the COVID-19 pandemic, in-hospital all-cause mortality significantly increased in patients admitted for cardiological PIP.

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.

Incidence and characterization of acute pulmonary embolism in patients with SARS-CoV-2 pneumonia: A multicenter Italian experience.

BACKGROUND AND AIMS: Several studies reported a high incidence of pulmonary embolism (PE) among patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, but detailed data about clinical characteristics, risk factors of these patients and prognostic role of PE are still lacking. We aim to evaluate the occurrence of pulmonary embolism among patients with SARS-CoV-2 infection, and to describe their risk factors, clinical characteristics, and in-hospital clinical outcomes. METHODS: This is a multicenter Italian study including 333 consecutive SARS-CoV-2 patients admitted to seven hospitals from February 22 to May 15, 2020. All the patients underwent computed tomography pulmonary angiography (CTPA) for PE detection. In particular, CTPA was performed in case of inadequate response to high-flow oxygen therapy (Fi02≥0.4 to maintain Sp02≥92%), elevated D-dimer (>0.5µg/mL), or echocardiographic signs of right ventricular dysfunction. Clinical, laboratory and radiological data were also analyzed. RESULTS: Among 333 patients with laboratory confirmed SARS-CoV-2 pneumonia and undergoing CTPA, PE was detected in 109 (33%) cases. At CTPA, subsegmental, segmental, lobar and central thrombi were detected in 31 (29%), 50 (46%), 20 (18%) and 8 (7%) cases, respectively. In-hospital death occurred in 29 (27%) patients in the PE-group and in 47 (21%) patients in the non-PE group (p = 0.25). Patients in PE-group had a low rate of traditional risk factors and deep vein thrombosis was detected in 29% of patients undergoing compression ultrasonography. In 71% of cases with documented PE, the thrombotic lesions were located in the correspondence of parenchymal consolidation areas. CONCLUSIONS: Despite a low rate of risk factors for venous thromboembolism, PE is present in about 1 out 3 patients with SARS-CoV-2 pneumonia undergoing CTPA for inadequate response to oxygen therapy, elevated D-dimer level, or echocardiographic signs of right ventricular dysfunction. In most of the cases, the thromboses were located distally in the pulmonary tree and were mainly confined within pneumonia areas.

Chest CT-derived pulmonary artery enlargement at the admission predicts overall survival in COVID-19 patients: insight from 1461 consecutive patients in Italy.

OBJECTIVES: Enlarged main pulmonary artery diameter (MPAD) resulted to be associated with pulmonary hypertension and mortality in a non-COVID-19 setting. The aim was to investigate and validate the association between MPAD enlargement and overall survival in COVID-19 patients. METHODS: This is a cohort study on 1469 consecutive COVID-19 patients submitted to chest CT within 72 h from admission in seven tertiary level hospitals in Northern Italy, between March 1 and April 20, 2020. Derivation cohort (n = 761) included patients from the first three participating hospitals; validation cohort (n = 633) included patients from the remaining hospitals. CT images were centrally analyzed in a core-lab blinded to clinical data. The prognostic value of MPAD on overall survival was evaluated at adjusted and multivariable Cox's regression analysis on the derivation cohort. The final multivariable model was tested on the validation cohort. RESULTS: In the derivation cohort, the median age was 69 (IQR, 58-77) years and 537 (70.6%) were males. In the validation cohort, the median age was 69 (IQR, 59-77) years with 421 (66.5%) males. Enlarged MPAD (≥ 31 mm) was a predictor of mortality at adjusted (hazard ratio, HR [95%CI]: 1.741 [1.253-2.418], p < 0.001) and multivariable regression analysis (HR [95%CI]: 1.592 [1.154-2.196], p = 0.005), together with male gender, old age, high creatinine, low well-aerated lung volume, and high pneumonia extension (c-index [95%CI] = 0.826 [0.796-0.851]). Model discrimination was confirmed on the validation cohort (c-index [95%CI] = 0.789 [0.758-0.823]), also using CT measurements from a second reader (c-index [95%CI] = 0.790 [0.753;0.825]). CONCLUSION: Enlarged MPAD (≥ 31 mm) at admitting chest CT is an independent predictor of mortality in COVID-19. KEY POINTS: • Enlargement of main pulmonary artery diameter at chest CT performed within 72 h from the admission was associated with a higher rate of in-hospital mortality in COVID-19 patients. • Enlargement of main pulmonary artery diameter (≥ 31 mm) was an independent predictor of death in COVID-19 patients at adjusted and multivariable regression analysis. • The combined evaluation of clinical findings, lung CT features, and main pulmonary artery diameter may be useful for risk stratification in COVID-19 patients.