Long-term prognostic impact of subclinical myocardial dysfunction in patients recovered from COVID-19.

BACKGROUND: Cardiovascular sequelae may occur in patients recovered from coronavirus disease 2019 (COVID-19). Recent studies have detected a considerable incidence of subclinical myocardial dysfunction-assessed with speckle-tracking echocardiography-and of long-COVID symptoms in these patients. This study aimed to define the long-term prognostic role of subclinical myocardial dysfunction and long-COVID condition in patients recovered from COVID-19 pneumonia. METHODS: We prospectively followed up 110 patients hospitalized at our institution due to COVID-19 pneumonia in April 2020 and then recovered from SARS-CoV-2 infection. A 7-month clinical and echocardiographic evaluation was performed, followed by a 21-month clinical follow-up. The primary outcome was major adverse cardiovascular events (MACE), a composite of myocardial infarction, stroke, heart failure hospitalization, and all-cause mortality. RESULTS: A subclinical myocardial dysfunction-defined as an impairment of left ventricular global longitudinal strain (≥-18%)-was identified at a 7-month follow-up in 37 patients (34%), was associated with an increased risk of long-term MACE with a good discriminative power (area under the curve: .73) and resulted in a strong independent predictor of extended MACE in multivariate regression analyses. Long-COVID condition was not associated with a worse long-term prognosis, instead. CONCLUSIONS: In patients recovered from COVID-19 pneumonia, a subclinical myocardial dysfunction is present in one-third of the whole population at 7-month follow-up and is associated with a higher risk of MACE at long-term follow-up. Speckle-tracking echocardiography is a promising tool to optimize the risk-stratification in patients recovered from COVID-19 pneumonia, while the definition of a long-COVID condition has no prognostic relevance.

Performing elective cardiac invasive procedures during the COVID-19 outbreak: a position statement from the European Association of Percutaneous Cardiovascular Interventions (EAPCI).

The rearrangement of healthcare services required to face the coronavirus disease 2019 (COVID-19) pandemic led to a drastic reduction in elective cardiac invasive procedures. We are already facing a "second wave" of infections and we might be dealing during the next months with a "third wave" and subsequently new waves. Therefore, during the different waves of the COVID-19 pandemic we have to face the problems of how to perform elective cardiac invasive procedures in non-COVID patients and which patients/procedures should be prioritised. In this context, the interplay between the pandemic stage, the availability of healthcare resources and the priority of specific cardiac disorders is crucial. Clear pathways for "hot" or presumed "hot" patients and "cold" patients are mandatory in each hospital. Depending on the local testing capacity and intensity of transmission in the area, healthcare facilities may test patients for SARS-CoV-2 infection before the interventional procedure, regardless of risk assessment for COVID-19. Pre-hospital testing should always be conducted in the presence of symptoms suggestive of SARS-CoV-2 infection. In cases of confirmed or suspected COVID-19 positive patients, full personal protective equipment using FFP 2/N95 masks, eye protection, gowning and gloves is indicated during cardiac interventions for healthcare workers. When patients have tested negative for COVID-19, medical masks may be sufficient. Indeed, individual patients should themselves wear medical masks during cardiac interventions and outpatient visits.

An individualized algorithm to predict mortality in COVID-19 pneumonia: a machine learning based study.

Introduction: Identifying SARS-CoV-2 patients at higher risk of mortality is crucial in the management of a pandemic. Artificial intelligence techniques allow one to analyze large amounts of data to find hidden patterns. We aimed to develop and validate a mortality score at admission for COVID-19 based on high-level machine learning. Material and methods: We conducted a retrospective cohort study on hospitalized adult COVID-19 patients between March and December 2020. The primary outcome was in-hospital mortality. A machine learning approach based on vital parameters, laboratory values and demographic features was applied to develop different models. Then, a feature importance analysis was performed to reduce the number of variables included in the model, to develop a risk score with good overall performance, that was finally evaluated in terms of discrimination and calibration capabilities. All results underwent cross-validation. Results: 1,135 consecutive patients (median age 70 years, 64% male) were enrolled, 48 patients were excluded, and the cohort was randomly divided into training (760) and test (327) groups. During hospitalization, 251 (22%) patients died. After feature selection, the best performing classifier was random forest (AUC 0.88 ±0.03). Based on the relative importance of each variable, a pragmatic score was developed, showing good performances (AUC 0.85 ±0.025), and three levels were defined that correlated well with in-hospital mortality. Conclusions: Machine learning techniques were applied in order to develop an accurate in-hospital mortality risk score for COVID-19 based on ten variables. The application of the proposed score has utility in clinical settings to guide the management and prognostication of COVID-19 patients.

Specific characteristics of STEMI in COVID-19 patients and their practical implications.

ST-elevation myocardial infarction (STEMI) is one of the cardiac emergencies whose management has been most challenged by the COVID-19 pandemic. Patients presenting with the "lethal combo" of STEMI and concomitant SARS-CoV-2 infection have faced dramatic issues related to the need for self-isolation, systemic inflammation with multi-organ disease and difficulties to obtain timely diagnosis and treatment. The interplay between these and other factors has partly neutralized the major advances in STEMI care achieved in the last decades, significantly impairing prognosis in these patients. In the present review article, we will provide an overview on mechanisms of myocardial injury, specific clinical and angiographic characteristics and contemporary management in different settings of STEMI patients with COVID-19, alongside the inherent implications in terms of in-hospital mortality and short-term clinical outcomes.

Impact of RAAS Inhibitors on Clinical Outcome and Mortality in Patients With STEMI During the COVID-19 Era: A Multicenter Observational Study

Conflicting results are available regarding the influence of ACEi/ARBs on the risk of COVID-19 infection, while less is known about their impact on the clinical outcome of patients with STEMI diagnosed with COVID-19. Our aim was to evaluate the impact of ACEi/ARBs therapy on in-hospital mortality and clinical outcomes of patients with STEMI during the COVID-19 pandemic. We retrospectively analyzed consecutive patients with STEMI hospitalized from February 20 to May 10, 2020 in four Hospitals in Lombardy. SARS-COV-2 diagnosis was performed by nasopharyngeal swab test. Procedural outcome, respiratory complications, and in-hospital mortality were reported. Univariate and multivariate analyses were performed by logistic regressions. Our population was represented by 182 patients with STEMI, 76.9% of which were males, and mean age was 67 ± 12.5. Hypertension was reported in 53.3%, and 29.1% was treated with ACEi/ARBs. COVID-19 diagnosis was confirmed in 17.1% of the patients. In-hospital mortality (13.2%) was significantly higher in patients with COVID-19 (31 vs. 10%, p = 0.003), even if ejection fraction [OR 0.93 (95% CI) 0.87–0.99;p = 0.03] and respiratory complications [OR 9.39 (95% CI) 1.91–45.9;p = 0.006] were the only two independent predictors. The incidence of COVID-19 infection was not influenced by ACEi/ARBs (16.5 in naïve vs. 18.8%) whose presence on admission did not correlate with respiratory complications or mortality both in the case of discontinuation and maintenance. In conclusion, in a high-risk population, such as that of patients with STEMI, the potential benefit of ACEi/ARB discontinuation in patients with COVID-19 is overcome by its detrimental effect. Intensive care, additional preventive respiratory investigations, regardless of swab test result, should be suggested for all patients admitted for STEMI during the pandemic.

Cardiovascular magnetic resonance characterization of myocardial injury in recovered COVID-19 patients with elevated troponins during hospital stay

Aims Despite being a common finding in hospitalized COVID-19 patients, cardiac troponin elevation remains a nonspecific detection of myocardial injury and further in-hospital investigation into the cause of myocardial injury is rarely done. COVID-19 patients with myocardial injury show a significantly higher in-hospital mortality rate compared with those without myocardial injury and among those with myocardial injury, greater degrees of troponin elevation are associated with higher mortality rates. There are still many questions regarding possible cardiovascular sequelae and prognostic significance in these patients. Being able to distinguish between inflammatory and ischaemic causes of myocardial injury cardiovascular magnetic resonance (CMR) is the non-invasive modality of choice to investigate myocardial involvement in these patients. Presented are the preliminary single-centre results from a multicentre study aimed to characterize the prevalence, type and extent of COVID-19-related cardiovascular sequelae using CMR imaging. Methods and results In this single-centre prospective observational cohort study, patients hospitalized with confirmed COVID-19 and at least one value of high sensitivity I troponin (hs-Tnl) >99th percentile during hospitalization were eligible for follow-up contrast-enhanced CMR imaging. Patients with any standard CMR contraindications were excluded. Images were acquired using a standardized myocarditis protocol including late gadolinium enhancement (LGE) and T1 and T2 mapping. Cutoff values of 1015 ms and 50 ms were used for abnormal T1 and T2 measurements, respectively. Of the 21 patients (65 ± 11.85 years) who underwent imaging, 15 (71.4%) were male. The mean follow-up duration from the date of confirmed COVID-19 diagnosis was 169 ± 19 days. The mean left ventricular ejection fraction was 64.1 ± 13.87 and 3 (14.3%) patients had evidence of wall motion abnormalities. LGE was seen in 9/20 (45.0%) patients, reflecting myocardial fibrosis. Increased native T1 signal representing myocardial fibrosis and/or oedema was seen in 9/20 (45.0%) patients. While increased native T2 signal, being more specific for oedema was observed in 3/20 (15.0%) patients. Considering CMR findings, 6 (28.6%) patients showed evidence of previous myocarditis. Conclusions In this single centre Italian study of patients hospitalized with COVID-19 and elevated cardiac enzymes, myocarditis-like injury was evident in about a quarter of the patients. Whether these findings will lead to long-term cardiac complications is still to be confirmed.

In-hospital prognostic role of coronary atherosclerotic burden in COVID-19 patients.

AIMS: Currently, there are few available data regarding a possible role for subclinical atherosclerosis as a risk factor for mortality in Coronavirus Disease 19 (COVID-19) patients. We used coronary artery calcium (CAC) score derived from chest computed tomography (CT) scan to assess the in-hospital prognostic role of CAC in patients affected by COVID-19 pneumonia. METHODS: Electronic medical records of patients with confirmed diagnosis of COVID-19 were retrospectively reviewed. Patients with known coronary artery disease (CAD) were excluded. A CAC score was calculated for each patient and was used to categorize them into one of four groups: 0, 1-299, 300-999 and at least 1000. The primary endpoint was in-hospital mortality for any cause. RESULTS: The final population consisted of 282 patients. Fifty-seven patients (20%) died over a follow-up time of 40 days. The presence of CAC was detected in 144 patients (51%). Higher CAC score values were observed in nonsurvivors [median: 87, interquartile range (IQR): 0.0-836] compared with survivors (median: 0, IQR: 0.0-136). The mortality rate in patients with a CAC score of at least 1000 was significantly higher than in patients without coronary calcifications (50 vs. 11%) and CAC score 1-299 (50 vs. 23%), P < 0.05. After adjusting for clinical variables, the presence of any CAC categories was not an independent predictor of mortality; however, a trend for increased risk of mortality was observed in patients with CAC of at least 1000. CONCLUSION: The correlation between CAC score and COVID-19 is fascinating and under-explored. However, in multivariable analysis, the CAC score did not show an additional value over more robust clinical variables in predicting in-hospital mortality. Only patients with the highest atherosclerotic burden (CAC ≥1000) could represent a high-risk population, similarly to patients with known CAD.

Repurposing colchicine's journey in view of drug-to-drug interactions. A review.

Colchicine's medical evolution is historically bound to the Mediterranean basin, since remarkable researchers from this region underscored its valuable properties. With the passing of years colchicine became an essential pharmaceutical substance for the treatment of rheumatologic and cardiovascular diseases. In light of recent findings, the therapeutic value of colchicine has grown. In clinical practice, colchicine remains underutilized in view of its proven efficacy and safety. Its complex pharmacokinetics and multifaceted anti-inflammatory role remain under investigation. The current review addresses the safe administration of colchicine in view of key drug to drug interactions. Finally, we are briefly presenting colchicine's future potential applications.

Lopinavir/Ritonavir and Darunavir/Cobicistat in Hospitalized COVID-19 Patients: Findings From the Multicenter Italian CORIST Study.

Background: Protease inhibitors have been considered as possible therapeutic agents for COVID-19 patients. Objectives: To describe the association between lopinavir/ritonavir (LPV/r) or darunavir/cobicistat (DRV/c) use and in-hospital mortality in COVID-19 patients. Study Design: Multicenter observational study of COVID-19 patients admitted in 33 Italian hospitals. Medications, preexisting conditions, clinical measures, and outcomes were extracted from medical records. Patients were retrospectively divided in three groups, according to use of LPV/r, DRV/c or none of them. Primary outcome in a time-to event analysis was death. We used Cox proportional-hazards models with inverse probability of treatment weighting by multinomial propensity scores. Results: Out of 3,451 patients, 33.3% LPV/r and 13.9% received DRV/c. Patients receiving LPV/r or DRV/c were more likely younger, men, had higher C-reactive protein levels while less likely had hypertension, cardiovascular, pulmonary or kidney disease. After adjustment for propensity scores, LPV/r use was not associated with mortality (HR = 0.94, 95% CI 0.78 to 1.13), whereas treatment with DRV/c was associated with a higher death risk (HR = 1.89, 1.53 to 2.34, E-value = 2.43). This increased risk was more marked in women, in elderly, in patients with higher severity of COVID-19 and in patients receiving other COVID-19 drugs. Conclusions: In a large cohort of Italian patients hospitalized for COVID-19 in a real-life setting, the use of LPV/r treatment did not change death rate, while DRV/c was associated with increased mortality. Within the limits of an observational study, these data do not support the use of LPV/r or DRV/c in COVID-19 patients.

A risk score based on baseline risk factors for predicting mortality in COVID-19 patients.

BACKGROUND: To develop a sensitive and clinically applicable risk assessment tool identifying coronavirus disease 2019 (COVID-19) patients with a high risk of mortality at hospital admission. This model would assist frontline clinicians in optimizing medical treatment with limited resources. METHODS: 6415 patients from seven hospitals in Wuhan city were assigned to the training and testing cohorts. A total of 6351 patients from another three hospitals in Wuhan, 2169 patients from outside of Wuhan, and 553 patients from Milan, Italy were assigned to three independent validation cohorts. A total of 64 candidate clinical variables at hospital admission were analyzed by random forest and least absolute shrinkage and selection operator (LASSO) analyses. RESULTS: Eight factors, namely, Oxygen saturation, blood Urea nitrogen, Respiratory rate, admission before the date the national Maximum number of daily new cases was reached, Age, Procalcitonin, C-reactive protein (CRP), and absolute Neutrophil counts, were identified as having significant associations with mortality in COVID-19 patients. A composite score based on these eight risk factors, termed the OURMAPCN-score, predicted the risk of mortality among the COVID-19 patients, with a C-statistic of 0.92 (95% confidence interval [CI] 0.90-0.93). The hazard ratio for all-cause mortality between patients with OURMAPCN-score >11 compared with those with scores ≤ 11 was 18.18 (95% CI 13.93-23.71; p < .0001). The predictive performance, specificity, and sensitivity of the score were validated in three independent cohorts. CONCLUSIONS: The OURMAPCN score is a risk assessment tool to determine the mortality rate in COVID-19 patients based on a limited number of baseline parameters. This tool can assist physicians in optimizing the clinical management of COVID-19 patients with limited hospital resources.

Development and validation of a risk score using complete blood count to predict in-hospital mortality in COVID-19 patients.

BACKGROUND: To develop a sensitive risk score predicting the risk of mortality in patients with coronavirus disease 2019 (COVID-19) using complete blood count (CBC). METHODS: We performed a retrospective cohort study from a total of 13,138 inpatients with COVID-19 in Hubei, China, and Milan, Italy. Among them, 9,810 patients with ≥2 CBC records from Hubei were assigned to the training cohort. CBC parameters were analyzed as potential predictors for all-cause mortality and were selected by the generalized linear mixed model (GLMM). FINDINGS: Five risk factors were derived to construct a composite score (PAWNN score) using the Cox regression model, including platelet counts, age, white blood cell counts, neutrophil counts, and neutrophil:lymphocyte ratio. The PAWNN score showed good accuracy for predicting mortality in 10-fold cross-validation (AUROCs 0.92-0.93) and subsets with different quartile intervals of follow-up and preexisting diseases. The performance of the score was further validated in 2,949 patients with only 1 CBC record from the Hubei cohort (AUROC 0.97) and 227 patients from the Italian cohort (AUROC 0.80). The latent Markov model (LMM) demonstrated that the PAWNN score has good prediction power for transition probabilities between different latent conditions. CONCLUSIONS: The PAWNN score is a simple and accurate risk assessment tool that can predict the mortality for COVID-19 patients during their entire hospitalization. This tool can assist clinicians in prioritizing medical treatment of COVID-19 patients. FUNDING: This work was supported by National Key R&D Program of China (2016YFF0101504, 2016YFF0101505, 2020YFC2004702, 2020YFC0845500), the Key R&D Program of Guangdong Province (2020B1111330003), and the medical flight plan of Wuhan University (TFJH2018006).

EAPCI Position Statement on Invasive Management of Acute Coronary Syndromes during the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic poses an unprecedented challenge to healthcare worldwide. The infection can be life threatening and require intensive care treatment. The transmission of the disease poses a risk to both patients and healthcare workers. The number of patients requiring hospital admission and intensive care may overwhelm health systems and negatively affect standard care for patients presenting with conditions needing emergency interventions. This position statements aims to assist cardiologists in the invasive management of acute coronary syndrome (ACS) patients in the context of the COVID-19 pandemic. To that end, we assembled a panel of interventional cardiologists and acute cardiac care specialists appointed by the European Association of Percutaneous Cardiovascular Interventions (EAPCI) and from the Acute Cardiovascular Care Association (ACVC) and included the experience from the first and worst affected areas in Europe. Modified diagnostic and treatment algorithms are proposed to adapt evidence-based protocols for this unprecedented challenge. Various clinical scenarios, as well as management algorithms for patients with a diagnosed or suspected COVID-19 infection, presenting with ST- and non-ST-segment elevation ACS are described. In addition, we address the need for re-organization of ACS networks, with redistribution of hub and spoke hospitals, as well as for in-hospital reorganization of emergency rooms and cardiac units, with examples coming from multiple European countries. Furthermore, we provide a guidance to reorganization of catheterization laboratories and, importantly, measures for protection of healthcare providers involved with invasive procedures.

Characterization of Myocardial Injury in Patients With COVID-19.

BACKGROUND: Myocardial injury is frequent among patients hospitalized with coronavirus disease-2019 (COVID-19) and is associated with a poor prognosis. However, the mechanisms of myocardial injury remain unclear and prior studies have not reported cardiovascular imaging data. OBJECTIVES: This study sought to characterize the echocardiographic abnormalities associated with myocardial injury and their prognostic impact in patients with COVID-19. METHODS: We conducted an international, multicenter cohort study including 7 hospitals in New York City and Milan of hospitalized patients with laboratory-confirmed COVID-19 who had undergone transthoracic echocardiographic (TTE) and electrocardiographic evaluation during their index hospitalization. Myocardial injury was defined as any elevation in cardiac troponin at the time of clinical presentation or during the hospitalization. RESULTS: A total of 305 patients were included. Mean age was 63 years and 205 patients (67.2%) were male. Overall, myocardial injury was observed in 190 patients (62.3%). Compared with patients without myocardial injury, those with myocardial injury had more electrocardiographic abnormalities, higher inflammatory biomarkers and an increased prevalence of major echocardiographic abnormalities that included left ventricular wall motion abnormalities, global left ventricular dysfunction, left ventricular diastolic dysfunction grade II or III, right ventricular dysfunction and pericardial effusions. Rates of in-hospital mortality were 5.2%, 18.6%, and 31.7% in patients without myocardial injury, with myocardial injury without TTE abnormalities, and with myocardial injury and TTE abnormalities. Following multivariable adjustment, myocardial injury with TTE abnormalities was associated with higher risk of death but not myocardial injury without TTE abnormalities. CONCLUSIONS: Among patients with COVID-19 who underwent TTE, cardiac structural abnormalities were present in nearly two-thirds of patients with myocardial injury. Myocardial injury was associated with increased in-hospital mortality particularly if echocardiographic abnormalities were present.

Common cardiovascular risk factors and in-hospital mortality in 3,894 patients with COVID-19: survival analysis and machine learning-based findings from the multicentre Italian CORIST Study.

BACKGROUND AND AIMS: There is poor knowledge on characteristics, comorbidities and laboratory measures associated with risk for adverse outcomes and in-hospital mortality in European Countries. We aimed at identifying baseline characteristics predisposing COVID-19 patients to in-hospital death. METHODS AND RESULTS: Retrospective observational study on 3894 patients with SARS-CoV-2 infection hospitalized from February 19th to May 23rd, 2020 and recruited in 30 clinical centres distributed throughout Italy. Machine learning (random forest)-based and Cox survival analysis. 61.7% of participants were men (median age 67 years), followed up for a median of 13 days. In-hospital mortality exhibited a geographical gradient, Northern Italian regions featuring more than twofold higher death rates as compared to Central/Southern areas (15.6% vs 6.4%, respectively). Machine learning analysis revealed that the most important features in death classification were impaired renal function, elevated C reactive protein and advanced age. These findings were confirmed by multivariable Cox survival analysis (hazard ratio (HR): 8.2; 95% confidence interval (CI) 4.6-14.7 for age ≥85 vs 18-44 y); HR = 4.7; 2.9-7.7 for estimated glomerular filtration rate levels <15 vs ≥ 90 mL/min/1.73 m2; HR = 2.3; 1.5-3.6 for C-reactive protein levels ≥10 vs ≤ 3 mg/L). No relation was found with obesity, tobacco use, cardiovascular disease and related-comorbidities. The associations between these variables and mortality were substantially homogenous across all sub-groups analyses. CONCLUSIONS: Impaired renal function, elevated C-reactive protein and advanced age were major predictors of in-hospital death in a large cohort of unselected patients with COVID-19, admitted to 30 different clinical centres all over Italy.

Early detection of elevated cardiac biomarkers to optimise risk stratification in patients with COVID-19.

OBJECTIVE: Risk stratification is crucial to optimise treatment strategies in patients with COVID-19. We aimed to evaluate the impact on mortality of an early assessment of cardiac biomarkers in patients with COVID-19. METHODS: Humanitas Clinical and Research Hospital (Rozzano-Milan, Lombardy, Italy) is a tertiary centre that has been converted to the management of COVID-19. Patients with confirmed COVID-19 were entered in a dedicated database for cohort observational analyses. Outcomes were stratified according to elevated levels (ie, above the upper level of normal) of high-sensitivity cardiac troponin I (hs-TnI), B-type natriuretic peptide (BNP) or both measured within 24 hours after hospital admission. The primary outcome was all-cause mortality. RESULTS: A total of 397 consecutive patients with COVID-19 were included up to 1 April 2020. At the time of hospital admission, 208 patients (52.4%) had normal values for cardiac biomarkers, 90 (22.7%) had elevated both hs-TnI and BNP, 59 (14.9%) had elevated only BNP and 40 (10.1%) had elevated only hs-TnI. The rate of mortality was higher in patients with elevated hs-TnI (22.5%, OR 4.35, 95% CI 1.72 to 11.04), BNP (33.9%, OR 7.37, 95% CI 3.53 to 16.75) or both (55.6%, OR 18.75, 95% CI 9.32 to 37.71) as compared with those without elevated cardiac biomarkers (6.25%). A multivariate analysis identified concomitant elevation of both hs-TnI and BNP as a strong independent predictor of all-cause mortality (OR 3.24, 95% CI 1.06 to 9.93). CONCLUSIONS: An early detection of elevated hs-TnI and BNP predicts mortality in patients with COVID-19. Cardiac biomarkers should be systematically assessed in patients with COVID-19 at the time of hospital admission in order to optimise risk stratification.