ABSTRACT
Background: MessengerRNA (mRNA) COVID-19 vaccination has been associated with a higher-than-expected occurrence of acute myocarditis. Scarce information is available on mid-term prognosis and changes in cardiac function, volumes, and tissue characterization on cardiac magnetic resonance (CMR). Method(s): Retrospective, multicenter study including patients with a definite diagnosis of acute myocarditis within 30 days from mRNA COVID-19 vaccination, with a confirmed myocarditis diagnosis based on endomyocardial biopsy (EMB) or autopsy or by the coexistence of positive biomarkers (troponin >99th upper reference limit or elevated creatine kinase myocardial band [CK-MB]) and cardiac MRI findings consistent with AM according to the 2018 updated Lake Louise Criteria. Result(s): 77 patients (median age 25 years [IQR 20-35], 15% female) were included and followed-up for 147 days [IQR 74-215]. Follow-up CMR was available in n=49 patients and showed no changes in biventricular ejection fraction (EF) as compared to CMR at diagnosis (left ventricular EF: 59%[55-65]vs. 60%[57-64], p=0.507, right ventricular EF: 56%[52-62]vs. 57%[52-61], p=0.563, respectively). Late gadolinium enhancement was present in all patients at diagnosis and persisted in only n=39 (79.6%) at follow-up (p=0.001), generally sparing the anterior wall and the septum. N=10 (20.4%) had a persistent edema based on T2-weighted short tau inversion recovery (STIR) sequences, with predominant involvement of inferior or inferiorlateral walls. The proportion of patients with increased T1 and T2 mapping signals significantly decreased at follow-up (n=13 (68%) vs. n=4 (13%),p<0.001, and n=21 (84%) vs. n=3 (10%),p<0.001, respectively), as well as the presence of pericardial effusion (n=16 (33%) vs. n=3 (6%),p=0.004). No differences in morpho-functional CMR parameters based on the type of vaccine administered were found (BNT162b2 Pfizer/BioNTech, n=36, 73.5%, m-RNA-1273 Moderna, n=13, 26.5%). Among patients with available follow-up (N=75, 97.4%), no major adverse cardiovascular events nor myocarditis recurrence or death were reported. Conclusion(s): At mid-term follow-up, patients who experienced an acute myocarditis after a mRNA COVID-19 vaccine had preserved biventricular EF. The rate and localization of residual scar or edema on CMR is in line with classic viral myocarditis with a good prognosis. This new piece of information should further reassure patients who experience acute myocarditis after mRNA COVID-19 vaccination.
ABSTRACT
Aims: Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Prediction models are needed to optimize clinical management and to early stratify patients at a higher mortality risk. Machine learning (ML) algorithms represent a novel approach to identify a prediction model with a good discriminatory capacity to be easily used in clinical practice. Methods and results: The Cardio-COVID is a multicentre observational study that involved a cohort of consecutive adult Caucasian patients with laboratory-confirmed COVID-19 [by real time reverse transcriptase-polymerase chain reaction (RT-PCR)] who were hospitalized in 13 Italian cardiology units from 1 March to 9 April 2020. Patients were followed-up after the COVID-19 diagnosis and all causes in-hospital mortality or discharge were ascertained until 23 April 2020. Variables with more than 20% of missing values were excluded. The Lasso procedure was used with a λ=0.07 for reducing the covariates number. Mortality was estimated by means of a Random Forest (RF). The dataset was randomly divided in two subsamples with the same percentage of death/alive people of the entire sample: training set contained 80% of the data and test set the remaining 20%. The training set was used in the calibration procedure where a RF models in-hospital mortality with the covariates selected by Lasso. Its accuracy was measured by means of the ROC curve, obtaining AUC, sensitivity, specificity, and related 95% confidence interval (CI) computed with 10 000 stratified bootstrap replicates. From the RF the relative Variable Importance Measure (relVIM) was extracted to understand which of the selected variables had the greatest impact on outcome, providing a ranking from the most (relVIM=100) to the less important variable. The model obtained was compared with the Gradient Boosting Machine (GBM) and with the logistic regression, where the predictions were cross validated. Finally, to understand if each model has the same performance in sample (training) and out of sample (test), the two AUCs were compared by means of the DeLong's test. Among 701 patients enrolled (mean age 67.2±13.2 years, 69.5% males), 165 (23.5%) died during a median hospitalization of 15 (IQR, 9-24) days. Variables selected by the Lasso were: age, Oxygen saturation, PaO2/FiO2, Creatinine Clearance and elevated Troponin. Compared with those who survived, deceased patients were older, had a lower blood oxygenation, a lower creatinine clearance levels and higher prevalence of elevated Troponin (all P<0.001). Training set included 561 patients and test set 140 patients. The best performance out of sample was provided by the RF with an AUC of 0.78 (95% CI: 0.68-0.88) and a sensitivity of 0.88 (95% CI: 0.58-1.00). Moreover, RF is the unique methodology that provided similar performance in sample and out of sample (DeLong test P=0.78). On the contrary, prediction model was less accurate by using GBM and logistic regression. The relVIM ranked the variables from the most to the less important in predicting the outcome as follows: clearance creatinine, PaO2/FiO2, age, oxygen saturation, and elevated Troponin. Conclusions: In a large COVID-19 population, we showed that a customizable MLbased score derived from clinical variables, is feasible and effective for the prediction of in-hospital mortality.
ABSTRACT
Background: Long-term effects of Coronavirus Disease of 2019 (COVID- 19) and their sustainability are of the utmost relevance. For the chronic phase, the main concerns are the development of pulmonary interstitial disease and/or lingering cardiovascular involvement. How to intercept, assess, and treat these patients with long-term consequences of COVID-19 remains uncertain. Purpose: We aimed to determine: 1) functional capacity of COVID-19 survivors by cardiopulmonary exercise testing (CPET);2) those characteristics associated with CPET performance;3) safety and tolerability of CPET. Methods: We prospectively enrolled consecutive patients with laboratoryconfirmed COVID-19 discharged alive at a single hospital in northern Italy. At 3-month from hospital discharge, complete clinical evaluation, transthoracic echocardiography, cardiopulmonary exercise testing (CPET), pulmonary function test (PFT), and dominant leg extension (DLE) maximal strength evaluation were performed. Results: From 225 patients discharged from March to November 2020 we excluded 12 incomplete/missing cases, and 13 unable to perform CPET leading to a final population of 200 patients. At PFT all median parameters were within normality range. Median percent-predicted peak oxygen uptake (%pVO2) was 88% (78.3- 103.1). Ninety-nine (49.5%) patients had %pVO2 below, whereas 101 (50.5%) above the 85% predicted value (indicating normality). Sixteen (16.2%) patients had respiratory, 28 (28.9%) cardiac, 21 (21.2%) mixed-cardiopulmonary, and 34 (34.3%) non-cardiopulmonary limitation of exercise. One-hundred sixty (80.0%) patients complain at least one symptom, without relationship with peakVO2. Multivariate linear regression analysis showed percent-predicted forced expiratory volume in one-second (β=5.29, p=0.023), percent-predicted diffusing capacity of lungs for carbon monoxide (β=6.31, p=0.001), and DLE maximal strength (β=14.09, p=0.008) independently associated with peakVO2. At sensitivity analysis, the results of previous multivariate linear regression analysis were also similar among sub-groups of patients with no previous significant disease in anamnesis (cardiovascular disease except for arterial hypertension, respiratory disease, kidney disease, or cancer) and of those with a length of hospital stay ≤7 days. None major event was reported during/after CPET, whereas only two cases (1.0%) had a mild symptomatic hypotension post exercise. None of the involved health professionals developed COVID-19. Conclusions: CPET after COVID-19 is safe and about 1/3rd of COVID-19 survivors show functional capacity limitation mainly explained by muscular impairment, calling for future research to identify patients at higher risk of long-term effects that may benefit from careful surveillance and targeted rehabilitation. (Figure Presented).
ABSTRACT
BACKGROUND: Investigations demonstrated a decrease of admissions for myocardial infarction (MI) during the CoronaVirus Disease-19 (COVID-19) outbreak. No study has evaluated the time required to reverse this downward curve of MI admissions. METHODS: This is a retrospective analysis on patients (N = 2415) admitted to the Emergency Departments for acute MI in nine Italian centers. Primary endpoint was the incidence rates (IRs) of MI admissions in the post-lockdown COVID-19 period (case-period: from May 4 to July 12, 2020) vs. the following control periods: January 1-February 19, 2020 (pre-lockdown period);February 20-May 3, 2020 (intra-lockdown period);May 4-July 12, 2019 (inter-year non-COVID-19 period). RESULTS: IR of admissions for MI in the post-lockdown period was higher than the intra-lockdown period (IR ratio, IRR: 1.60, 95% CI 1.42-1.81;p = 0.0001), was lower than the pre-lockdown period (IRR: 0.86, 0.77-0.96;p = 0.009) and similar to the inter-year non-COVID-19 period (IRR: 0.96, 0.87-1.07;p = 0.47). Within the case period, the increase in MI admissions was more pronounced in earlier vs later weeks (IRR 1.19, 95% CI 1.02-1.38, p = 0.024) and, compared to the inter-year control period, was significant for non ST-segment elevation MI (IRR: 1.25, 95% CI 1.08-1.46, p = 0.004), but was not observed for ST-segment elevation MI (STEMI), where hospitalizations were reduced (IRR 0.76, 95% CI 0.65-0.88, p = 0.0001). CONCLUSIONS: Our study first indicates an increase in the number of admissions for MI after the removal of the national lockdown for COVID-19 in Italy. This increase was prevalent in the first weeks following the lockdown removal, but was under-represented in STEMI patients.