COVID-19 Pneumonia with Migratory Pattern in Agammaglobulinemic Patients: A Report of Two Cases and Review of Literature.

X-linked agammaglobulinemia (XLA) is a primary immunodeficiency characterized by marked reduction in serum immunoglobulins and early-onset infections. Coronavirus Disease-2019 (COVID-19) pneumonia in immunocompromised patients presents clinical and radiological peculiarities which have not yet been completely understood. Very few cases of agammaglobulinemic patients with COVID-19 have been reported since the beginning of the pandemic in February 2020. We report two cases of migrant COVID-19 pneumonia in XLA patients.

Machine learning for prediction of in-hospital mortality in coronavirus disease 2019 patients: results from an Italian multicenter study.

BACKGROUND: Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Machine learning algorithms represent a novel approach to identifying a prediction model with a good discriminatory capacity to be easily used in clinical practice. The aim of this study was to obtain a risk score for in-hospital mortality in patients with coronavirus disease infection (COVID-19) based on a limited number of features collected at hospital admission. METHODS AND RESULTS: We studied an Italian cohort of consecutive adult Caucasian patients with laboratory-confirmed COVID-19 who were hospitalized in 13 cardiology units during Spring 2020. The Lasso procedure was used to select the most relevant covariates. The dataset was randomly divided into a training set containing 80% of the data, used for estimating the model, and a test set with the remaining 20%. A Random Forest modeled in-hospital mortality with the selected set of covariates: its accuracy was measured by means of the ROC curve, obtaining AUC, sensitivity, specificity and related 95% confidence interval (CI). This model was then compared with the one obtained by the Gradient Boosting Machine (GBM) and with logistic regression. Finally, to understand if each model has the same performance in the training and test set, the two AUCs were compared using the DeLong's test. Among 701 patients enrolled (mean age 67.2 ±â€Š13.2 years, 69.5% male individuals), 165 (23.5%) died during a median hospitalization of 15 (IQR, 9-24) days. Variables selected by the Lasso procedure 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, lower creatinine clearance levels and higher prevalence of elevated troponin (all P < 0.001). The best performance out of the samples was provided by Random Forest 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, Random Forest was the unique model that provided similar performance in sample and out of sample (DeLong test P = 0.78). CONCLUSION: In a large COVID-19 population, we showed that a customizable machine learning-based score derived from clinical variables is feasible and effective for the prediction of in-hospital mortality.

Low-dose Lung Radiotherapy for COVID-19-related Pneumonia: Preliminary Results of the Italian Mono-institutional COLOR-19 Trial.

AIM: To evaluate the feasibility and tolerability of low-dose radiotherapy (LDRT) delivered to both lungs in the treatment of SARS-CoV-2-immune-mediated pneumonia in the COLOR-19 study (NCT0437747). PATIENTS AND METHODS: From May 2020 to April 2021 at Brescia University Radiation Oncology Department, three patients with COVID-19-related pneumonia were treated with LDRT according to the COLOR-19 protocol. All patients were treated with a single fraction at the average prescription dose of 0.7 Gy to both lungs. RESULTS: Three patients were enrolled (two males and one female, aged 61-81 years) and underwent LDRT. Despite LDRT being safely performed without significant side-effects, two patients died (one 81-year-old male due to septic shock secondary to Escherichia coli infection and one 79-year-old male, already in poor condition, due to worsening of COVID-19). The remaining female patient (61 years old) underwent LDRT for less severe COVID-19: her clinical condition and chest X-ray improved, and she was discharged home completely asymptomatic 27 days after hospital admission. Blood levels of C-reactive protein and ferritin generally decreased after LDRT. CONCLUSION: Early results of the COLOR-19 study demonstrate the feasibility of LDRT for therapy of COVID-19-related pneumonia; no conclusions on the efficacy have been reached due to poor accrual.

Chest X-ray versus chest computed tomography for outcome prediction in hospitalized patients with COVID-19.

The purpose of this study was to compare the prognostic value of chest X-ray (CXR) and chest computed tomography (CT) in a group of hospitalized patients with COVID-19. For this study, we retrospectively selected a cohort of 106 hospitalized patients with COVID-19 who underwent both CXR and chest CT at admission. For each patient, the pulmonary involvement was ranked by applying the Brixia score for CXR and the percentage of well-aerated lung (WAL) for CT. The Brixia score was assigned at admission (A-Brixia score) and during hospitalization. During hospitalization, only the highest score (H-Brixia score) was considered. At admission, the percentage of WAL (A-CT%WAL) was quantified using a dedicated software. On logistic regression analyses, H-Brixia score was the most effective radiological marker for predicting in-hospital mortality and invasive mechanical ventilation. Additionally, A-CT%WAL did not provide substantial advantages in the risk stratification of hospitalized patients with COVID-19 compared to A-Brixia score.

Early prediction of in-hospital death of COVID-19 patients: a machine-learning model based on age, blood analyses, and chest x-ray score.

An early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED) was developed and validated using a machine-learning model. In total, 2782 patients were enrolled between March 2020 and December 2020, including 2106 patients (first wave) and 676 patients (second wave) in the COVID-19 outbreak in Italy. The first-wave patients were divided into two groups with 1474 patients used to train the model, and 632 to validate it. The 676 patients in the second wave were used to test the model. Age, 17 blood analytes, and Brescia chest X-ray score were the variables processed using a random forests classification algorithm to build and validate the model. Receiver operating characteristic (ROC) analysis was used to assess the model performances. A web-based death-risk calculator was implemented and integrated within the Laboratory Information System of the hospital. The final score was constructed by age (the most powerful predictor), blood analytes (the strongest predictors were lactate dehydrogenase, D-dimer, neutrophil/lymphocyte ratio, C-reactive protein, lymphocyte %, ferritin std, and monocyte %), and Brescia chest X-ray score (https://bdbiomed.shinyapps.io/covid19score/). The areas under the ROC curve obtained for the three groups (training, validating, and testing) were 0.98, 0.83, and 0.78, respectively. The model predicts in-hospital mortality on the basis of data that can be obtained in a short time, directly at the ED on admission. It functions as a web-based calculator, providing a risk score which is easy to interpret. It can be used in the triage process to support the decision on patient allocation.

BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset.

In this work we design an end-to-end deep learning architecture for predicting, on Chest X-rays images (CXR), a multi-regional score conveying the degree of lung compromise in COVID-19 patients. Such semi-quantitative scoring system, namely Brixia score, is applied in serial monitoring of such patients, showing significant prognostic value, in one of the hospitals that experienced one of the highest pandemic peaks in Italy. To solve such a challenging visual task, we adopt a weakly supervised learning strategy structured to handle different tasks (segmentation, spatial alignment, and score estimation) trained with a "from-the-part-to-the-whole" procedure involving different datasets. In particular, we exploit a clinical dataset of almost 5,000 CXR annotated images collected in the same hospital. Our BS-Net demonstrates self-attentive behavior and a high degree of accuracy in all processing stages. Through inter-rater agreement tests and a gold standard comparison, we show that our solution outperforms single human annotators in rating accuracy and consistency, thus supporting the possibility of using this tool in contexts of computer-assisted monitoring. Highly resolved (super-pixel level) explainability maps are also generated, with an original technique, to visually help the understanding of the network activity on the lung areas. We also consider other scores proposed in literature and provide a comparison with a recently proposed non-specific approach. We eventually test the performance robustness of our model on an assorted public COVID-19 dataset, for which we also provide Brixia score annotations, observing good direct generalization and fine-tuning capabilities that highlight the portability of BS-Net in other clinical settings. The CXR dataset along with the source code and the trained model are publicly released for research purposes.

Lombardy, Northern Italy: COVID-19 second wave less severe and deadly than the first? A preliminary investigation.

BACKGROUND: The much-heralded second wave of coronavirus disease (COVID-19) has arrived in Italy. Right now, one of the main questions about COVID-19 is whether the second wave is less severe and deadly than the first wave. In order to answer this challenging question, we decided to evaluate the chest X-ray (CXR) severity of COVID-19 pneumonia, the mechanical ventilation (MV) use, the patient outcome, and certain clinical/laboratory data during the second wave and compare them with those of the first wave. METHODS: During the two COVID-19 waves two independent groups of hospitalised patients were selected. The first group consisted of the first 100 COVID-19 patients admitted to our hospital during the first wave. The second group consisted of another 100 consecutive COVID-19 patients admitted to our hospital during the second wave. We enlisted only Caucasian male patients over the age of fifty for whom the final outcome was available. For each patient, the CXR severity of COVID-19 pneumonia, the MV use, the patient outcome, comorbidities, corticosteroid use, and C-reactive protein (CRP) levels were considered. Nonparametric statistical tests were used to compare the data obtained from the two waves. RESULTS: The CXR severity of COVID-19 pneumonia, the in-hospital mortality, and CRP levels were significantly higher in the first wave than in the second wave (p ≤ .041). Although not statistically significant, the frequency of MV use was higher in the first wave. CONCLUSIONS: This preliminary investigation seems to confirm that the COVID-19 second wave is less severe and deadly than the first wave.

Which role for chest x-ray score in predicting the outcome in COVID-19 pneumonia?

OBJECTIVE: We aim to demonstrate that a chest X-ray (CXR) scoring system for COVID-19 patients correlates with patient outcome and has a prognostic value. METHODS: This retrospective study included CXRs of COVID-19 patients that reported the Brixia score, a semi-quantitative scoring system rating lung involvement from 0 to 18. The highest (H) and lowest (L) values were registered along with scores on admission (A) and end of hospitalization (E). The Brixia score was correlated with the outcome (death or discharge). RESULTS: A total of 953 patients met inclusion criteria. In total, 677/953 were discharged and 276/953 died during hospitalization. A total of 524/953 had one CXR and 429/953 had more than one CXR. H-score was significantly higher in deceased (median, 12; IQR 9-14) compared to that in discharged patients (median, 8; IQR 5-11) (p < 0.0001). In 429/953 patients with multiple CXR, A-score, L-score, and E-score were higher in deceased than in discharged patients (A-score 9 vs 8; p = 0.039; L-score 7 vs 5; p < 0.0003; E-score 12 vs 7; p < 0.0001). In the entire cohort, logistic regression showed a significant predictive value for age (p < 0.0001, OR 1.13), H-score (p < 0.0001, OR 1.25), and gender (p = 0.01, male OR 1.67). AUC was 0.863. In patients with ≥ 2 CXR, A-, L-, and E-scores correlated significantly with the outcome. Cox proportional hazards regression indicated age (p < 0.0001, HR 4.17), H-score (< 9, HR 0.36, p = 0.0012), and worsening of H-score vs A score > 3 (HR 1.57, p = 0.0227) as associated with worse outcome. CONCLUSIONS: The Brixia score correlates strongly with disease severity and outcome; it may support the clinical decision-making, particularly in patients with moderate-to-severe signs and symptoms. The Brixia score should be incorporated in a prognostic model, which would be desirable, particularly in resource-constraint scenarios. KEY POINTS: • To demonstrate the importance of the Brixia score in assessing and monitoring COVID-19 lung involvement. • The Brixia score strongly correlates with patient outcome and can be easily implemented in the routine reporting of CXR.

Characteristics and outcomes of patients hospitalized for COVID-19 and cardiac disease in Northern Italy.

AIMS: To compare demographic characteristics, clinical presentation, and outcomes of patients with and without concomitant cardiac disease, hospitalized for COVID-19 in Brescia, Lombardy, Italy. METHODS AND RESULTS: The study population includes 99 consecutive patients with COVID-19 pneumonia admitted to our hospital between 4 March and 25 March 2020. Fifty-three patients with a history of cardiac disease were compared with 46 without cardiac disease. Among cardiac patients, 40% had a history of heart failure, 36% had atrial fibrillation, and 30% had coronary artery disease. Mean age was 67 ± 12 years, and 80 (81%) patients were males. No differences were found between cardiac and non-cardiac patients except for higher values of serum creatinine, N-terminal probrain natriuretic peptide, and high sensitivity troponin T in cardiac patients. During hospitalization, 26% patients died, 15% developed thrombo-embolic events, 19% had acute respiratory distress syndrome, and 6% had septic shock. Mortality was higher in patients with cardiac disease compared with the others (36% vs. 15%, log-rank P = 0.019; relative risk 2.35; 95% confidence interval 1.08-5.09). The rate of thrombo-embolic events and septic shock during the hospitalization was also higher in cardiac patients (23% vs. 6% and 11% vs. 0%, respectively). CONCLUSIONS: Hospitalized patients with concomitant cardiac disease and COVID-19 have an extremely poor prognosis compared with subjects without a history of cardiac disease, with higher mortality, thrombo-embolic events, and septic shock rates.

Factors Associated With Surgical Mortality and Complications Among Patients With and Without Coronavirus Disease 2019 (COVID-19) in Italy.

Importance: There are limited data on mortality and complications rates in patients with coronavirus disease 2019 (COVID-19) who undergo surgery. Objective: To evaluate early surgical outcomes of patients with COVID-19 in different subspecialties. Design, Setting, and Participants: This matched cohort study conducted in the general, vascular and thoracic surgery, orthopedic, and neurosurgery units of Spedali Civili Hospital (Brescia, Italy) included patients who underwent surgical treatment from February 23 to April 1, 2020, and had positive test results for COVID-19 either before or within 1 week after surgery. Gynecological and minor surgical procedures were excluded. Patients with COVID-19 were matched with patients without COVID-19 with a 1:2 ratio for sex, age group, American Society of Anesthesiologists score, and comorbidities recorded in the surgical risk calculator of the American College of Surgeons National Surgical Quality Improvement Program. Patients older than 65 years were also matched for the Clinical Frailty Scale score. Exposures: Patients with positive results for COVID-19 and undergoing surgery vs matched surgical patients without infection. Screening for COVID-19 was performed with reverse transcriptase-polymerase chain reaction assay in nasopharyngeal swabs, chest radiography, and/or computed tomography. Diagnosis of COVID-19 was based on positivity of at least 1 of these investigations. Main Outcomes and Measures: The primary end point was early surgical mortality and complications in patients with COVID-19; secondary end points were the modeling of complications to determine the importance of COVID-19 compared with other surgical risk factors. Results: Of 41 patients (of 333 who underwent operation during the same period) who underwent mainly urgent surgery, 33 (80.5%) had positive results for COVID-19 preoperatively and 8 (19.5%) had positive results within 5 days from surgery. Of the 123 patients of the combined cohorts (78 women [63.4%]; mean [SD] age, 76.6 [14.4] years), 30-day mortality was significantly higher for those with COVID-19 compared with control patients without COVID-19 (odds ratio [OR], 9.5; 95% CI, 1.77-96.53). Complications were also significantly higher (OR, 4.98; 95% CI, 1.81-16.07); pulmonary complications were the most common (OR, 35.62; 95% CI, 9.34-205.55), but thrombotic complications were also significantly associated with COVID-19 (OR, 13.2; 95% CI, 1.48-∞). Different models (cumulative link model and classification tree) identified COVID-19 as the main variable associated with complications. Conclusions and Relevance: In this matched cohort study, surgical mortality and complications were higher in patients with COVID-19 compared with patients without COVID-19. These data suggest that, whenever possible, surgery should be postponed in patients with COVID-19.

Chest X-ray severity index as a predictor of in-hospital mortality in coronavirus disease 2019: A study of 302 patients from Italy.

OBJECTIVES: This study aimed to assess the usefulness of a new chest X-ray scoring system - the Brixia score - to predict the risk of in-hospital mortality in hospitalized patients with coronavirus disease 2019 (COVID-19). METHODS: Between March 4, 2020 and March 24, 2020, all CXR reports including the Brixia score were retrieved. We enrolled only hospitalized Caucasian patients with COVID-19 for whom the final outcome was available. For each patient, age, sex, underlying comorbidities, immunosuppressive therapies, and the CXR report containing the highest score were considered for analysis. These independent variables were analyzed using a multivariable logistic regression model to extract the predictive factors for in-hospital mortality. RESULTS: 302 Caucasian patients who were hospitalized for COVID-19 were enrolled. In the multivariable logistic regression model, only Brixia score, patient age, and conditions that induced immunosuppression were the significant predictive factors for in-hospital mortality. According to receiver operating characteristic curve analyses, the optimal cutoff values for Brixia score and patient age were 8 points and 71 years, respectively. Three different models that included the Brixia score showed excellent predictive power. CONCLUSIONS: Patients with a high Brixia score and at least one other predictive factor had the highest risk of in-hospital death.

Acute pulmonary embolism in COVID-19 disease: Preliminary report on seven patients.

There is some evidence that Covid 19 pneumonia is associated with prothrombotic status and increased risk of venous thromboembolic events (deep venous thrombosis and pulmonary embolism). Over a two-week period we admitted in our Unit 25 patients with Covid-19 pneumonia, of these pulmonary embolism was diagnosed using computed tomography angiography in 7. We report on clinical and biochemical features of these patients. They were all males, with a mean age of 70.3 years (range 58-84); traditional risk factors for venous thromboembolism were identified in the majority of patients with pulmonary embolism, however not differently from those without pulmonary embolism. Clinical presentation of pulmonary embolism patients was usually characterized by persistence or worsening of respiratory symptoms, with increasing oxygen requirement. D-dimer levels were several fold higher than the upper threshold of normal; in patients in whom PE was recognized during hospital stay, a rapid and relevant increase of D-dimer levels was observed. Computed tomographic findings ranged from massive acute pulmonary embolism to a segmental or sub-segmental pattern; furthermore, thrombosis of sub-segmental pulmonary arteries within lung infiltrates were occasionally seen, suggesting local mechanisms. Six out of 7 patients were treated with unfractionated or low molecular weight heparin with clinical benefit within few days; one patient needed systemic thrombolysis (death from hemorrhagic complication).

Tocilizumab for the treatment of severe COVID-19 pneumonia with hyperinflammatory syndrome and acute respiratory failure: A single center study of 100 patients in Brescia, Italy.

A hyperinflammatory syndrome (HIS) may cause a life-threatening acute respiratory distress syndrome (ARDS) in patients with COVID-19 pneumonia. A prospective series of 100 consecutive patients admitted to the Spedali Civili University Hospital in Brescia (Italy) between March 9th and March 20th with confirmed COVID-19 pneumonia and ARDS requiring ventilatory support was analyzed to determine whether intravenous administration of tocilizumab (TCZ), a monoclonal antibody that targets the interleukin 6 (IL-6) receptor, was associated with improved outcome. Tocilizumab was administered at a dosage of 8 mg/kg by two consecutive intravenous infusions 12 h apart. A third infusion was optional based on clinical response. The outcome measure was an improvement in acute respiratory failure assessed by means of the Brescia COVID Respiratory Severity Score (BCRSS 0 to 8, with higher scores indicating higher severity) at 24-72 h and 10 days after tocilizumab administration. Out of 100 treated patients (88 M, 12 F; median age: 62 years), 43 received TCZ in the intensive care unit (ICU), while 57 in the general ward as no ICU beds were available. Of these 57 patients, 37 (65%) improved and suspended noninvasive ventilation (NIV) (median BCRSS: 1 [IQR 0-2]), 7 (12%) patients remained stable in NIV, and 13 (23%) patients worsened (10 died, 3 were admitted to ICU). Of the 43 patients treated in the ICU, 32 (74%) improved (17 of them were taken off the ventilator and were discharged to the ward), 1 (2%) remained stable (BCRSS: 5) and 10 (24%) died (all of them had BCRSS≥7 before TCZ). Overall at 10 days, the respiratory condition was improved or stabilized in 77 (77%) patients, of whom 61 showed a significant clearing of diffuse bilateral opacities on chest x-ray and 15 were discharged from the hospital. Respiratory condition worsened in 23 (23%) patients, of whom 20 (20%) died. All the patients presented with lymphopenia and high levels of C-reactive protein (CRP), fibrinogen, ferritin and IL-6 indicating a HIS. During the 10-day follow-up, three cases of severe adverse events were recorded: two patients developed septic shock and died, one had gastrointestinal perforation requiring urgent surgery and was alive at day 10. In conclusion, our series showed that COVID-19 pneumonia with ARDS was characterized by HIS. The response to TCZ was rapid, sustained, and associated with significant clinical improvement.

COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a new virus recently isolated from humans. SARS-CoV-2 was discovered to be the pathogen responsible for a cluster of pneumonia cases associated with severe respiratory disease that occurred in December 2019 in China. This novel pulmonary infection, formally called Coronavirus Disease 2019 (COVID-19), has spread rapidly in China and beyond. On 8 March 2020, the number of Italians with SARS-CoV-2 infection was 7375 with a 48% hospitalization rate. At present, chest-computed tomography imaging is considered the most effective method for the detection of lung abnormalities in early-stage disease and quantitative assessment of severity and progression of COVID-19 pneumonia. Although chest X-ray (CXR) is considered not sensitive for the detection of pulmonary involvement in the early stage of the disease, we believe that, in the current emergency setting, CXR can be a useful diagnostic tool for monitoring the rapid progression of lung abnormalities in infected patients, particularly in intensive care units. In this short communication, we present our experimental CXR scoring system that we are applying to hospitalized patients with COVID-19 pneumonia to quantify and monitor the severity and progression of this new infectious disease. We also present the results of our preliminary validation study on a sample of 100 hospitalized patients with SARS-CoV-2 infection for whom the final outcome (recovery or death) was available.

Radiographic severity index in COVID-19 pneumonia: relationship to age and sex in 783 Italian patients.

PURPOSE: To improve the risk stratification of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an experimental chest X-ray (CXR) scoring system for quantifying lung abnormalities was introduced in our Diagnostic Imaging Department. The purpose of this study was to retrospectively evaluate correlations between the CXR score and the age or sex of Italian patients infected with SARS-CoV-2. MATERIALS AND METHODS: Between March 4, 2020, and March 18, 2020, all CXR reports containing the new scoring system were retrieved. Only hospitalized patients with SARS-CoV-2 infection were enrolled. For each patient, age, sex, and the CXR report containing the highest score were considered for the analysis. Patients were also divided into seven groups according to age. Nonparametric statistical tests were used to examine the relationship between the severity of lung disease and the age or sex. RESULTS: 783 Italian patients (532 males and 251 females) with SARS-CoV-2 infection were enrolled. The CXR score was significantly higher in males than in females only in groups aged 50 to 79 years. A significant correlation was observed between the CXR score and age in both males and females. Males aged 50 years or older and females aged 80 years or older with coronavirus disease 2019 showed the highest CXR score (median ≥ 8). CONCLUSIONS: Males aged 50 years or older and females aged 80 years or older showed the highest risk of developing severe lung disease. Our results may help to identify the highest-risk patients and those who require specific treatment strategies.

Cardiac Involvement in a Patient With Coronavirus Disease 2019 (COVID-19).

Importance: Virus infection has been widely described as one of the most common causes of myocarditis. However, less is known about the cardiac involvement as a complication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Objective: To describe the presentation of acute myocardial inflammation in a patient with coronavirus disease 2019 (COVID-19) who recovered from the influenzalike syndrome and developed fatigue and signs and symptoms of heart failure a week after upper respiratory tract symptoms. Design, Setting, and Participant: This case report describes an otherwise healthy 53-year-old woman who tested positive for COVID-19 and was admitted to the cardiac care unit in March 2020 for acute myopericarditis with systolic dysfunction, confirmed on cardiac magnetic resonance imaging, the week after onset of fever and dry cough due to COVID-19. The patient did not show any respiratory involvement during the clinical course. Exposure: Cardiac involvement with COVID-19. Main Outcomes and Measures: Detection of cardiac involvement with an increase in levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) and high-sensitivity troponin T, echocardiography changes, and diffuse biventricular myocardial edema and late gadolinium enhancement on cardiac magnetic resonance imaging. Results: An otherwise healthy 53-year-old white woman presented to the emergency department with severe fatigue. She described fever and dry cough the week before. She was afebrile but hypotensive; electrocardiography showed diffuse ST elevation, and elevated high-sensitivity troponin T and NT-proBNP levels were detected. Findings on chest radiography were normal. There was no evidence of obstructive coronary disease on coronary angiography. Based on the COVID-19 outbreak, a nasopharyngeal swab was performed, with a positive result for SARS-CoV-2 on real-time reverse transcriptase-polymerase chain reaction assay. Cardiac magnetic resonance imaging showed increased wall thickness with diffuse biventricular hypokinesis, especially in the apical segments, and severe left ventricular dysfunction (left ventricular ejection fraction of 35%). Short tau inversion recovery and T2-mapping sequences showed marked biventricular myocardial interstitial edema, and there was also diffuse late gadolinium enhancement involving the entire biventricular wall. There was a circumferential pericardial effusion that was most notable around the right cardiac chambers. These findings were all consistent with acute myopericarditis. She was treated with dobutamine, antiviral drugs (lopinavir/ritonavir), steroids, chloroquine, and medical treatment for heart failure, with progressive clinical and instrumental stabilization. Conclusions and Relevance: This case highlights cardiac involvement as a complication associated with COVID-19, even without symptoms and signs of interstitial pneumonia.

COVID-19 Pneumonia: Three Thoracic Complications in the Same Patient

The most dreaded thoracic complications in patients with coronavirus disease 2019 (COVID-19) are acute pulmonary embolism and pulmonary fibrosis. Both the complications are associated with an increased risk of morbidity and mortality. While acute pulmonary embolism is not a rare finding in patients with COVID-19 pneumonia, the prevalence of pulmonary fibrosis remains unclear. Spontaneous pneumothorax is another possible complication in COVID-19 pneumonia, although its observation is rather uncommon. Herein, we present interesting computed tomography images of the first case of COVID-19 pneumonia that initially developed acute pulmonary embolism and subsequently showed progression toward pulmonary fibrosis and spontaneous pneumothorax.