Quantitative Chest CT Analysis to Measure Short-Term Sequelae of COVID-19 Pneumonia: A Monocentric Prospective Study.

(1) Background: Quantitative CT analysis (QCT) has demonstrated promising results in the prognosis prediction of patients affected by COVID-19. We implemented QCT not only at diagnosis but also at short-term follow-up, pairing it with a clinical examination in search of a correlation between residual respiratory symptoms and abnormal QCT results. (2) Methods: In this prospective monocentric trial performed during the "first wave" of the Italian pandemic, i.e., from March to May 2020, we aimed to test the relationship between %deltaCL (variation of %CL-compromised lung volume) and variations of symptoms-dyspnea, cough and chest pain-at follow-up clinical assessment after hospitalization. (3) Results: 282 patients (95 females, 34%) with a median age of 60 years (IQR, 51-69) were included. We reported a correlation between changing lung abnormalities measured by QCT, and residual symptoms at short-term follow up after COVID-19 pneumonia. Independently from age, a low percentage of surviving patients (1-4%) may present residual respiratory symptoms at approximately two months after discharge. QCT was able to quantify the extent of residual lung damage underlying such symptoms, as the reduction of both %PAL (poorly aerated lung) and %CL volumes was correlated to their disappearance. (4) Conclusions QCT may be used as an objective metric for the measurement of COVID-19 sequelae.

CMR prevalence of subclinical myocardial damage in non-hospitalized COVID-19 patients: are we looking for a needle in a haystack?

Aims Subclinical myocardial damage is not uncommon in COVID-19 patients, likely reflecting a combination of direct viral toxicity with the activation of an uncontrolled autoimmune response usually developing during the cytokine storm phase. Whilst myocardial involvement in hospitalized patients has been extensively described in literature, no data are currently available for non-hospitalized individuals. Present study aimed to explore prevalence and impact on patients’ management of myocardial damage detected with CMR, in a cohort of consecutive non-hospitalized SARS-CoV-2 infection patients. Methods and results We conducted a single centre prospective observational study on 31 consecutive patients with previous COVID-19 who underwent CMR between October 2020 and June 2021 without requiring hospital admission. Myocarditis was defined by CMR according to the revised Lake Louise Criteria (LLC), if at least one criterion was positive: T2-based marker for myocardial oedema and T1-based marker for associated myocardial injury. Our patients’ cohort included 31 individuals with a mean age of 42.5 ± 17.4 years (20 males;64.5%) with mean follow-up time of 365.8 ± 89 days between first positive PCR and last clinical evaluation. CMR evidence of cardiac involvement was observed in six patients (19.3%)—including two acute (of which one with pericardial inflammation), one subacute and three healed myocarditis. CMR abnormalities were associated with a higher percentage of palpitations (83% vs. 24%, P = 0.013) and chest pain (66% vs. 16%, P = 0.026) during the active phase of COVID-19. In all CMR positive cases, a tailored therapeutic approach was established consisting with the administration of cardioactive therapy with beta-blockers. All cases were uneventful during the follow-up period. Conclusions Our data showed a 19.3% prevalence of unexpected/subclinical myocardial involvement in a cohort of 31 consecutive non-hospitalized patients with previous SARS-CoV-2 infection. CMR findings were retrospectively associated with cardiac symptoms during the acute phase and yielded a change in clinical and therapeutic management in all positive cases. A better knowledge of symptomatic course of COVID-19 could help physicians to adequately select individuals in which CMR may show signs of cardiac damage.

Compromised Lung Volume and Hemostatic Abnormalities in COVID-19 Pneumonia: Results from an Observational Study on 510 Consecutive Patients.

BACKGROUND: Hemostatic abnormalities have been described in COVID-19, and pulmonary microthrombosis was consistently found at autopsy with concomitant severe lung damage. METHODS: This is a retrospective observational cross-sectional study including consecutive patients with COVID-19 pneumonia who underwent unenhanced chest CT upon admittance at the emergency room (ER) in one large academic hospital. QCT was used for the calculation of compromised lung volume (%CL). Clinical data were retrieved from patients' files. Laboratory data were obtained upon presentation at the ER. AIM: The aim of this study was to evaluate the correlation between hemostatic abnormalities and lung involvement in patients affected by COVID-19 pneumonia as described using computer-aided quantitative evaluation of chest CT (quantitative CT (QCT)). RESULTS: A total of 510 consecutive patients (68% males), aged 67 years in median, diagnosed with COVID-19 pneumonia, who underwent unenhanced CT scan upon admission to the ER, were included. In all, 115 patients had %CL > 23%; compared to those with %CL < 23%, they showed higher levels of D-dimer, fibrinogen, and CRP, greater platelet count, and longer PT ratio. Via multivariate regression analysis, BMI ≥ 30 kg/m2, D-dimer levels > 500 ng/mL, CRP > 5.0 ng/mL and PT ratio > 1.2 were found to be independent predictors of a %CL > 23% (adjusted odds ratios (95% confidence intervals): 2.1 (1.1-4.0), 3.1 (1.6-5.8), 2.4 (1.3-4.5), and 3.4 (1.4-8.5), respectively). CONCLUSIONS: Hemostatic abnormalities in patients affected by COVID-19 correlate with the severity of lung injury as measured by %CL. Our results underline the pathogenetic role of hemostasis in COVID-19 pneumonia beyond the presence of clinically evident thromboembolic complications.

Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation.

OBJECTIVE: Lombardy (Italy) was the epicentre of the COVID-19 pandemic in March 2020. The healthcare system suffered from a shortage of ICU beds and oxygenation support devices. In our Institution, most patients received chest CT at admission, only interpreted visually. Given the proven value of quantitative CT analysis (QCT) in the setting of ARDS, we tested QCT as an outcome predictor for COVID-19. METHODS: We performed a single-centre retrospective study on COVID-19 patients hospitalised from January 25, 2020, to April 28, 2020, who received CT at admission prompted by respiratory symptoms such as dyspnea or desaturation. QCT was performed using a semi-automated method (3D Slicer). Lungs were divided by Hounsfield unit intervals. Compromised lung (%CL) volume was the sum of poorly and non-aerated volumes (- 500, 100 HU). We collected patient's clinical data including oxygenation support throughout hospitalisation. RESULTS: Two hundred twenty-two patients (163 males, median age 66, IQR 54-6) were included; 75% received oxygenation support (20% intubation rate). Compromised lung volume was the most accurate outcome predictor (logistic regression, p < 0.001). %CL values in the 6-23% range increased risk of oxygenation support; values above 23% were at risk for intubation. %CL showed a negative correlation with PaO2/FiO2 ratio (p < 0.001) and was a risk factor for in-hospital mortality (p < 0.001). CONCLUSIONS: QCT provides new metrics of COVID-19. The compromised lung volume is accurate in predicting the need for oxygenation support and intubation and is a significant risk factor for in-hospital death. QCT may serve as a tool for the triaging process of COVID-19. KEY POINTS: • Quantitative computer-aided analysis of chest CT (QCT) provides new metrics of COVID-19. • The compromised lung volume measured in the - 500, 100 HU interval predicts oxygenation support and intubation and is a risk factor for in-hospital death. • Compromised lung values in the 6-23% range prompt oxygenation therapy; values above 23% increase the need for intubation.