Mid-term Follow-Up chest CT findings in recovered COVID-19 patients with residual symptoms.

OBJECTIVES: More than a year has passed since the initial outbreak of SARS-CoV-2, which caused many hospitalizations worldwide due to COVID-19 pneumonia and its complications. However, there is still a lack of information detailing short- and long-term outcomes of previously hospitalized patients. The purpose of this study is to analyze the most frequent lung CT findings in recovered COVID-19 patients at mid-term follow-ups. METHODS: A total of 407 consecutive COVID-19 patients who were admitted to the XXXX and discharged between February 27, 2020, and June 26, 2020 were recruited into this study. Out of these patients, a subset of 108 patients who presented with residual asthenia and dyspnea at discharge, altered spirometric data, positive lung ultrasound and positive chest X-ray was subsequently selected, and was scheduled to undergo a mid-term chest computer tomography study, which was evaluated for specific lung alterations and morphological patterns. RESULTS: The most frequently observed lung CT alterations, in order of frequency, were ground glass opacities (81%), linear opacities (74%), bronchiolectases (64,81%), and reticular opacities (63,88%). The most common morphological pattern was the nonspecific interstitial pneumonia pattern (63,88%). Features consistent with pulmonary fibrosis were observed in 32 patients (29,62%). CONCLUSIONS: Our work showed that recovered COVID-19 patients that were hospitalized and that exhibited residual symptoms after discharge had a slow radiological recovery with persistent residual lung alterations. ADVANCES IN KNOWLEDGE: This slow recovery process should be kept in mind when determining the follow-up phases in order to improve the long-term management of patients affected by COVID-19.

A mid-term follow-up with a lung ultrasonographic score correlates with the severity of COVID-19 acute phase.

Lung ultrasound (LUS) has rapidly emerged in COVID-19 diagnosis and for the follow-up during the acute phase. LUS is not yet used routinely in lung damage follow-up after COVID-19 infection. We investigated the correlation between LUS score, and clinical and laboratory parameters of severity of SARS-COV-2 damage during hospitalization and at follow-up visit. Observational retrospective study including all the patients discharged from the COVID-19 wards, who attended the post-COVID outpatient clinic of the IRCCS Policlinico San Matteo in April-June 2020. 115 patients were enrolled. Follow-up visits with LUS score measurements were at a median of 38 days (IQR 28-48) after discharge. LUS scores were associated with the length of hospitalization (p < 0.001), patients' age (p = 0.036), use of non-invasive ventilation (CPAP p < 0.001 or HFNC p = 0.018), administration of corticosteroids therapy (p = 0.030), and laboratory parameters during the acute phase (WBC p < 0.001, LDH p < 0.001, CRP p < 0.001, D-dimer p = 0.008, IL-6 p = 0.045), and inversely correlated with lymphocyte count (p = 0.007). We found correlation between LUS score and both LDH (p = 0.001) and the antibody anti-SARS-CoV-2 titers (p value = 0.008). Most of these finding were confirmed by dichothomizing the LUS score (≤ 9 or > 9 points). We found a significantly higher LUS score at the follow-up in the patients with persistent dyspnea (7.00, IQR 3.00-11.00) when compared to eupnoeic patients (3.00, IQR 0-7.00 p < 0.001). LUS score at follow-up visit correlates with more severe lung disease. These findings support the hypothesis that ultrasound could be a valid tool in the follow-up medium-term COVID-19 lung damage.

Competing-risk analysis of coronavirus disease 2019 in-hospital mortality in a Northern Italian centre from SMAtteo COvid19 REgistry (SMACORE).

An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. All consecutive hospitalised patients from February 21st to March 30th, 2020, with confirmed COVID-19 from the IRCCS Policlinico San Matteo, Pavia, Lombardy, Italy, were included. In-hospital mortality and discharge were evaluated by competing risk analysis. The Fine and Gray model was fitted in order to estimate the effect of covariates on the cumulative incidence functions (CIFs) for in-hospital mortality and discharge. 426 adult patients [median age 68 (IQR 56 to 77 years)] were admitted with confirmed COVID-19 over a 5-week period; 292 (69%) were male. By 21 April 2020, 141 (33%) of these patients had died, 239 (56%) patients had been discharged and 46 (11%) were still hospitalised. Among these 46 patients, updated as of 30 May, 2020, 5 (10.9%) had died, 8 (17.4%) were still in ICU, 12 (26.1%) were transferred to lower intensity care units and 21 (45.7%) were discharged. Regression on the CIFs for in-hospital mortality showed that older age, male sex, number of comorbidities and hospital admission after March 4th were independent risk factors associated with in-hospital mortality. Older age, male sex and number of comorbidities definitively predicted in-hospital mortality in hospitalised patients with COVID-19.

EBV DNA increase in COVID-19 patients with impaired lymphocyte subpopulation count.

OBJECTIVES: The immunologic profile and opportunistic viral DNA increase were monitored in Italian patients with COVID-19 in order to identify markers of disease severity. METHODS: A total of 104 patients infected with SARS-CoV-2 were evaluated in the study. Of them, 42/104 (40.4%) were hospitalized in an intensive care unit (ICU) and 62/104(59.6%) in a sub-intensive care unit (SICU). Human cytomegalovirus (HCMV) and Epstein-Barr virus (EBV), Parvovirus B19 and Human Herpesvirus 6 virus reactivations were determined by real-time PCR, and lymphocyte subpopulation counts were determined by flow cytometry. RESULTS: Among opportunistic viruses, only EBV was consistently detected. EBV DNA was observed in 40/42 (95.2%) of the ICU patients and in 51/61 (83.6%) of the SICU patients. Comparing the two groups of patients, the EBV DNA median level among ICU patients was significantly higher than that observed in SICU patients. In parallel, a significant reduction of CD8 T cell and NK count in ICU patients as compared with SICU patients was observed (p<0.05). In contrast, B cell count was significantly increased in ICU patients (p=0.0172). CONCLUSIONS: A correlation between reduced CD8+ T cells and NK counts, EBV DNA levels and COVID-19 severity was observed. Other opportunistic viral infections were not observed. The relationship between EBV load and COVID-19 severity should be further evaluated in longitudinal studies.

CovidDeep: SARS-CoV-2/COVID-19 Test Based on Wearable Medical Sensors and Efficient Neural Networks (preprint)

The novel coronavirus (SARS-CoV-2) has led to a pandemic. The current testing regime based on Reverse Transcription-Polymerase Chain Reaction for SARS-CoV-2 has been unable to keep up with testing demands, and also suffers from a relatively low positive detection rate in the early stages of the resultant COVID-19 disease. Hence, there is a need for an alternative approach for repeated large-scale testing of SARS-CoV-2/COVID-19. We propose a framework called CovidDeep that combines efficient DNNs with commercially available WMSs for pervasive testing of the virus. We collected data from 87 individuals, spanning three cohorts including healthy, asymptomatic, and symptomatic patients. We trained DNNs on various subsets of the features automatically extracted from six WMS and questionnaire categories to perform ablation studies to determine which subsets are most efficacious in terms of test accuracy for a three-way classification. The highest test accuracy obtained was 98.1%. We also augmented the real training dataset with a synthetic training dataset drawn from the same probability distribution to impose a prior on DNN weights and leveraged a grow-and-prune synthesis paradigm to learn both DNN architecture and weights. This boosted the accuracy of the various DNNs further and simultaneously reduced their size and floating-point operations.

Clinical characteristics of coronavirus disease (COVID-19) early findings from a teaching hospital in Pavia, North Italy, 21 to 28 February 2020.

We describe clinical characteristics, treatments and outcomes of 44 Caucasian patients with coronavirus disease (COVID-19) at a single hospital in Pavia, Italy, from 21-28 February 2020, at the beginning of the outbreak in Europe. Seventeen patients developed severe disease, two died. After a median of 6 days, 14 patients were discharged from hospital. Predictors of lower odds of discharge were age > 65 years, antiviral treatment and for severe disease, lactate dehydrogenase > 300 mg/dL.