| Literature DB >> 33303539 |
Thomas Sonnweber1,2, Sabina Sahanic1,2, Alex Pizzini1, Anna Luger3, Christoph Schwabl3, Bettina Sonnweber4, Katharina Kurz1, Sabine Koppelstätter1, David Haschka1, Verena Petzer5, Anna Boehm1, Magdalena Aichner1, Piotr Tymoszuk1, Daniela Lener6, Markus Theurl6, Almut Lorsbach-Köhler1, Amra Tancevski1, Anna Schapfl4, Marc Schaber4, Richard Hilbe1, Manfred Nairz1, Bernhard Puchner7, Doris Hüttenberger1, Christoph Tschurtschenthaler1, Malte Aßhoff1, Andreas Peer8, Frank Hartig8, Romuald Bellmann8, Michael Joannidis8, Can Gollmann-Tepeköylü9, Johannes Holfeld9, Gudrun Feuchtner3, Alexander Egger10, Gregor Hoermann10,11,12, Andrea Schroll1, Gernot Fritsche1, Sophie Wildner1, Rosa Bellmann-Weiler1, Rudolf Kirchmair6,7, Raimund Helbok13, Helmut Prosch14, Dietmar Rieder15, Zlatko Trajanoski15, Florian Kronenberg16, Ewald Wöll4, Günter Weiss1, Gerlig Widmann3,17, Judith Löffler-Ragg1,17, Ivan Tancevski1,17.
Abstract
BACKGROUND: After the 2002/2003 severe acute respiratory syndrome outbreak, 30% of survivors exhibited persisting structural pulmonary abnormalities. The long-term pulmonary sequelae of coronavirus disease 2019 (COVID-19) are yet unknown, and comprehensive clinical follow-up data are lacking.Entities:
Year: 2021 PMID: 33303539 PMCID: PMC7736754 DOI: 10.1183/13993003.03481-2020
Source DB: PubMed Journal: Eur Respir J ISSN: 0903-1936 Impact factor: 16.671
Demographics and clinical characteristics of patients enrolled in the Development of Interstitial Lung Disease (ILD) in Patients with SARS-CoV-2 infection (CovILD) study
| 145 | |
| 57±14 | |
| 63 (43) | |
| 26±5 | |
| 57 (39) | |
| Current smokers | 4 (3) |
| Pack-years | 8±16 |
| None | 33 (23) |
| Cardiovascular disease | 58 (40) |
| Hypertension | 44 (30) |
| Pulmonary disease | 27 (19) |
| COPD | 8 (6) |
| Asthma | 10 (7) |
| ILD# | 1 (1) |
| Metabolic disease | 63 (43) |
| Hypercholesterolaemia | 27 (19) |
| Diabetes mellitus, type 2 | 24 (17) |
| Chronic kidney disease | 10 (7) |
| Chronic liver disease | 8 (6) |
| Malignancy | 17 (12) |
| Immunodeficiency¶ | 9 (6) |
| 109 (75) | |
| Oxygen supply | 72 (66) |
| Noninvasive ventilation | 3 (3) |
| Invasive ventilation | 29 (27) |
Data are presented as n, mean±sd or n (%). BMI: body mass index. #: n=1 with a history of radiation-induced pneumonitis; ¶: due to disease or ongoing immunosuppressive treatment: renal transplantation (n=1), psoriasis vulgaris (n=1), morbus Hashimoto (n=1), leukaemia (n=1), lymphoma (n=1), gout (n=1), polyarthritis (n=1). +: all patients needing noninvasive or invasive ventilation were supplied with oxygen before intensive care unit admission; relative numbers depict the treatment of in-hospital patients.
FIGURE 1Symptom burden in the Development of Interstitial Lung Disease (ILD) in Patients with SARS-CoV-2 infection (CovILD) study cohort during acute coronavirus disease 2019 (COVID-19) and at follow-up. a) Using a standardised questionnaire, performance status and overall burden of symptoms were assessed for the time-point of disease onset, 60 days (V1), and 100 days (V2) after diagnosis of COVID-19. b) Symptom burden was assessed using a standardised questionnaire at COVID-19 onset and at 100 days post-COVID-19 diagnosis. All symptoms significantly improved over time (p<0.001 for all read-outs). nacute=145, nfollow-up=135.
Pulmonary function of coronavirus disease 2019 (COVID-19) patients at follow-up
| 126 | 133 | ||
| 53 (42) | 48 (36) | 0.388 | |
| 3.6±1.0 | 3.7±0.9 | ||
| 34 (27) | 29 (22) | ||
| 2.9±0.8 | 3.0±0.8 | ||
| 28 (22) | 30 (22) | 1.000 | |
| 84±11 | 80±11 | ||
| 5 (4) | 11 (8) | 0.063 | |
| 6.2±1.3 | 6.2±1.3 | 0.881 | |
| 14 (11) | 15 (11) | 0.791 | |
| 7.7±2.4 | 7.9±2.3 | ||
| 39 (31) | 28 (21) | ||
| 79±10 | 78±9 | 0.864 | |
| 40 (32) | 45 (37) | 0.871 |
Data are presented as n, n (%) or mean±sd, unless otherwise stated. Bold type represents statistical significance. Wilcoxon signed-rank test and McNemar test were used to assess time-related differences. FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; TLC: total lung capacity; DLCO: diffusing capacity of the lung for carbon monoxide; PO: partial pressure of oxygen assessed with blood gas analysis (without oxygen supplementation). #: 60 days after COVID-19 diagnosis; ¶: 100 days after COVID-19 diagnosis; +: lung function was considered impaired if FVC, FEV1, FEV1/FVC ratio, TLC or DLCO were below the predicted normal.
FIGURE 2Chest computed tomography (CT) lung analysis at coronavirus disease 2019 (COVID-19) onset and follow-up. a) The pattern of pathological findings assessed with CT at 60 (V1) and 100 days (V2) after diagnosis of COVID-19. b) Automated analysis of lung opacities assessed on CT scans from the acute disease phase, 60 days and 100 days after COVID-19 diagnosis employing Syngo.via CT Pneumonia Analysis software (Siemens Healthineers, Erlangen, Germany). c) CT severity scoring by radiologists at COVID-19 onset, 60 days and 100 days after COVID-19 diagnosis. The severity score was calculated via CT evaluation by three independent radiologists who qualitatively graded lung impairment for each lobe separately (grade 0–5, with 0 for no involvement and 5 for massive involvement). A total score was achieved by summation of grades for all five lobes (maximum 25 points). Data are presented as mean±se. nacute=23, nV1=145, nV2=135.
FIGURE 3Representative computed tomography scans of coronavirus disease 2019 patients with a) minimal, b) moderate and c) severe radiological findings at first follow-up. Percentage of opacity/high opacity a) 0.07/0.00; b) 10.29/0.69; c) 56.87/5.92.
FIGURE 4Representative sequential computed tomography (CT) scans of a 56-year-old male coronavirus disease 2019 (COVID-19) patient during acute disease and follow-up. Pulmonary three-dimensional modelling assessed with CT is shown a) during acute COVID-19, b) at 60 days follow-up and c) at 100 days follow-up. Pulmonary opacities, mainly reflecting ground-glass opacities and/or consolidation, were quantified with Syngo.via CT Pneumonia Analysis software (Siemens Healthineers, Erlangen, Germany). Areas with increased opacity are marked in red, whereas normal lung areas are indicated in green.
FIGURE 5Changes in pulmonary impairment according to computed tomography (CT) analysis in patients of different acute coronavirus disease 2019 (COVID-19) disease severities. Time-dependent changes of CT severity score in patients with mild to critical COVID-19. Disease severity was graded by the need for acute medical treatment, as follows. Mild: outpatient care; moderate: hospitalisation without respiratory support; severe: hospitalisation with the need for oxygen supply; critical: patients treated at the intensive care unit with the need for noninvasive or invasive ventilation. Except for patients with mild COVID-19, who demonstrated only minor pulmonary CT abnormalities, all other patient groups demonstrated a significant improvement of lung abnormalities in CT scans (p=0.042 to p<0.001 for time-dependent changes). CT severity scoring ranges from 0 to 25 and was applied as detailed in the methods section. Visit 1 (V1) and visit 2 (V2) were performed 60 and 100 days after the diagnosis of COVID-19, respectively. Data are presented as mean±se.