SARS-CoV-2 seroprevalence survey among health care providers in a Belgian public multiple-site hospital.

Although the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is lasting for more than 1 year, the exposition risks of health-care providers are still unclear. Available evidence is conflicting. We investigated the prevalence of antibodies against SARS-CoV-2 in the staff of a large public hospital with multiple sites in the Antwerp region of Belgium. Risk factors for infection were identified by means of a questionnaire and human resource data. We performed hospital-wide serology tests in the weeks following the first epidemic wave (16 March to the end of May 2020) and combined the results with the answers from an individual questionnaire. Overall seroprevalence was 7.6%. We found higher seroprevalences in nurses [10.0%; 95% confidence interval (CI) 8.9-11.2] than in physicians 6.4% (95% CI 4.6-8.7), paramedical 6.0% (95% CI 4.3-8.0) and administrative staff (2.9%; 95% CI 1.8-4.5). Staff who indicated contact with a confirmed coronavirus disease 2019 (COVID-19) colleague had a higher seroprevalence (12.0%; 95% CI 10.7-13.4) than staff who did not (4.2%; 95% CI 3.5-5.0). The same findings were present for contacts in the private setting. Working in general COVID-19 wards, but not in emergency departments or intensive care units, was also a significant risk factor. Since our analysis points in the direction of active SARS-CoV-2 transmission within hospitals, we argue for implementing a stringent hospital-wide testing and contact-tracing policy with special attention to the health care workers employed in general COVID-19 departments. Additional studies are needed to establish the transmission dynamics.

Comparison between the ATS/ERS/JRS/ALAT criteria of 2011 and 2018 for Usual Interstitial Pneumonia on HRCT: a cross-sectional study.

OBJECTIVES: To determine whether the revised 2018 ATS/ERS/JRS/ALAT radiological criteria for usual interstitial pneumonia (UIP) provide better diagnostic agreement compared to the 2011 guidelines. METHODS: Cohort for this cross-sectional study (single center, nonacademic) was recruited from a multidisciplinary team discussion (MDD) from July 2010 until November 2018, with clinical suspicion of fibrosing interstitial lung disease (n= 325). Exclusion criteria were technical HRCT issues, known connective tissue disease (rheumatoid arthritis, systemic sclerosis, poly-or dermatomyositis), exposure to pulmonary toxins or lack of working diagnosis after MDD. Four readers with varying degrees in HRCT interpretation independently categorized 192 HRCTs, according to both the previous and current ATS/ERS/JRS/ALAT radiological criteria. An inter-rater variability analysis (Gwet's second-order agreement coefficient, AC2) was performed. RESULTS: The resulting Gwet's AC2 for the 2011 and 2018 ATS/ERS/JRS/ALAT radiological criteria is 0.62 (±0.05) and 0.65 (±0.05), respectively. We report only minor differences in agreement level among the readers. Distribution according to the 2011 guidelines is as follows: 57.3% 'UIP pattern', 24% 'possible UIP pattern', 18.8% 'inconsistent with UIP pattern' and for the 2018 guidelines: 59.6% 'UIP', 14.5% 'probable UIP', 15.9% 'indeterminate for UIP' and 10% 'alternative diagnosis'. CONCLUSIONS: No statistically significant higher degree of diagnostic agreement is observed when applying the revised 2018 ATS/ERS/JRS/ALAT radiological criteria for UIP compared to those of 2011. The inter-rater variability for categorizing the HRCT patterns is moderate for both classification systems, independent of experience in HRCT interpretation. The major advantage of the current guidelines is the better subdivision in the categories with a lower diagnostic certainty for UIP. ADVANCES IN KNOWLEDGE: - In 2018, a revision of the 2011 ATS/ERS/JRS/ALAT radiological criteria for UIP was published, part of diagnostic guidelines for idiopathic pulmonary fibrosis.- The inter-rater agreement among radiologist is moderate for both classification systems, without a significantly higher degree of agreement when applying the revised radiological criteria.

Interstitial lung disease in systemic sclerosis quantification of disease classification and progression with high-resolution computed tomography: An observational study.

Introduction: Systemic sclerosis-associated interstitial lung disease accounts for up to 20% of mortality in these patients and has a highly variable prognosis. Functional respiratory imaging, a quantitative computed tomography imaging technique which allows mapping of regional information, can provide a detailed view of lung structures. It thereby shows potential to better characterize this disease. Purpose: To evaluate the use of functional respiratory imaging quantitative computed tomography in systemic sclerosis-associated interstitial lung disease staging, as well as the relationship between short-term changes in pulmonary function tests and functional respiratory imaging quantitative computed tomography with respect to disease severity. Materials and methods: An observational cohort of 35 patients with systemic sclerosis was retrospectively studied by comparing serial pulmonary function tests and in- and expiratory high-resolution computed tomography over 1.5-year interval. After classification into moderate to severe lung disease and limited lung disease (using a hybrid method integrating quantitative computed tomography and pulmonary function tests), post hoc analysis was performed using mixed-effects models and estimated marginal means in terms of functional respiratory imaging parameters. Results: At follow-up, relative mean forced vital capacity percentage change was not significantly different in the limited (6.37%; N = 13; p = 0.053) and moderate to severe disease (-3.54%; N = 16; p = 0.102) groups, respectively. Specific airway resistance decreased from baseline for both groups. (Least square mean changes -25.11% predicted (p = 0.006) and -14.02% predicted (p = 0.001) for limited and moderate to severe diseases.) In contrast to limited disease from baseline, specific airway radius increased in moderate to severe disease by 8.57% predicted (p = 0.011) with decline of lower lobe volumes of 2.97% predicted (p = 0.031). Conclusion: Functional respiratory imaging is able to differentiate moderate to severe disease versus limited disease and to detect disease progression in systemic sclerosis.

Machine Learning Algorithms Utilizing Functional Respiratory Imaging May Predict COPD Exacerbations.

RATIONALE AND OBJECTIVES: Acute chronic obstructive pulmonary disease exacerbations (AECOPD) have a significant negative impact on the quality of life and accelerate progression of the disease. Functional respiratory imaging (FRI) has the potential to better characterize this disease. The purpose of this study was to identify FRI parameters specific to AECOPD and assess their ability to predict future AECOPD, by use of machine learning algorithms, enabling a better understanding and quantification of disease manifestation and progression. MATERIALS AND METHODS: A multicenter cohort of 62 patients with COPD was analyzed. FRI obtained from baseline high resolution CT data (unenhanced and volume gated), clinical, and pulmonary function test were analyzed and incorporated into machine learning algorithms. RESULTS: A total of 11 baseline FRI parameters could significantly distinguish ( p < 0.05) the development of AECOPD from a stable period. In contrast, no baseline clinical or pulmonary function test parameters allowed significant classification. Furthermore, using Support Vector Machines, an accuracy of 80.65% and positive predictive value of 82.35% could be obtained by combining baseline FRI features such as total specific image-based airway volume and total specific image-based airway resistance, measured at functional residual capacity. Patients who developed an AECOPD, showed significantly smaller airway volumes and (hence) significantly higher airway resistances at baseline. CONCLUSION: This study indicates that FRI is a sensitive tool (PPV 82.35%) for predicting future AECOPD on a patient specific level in contrast to classical clinical parameters.

A randomized study using functional respiratory imaging to characterize bronchodilator effects of glycopyrrolate/formoterol fumarate delivered by a metered dose inhaler using co-suspension delivery technology in patients with COPD.

Background: Functional respiratory imaging (FRI) uses high-resolution computed tomography (HRCT) scans to assess changes in airway volume and resistance. Patients and methods: In this randomized, double-blind, 2-week, crossover, Phase IIIB study, patients with moderate-to-severe COPD received twice-daily glycopyrrolate/formoterol fumarate delivered by a metered dose inhaler (GFF MDI, 18/9.6 µg) and placebo MDI, formulated using innovative co-suspension delivery technology. Co-primary endpoints included the following: specific image-based airway volume (siVaw) and specific image-based airway resistance (siRaw) at Day 15, measured using FRI. Secondary and other endpoints included the following: change from baseline in post-dose forced expiratory volume in 1 second (FEV1) and inspiratory capacity (IC; spirometry) and ratio to baseline in post-dose functional residual capacity (FRC) and residual volume (RV; body plethysmography). Results: Twenty patients (46-78 years of age) were randomized and treated; of whom 19 completed the study. GFF MDI treatment increased siVaw by 75% and reduced siRaw by 71% vs placebo MDI (both P<0.0001). Image-based airway volume (iVaw) and image-based airway resistance (iRaw), without adjusting for lobe volume, demonstrated corresponding findings to the co-primary endpoint, as lobe volumes did not change with either treatment. Approximately 48% of the delivered dose of glycopyrronium and formoterol fumarate was estimated to be deposited in the lungs. Compared with placebo, GFF MDI treatment improved post-dose FEV1 and IC (443 mL and 454 mL, respectively; both P<0.001) and reduced FRC and RV (13% and 22%, respectively; both P<0.0001). There were no significant safety findings. Conclusion: GFF MDI demonstrated significant, clinically meaningful benefits on FRI-based airway volume and resistance in patients with moderate-to-severe COPD. Benefits were associated with improvements in FEV1, IC, and hyperinflation. Clinical trial registration: ClinicalTrials.gov: NCT02643082.

Functional respiratory imaging (FRI) for optimizing therapy development and patient care.

Functional imaging techniques offer the possibility of improved visualization of anatomical structures such as; airways, lobe volumes and blood vessels. Computer-based flow simulations with a three-dimensional element add functionality to the images. By providing valuable detailed information about airway geometry, internal airflow distribution and inhalation profile, functional respiratory imaging can be of use routinely in the clinic. Three dimensional visualization allows for highly detailed follow-up in terms of disease progression or in assessing effects of interventions. Here, we explore the usefulness of functional respiratory imaging in different respiratory diseases. In patients with asthma and COPD, functional respiratory imaging has been used for phenotyping these patients, to predict the responder and non-responder phenotype and to evaluate different innovative therapeutic interventions.