AI-Based Chest CT Analysis for Rapid COVID-19 Diagnosis and Prognosis: A Practical Tool to Flag High-Risk Patients and Lower Healthcare Costs

peer reviewedEarly diagnosis of COVID-19 is required to provide the best treatment to our patients, to prevent the epidemic from spreading in the community, and to reduce costs associated with the aggravation of the disease. We developed a decision tree model to evaluate the impact of using an artificial intelligence-based chest computed tomography (CT) analysis software (icolung, icometrix) to analyze CT scans for the detection and prognosis of COVID-19 cases. The model compared routine practice where patients receiving a chest CT scan were not screened for COVID-19, with a scenario where icolung was introduced to enable COVID-19 diagnosis. The primary outcome was to evaluate the impact of icolung on the transmission of COVID-19 infection, and the secondary outcome was the in-hospital length of stay. Using EUR 20000 as a willingness-to-pay threshold, icolung is cost-effective in reducing the risk of transmission, with a low prevalence of COVID-19 infections. Concerning the hospitalization cost, icolung is cost-effective at a higher value of COVID-19 prevalence and risk of hospitalization. This model provides a framework for the evaluation of AI-based tools for the early detection of COVID-19 cases. It allows for making decisions regarding their implementation in routine practice, considering both costs and effects

Automatized lung disease quantification in patients with COVID-19 as a predictive tool to assess hospitalization severity

peer reviewedThe pandemic of COVID-19 led to a dramatic situation in hospitals, where staff had to deal with a huge number of patients in respiratory distress. To alleviate the workload of radiologists, we implemented an artificial intelligence (AI) - based analysis named CACOVID-CT, to automatically assess disease severity on chest CT scans obtained from those patients. We retrospectively studied CT scans obtained from 476 patients admitted at the University Hospital of Liege with a COVID-19 disease. We quantified the percentage of COVID-19 affected lung area (% AA) and the CT severity score (total CT-SS). These quantitative measurements were used to investigate the overall prognosis and patient outcome: hospital length of stay (LOS), ICU admission, ICU LOS, mechanical ventilation, and in-hospital death. Both CT-SS and % AA were highly correlated with the hospital LOS, the risk of ICU admission, the risk of mechanical ventilation and the risk of in-hospital death. Thus, CAD4COVID-CT analysis proved to be a useful tool in detecting patients with higher hospitalization severity risk. It will help for management of the patients flow. The software measured the extent of lung damage with great efficiency, thus relieving the workload of radiologists

Airflow obstruction as a marker of adverse prognosis in rheumatoid arthritis

peer reviewedObjectivesIn our study, we explored the specific subgroup of patients with rheumatoid arthritis (RA) suffering from obstructive lung disease (OLD) and its impact on morbi-mortality.MethodsOur retrospective study included 309 patients suffering from RA with either obstructive (O-RA) or non-obstructive patterns (non-O-RA). OLD was defined based on the Tiffeneau index at the first available pulmonary functional test (PFT). Survival was then calculated and represented by a Kaplan–Meier curve. The comparison between the populations considered was performed by the Log-Rank test.ResultsOut of the 309 RA patients, 102 (33%) had airway obstruction. The overall survival time was significantly lower in the O-RA group than in the non-O-RA group (n = 207) (p < 0.001). The median survival time was 11.75 years in the O-RA group and higher than 16 years in the non-O-RA group. Multivariate analysis identified OLD as an independent risk factor for mortality (HR 2.20; 95% CI 1.21–4.00, p < 0.01).ConclusionAirway obstruction can be an independent risk factor of mortality in RA and should be considered as an early marker of poor prognosis. Further prospective longitudinal studies are required in order to determine the best clinical management for O-RA patients

Systematic review of overlapping microRNA patterns in COVID-19 and idiopathic pulmonary fibrosis.

peer reviewed[en] BACKGROUND: Pulmonary fibrosis is an emerging complication of SARS-CoV-2 infection. In this study, we speculate that patients with COVID-19 and idiopathic pulmonary fibrosis (IPF) may share aberrant expressed microRNAs (miRNAs) associated to the progression of lung fibrosis. OBJECTIVE: To identify miRNAs presenting similar alteration in COVID-19 and IPF, and describe their impact on fibrogenesis. METHODS: A systematic review of the literature published between 2010 and January 2022 (PROSPERO, CRD42022341016) was conducted using the key words (COVID-19 OR SARS-CoV-2) AND (microRNA OR miRNA) or (idiopathic pulmonary fibrosis OR IPF) AND (microRNA OR miRNA) in Title/Abstract. RESULTS: Of the 1988 references considered, 70 original articles were appropriate for data extraction: 27 studies focused on miRNAs in COVID-19, and 43 on miRNAs in IPF. 34 miRNAs were overlapping in COVID-19 and IPF, 7 miRNAs presenting an upregulation (miR-19a-3p, miR-200c-3p, miR-21-5p, miR-145-5p, miR-199a-5p, miR-23b and miR-424) and 9 miRNAs a downregulation (miR-17-5p, miR-20a-5p, miR-92a-3p, miR-141-3p, miR-16-5p, miR-142-5p, miR-486-5p, miR-708-3p and miR-150-5p). CONCLUSION: Several studies reported elevated levels of profibrotic miRNAs in COVID-19 context. In addition, the balance of antifibrotic miRNAs responsible of the modulation of fibrotic processes is impaired in COVID-19. This evidence suggests that the deregulation of fibrotic-related miRNAs participates in the development of fibrotic lesions in the lung of post-COVID-19 patients