Dataset Information

Lung ultrasonography for early management of patients with respiratory symptoms during COVID-19 pandemic.

ABSTRACT: COVID-19 pandemic is representing a serious challenge to worldwide public health. Lung Ultrasonography (LUS) has been signaled as a potential useful tool in this pandemic contest either to intercept viral pneumonia or to foster alternative paths. LUS could be useful in determining early lung involvement suggestive or not of COVID-19 pneumonia and potentially plays a role in managing decisions for hospitalization in isolation or admission in general ward. In order to face pandemic, in a period in which a large number of emergency room accesses with suspicious symptoms are expected, physicians need a standardized ultrasonographic approach, fast educational processes in order to be able to recognize both suggestive and not suggestive echographic signs and shared algorithms for LUS role in early management of patients.

SUBMITTER: Smargiassi A

PROVIDER: S-EPMC7338342 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Lung ultrasonography for early management of patients with respiratory symptoms during COVID-19 pandemic.

Smargiassi Andrea A Soldati Gino G Borghetti Alberto A Scoppettuolo Giancarlo G Tamburrini Enrica E Testa Antonia Carla AC Moro Francesca F Natale Luigi L Larici Anna Rita AR Buonsenso Danilo D Valentini Piero P Draisci Gaetano G Zanfini Bruno Antonio BA Pompili Maurizio M Scambia Giovanni G Lanzone Antonio A Franceschi Francesco F Rapaccini Gian Ludovico GL Gasbarrini Antonio A Gasbarrini Antonio A Giorgini Paolo P Richeldi Luca L Demi Libertario L Inchingolo Riccardo R

Journal of ultrasound 20200707 4

COVID-19 pandemic is representing a serious challenge to worldwide public health. Lung Ultrasonography (LUS) has been signaled as a potential useful tool in this pandemic contest either to intercept viral pneumonia or to foster alternative paths. LUS could be useful in determining early lung involvement suggestive or not of COVID-19 pneumonia and potentially plays a role in managing decisions for hospitalization in isolation or admission in general ward. In order to face pandemic, in a period in ...[more]

PMID: 32638333

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Project description:BackgroundCOVID-19 pandemic is disaster to public health worldwide. Better perspective on COVID's features early in its course-prior to the development of vaccines and widespread variants-may prove useful in the understanding of future pandemics. Ontology provides a standardized integrative method for knowledge modeling and computer-assisted reasoning. In this study, we systematically extracted and analyzed clinical phenotypes and comorbidities in COVID-19 patients found at different countries and regions during the early pandemic using an ontology-based bioinformatics approach, with the aim to identify new insights and hidden patterns of the COVID-19 symptoms.ResultsA total of 48 research articles reporting analysis of first-hand clinical data from over 40,000 COVID-19 patients were surveyed. The patients studied therein were diagnosed with COVID-19 before May 2020. A total of 18 commonly-occurring phenotypes in these COVID-19 patients were first identified and then classified into different hierarchical groups based on the Human Phenotype Ontology (HPO). This meta-analytic approach revealed that fever, cough, and the loss of smell and taste were ranked as the most commonly-occurring phenotype in China, the US, and Italy, respectively. We also found that the patients from Europe and the US appeared to have more frequent occurrence of many nervous and abdominal symptom phenotypes (e.g., loss of smell, loss of taste, and diarrhea) than patients from China during the early pandemic. A total of 22 comorbidities, such as diabetes and kidney failure, were found to commonly exist in COVID-19 patients and positively correlated with the severity of the disease. The knowledge learned from the study was further modeled and represented in the Coronavirus Infectious Disease Ontology (CIDO), supporting semantic queries and analysis. Furthermore, also considering the symptoms caused by new viral variants at the later stages, a spiral model hypothesis was proposed to address the changes of specific symptoms during different stages of the pandemic.ConclusionsDifferential patterns of symptoms in COVID-19 patients were found given different locations, time, and comorbidity types during the early pandemic. The ontology-based informatics provides a unique approach to systematically model, represent, and analyze COVID-19 symptoms, comorbidities, and the factors that influence the disease outcomes.

Project description:The Greater Glasgow & Clyde NHS Trust Community Respiratory Response Team was established to manage patients with chronic respiratory disease at home during the COVID-19 pandemic. The team aimed to avert hospital admission while maximally utilising remote consultations. This observational study analysed outcomes of the triage pathway used, use of remote consultations, hospital admissions and mortality among patients managed by the team. Patients' electronic health records were retrospectively reviewed. Rates of emergency department attendance, hospital admission and death within 28 days of referral were compared across triage pathways. Segmented linear regression was carried out for emergency admissions in Greater Glasgow and Clyde pre- and post- Community Respiratory Response Team implementation, using emergency admissions for chronic obstructive pulmonary disease in the rest of Scotland as control and adjusting for all-cause emergency admissions. The triage category correlated with hospital admission and death. The red pathway had the highest proportion attending the emergency department (21%), significantly higher than the amber and green pathways (p = 0.03 and p = 0.004, respectively). The highest number of deaths were in the blue "end-of-life" pathway (p < 0.001). 87% of interactions were undertaken remotely. Triage severity appropriately led to targeted home visits. No nosocomial COVID-19 infections occurred among patients or staff. The Community Respiratory Response Team was associated with a significant decrease in emergency admissions (RR = 0.96 for each additional month under the Poisson model) compared to the counterfactual if the service had not been in place, suggesting a benefit in reducing secondary care pressures. The Community Respiratory Response Team effectively managed patients with chronic respiratory disease in the community, with an associated reduction in secondary care pressures during the COVID-19 pandemic.

Dataset Information

Lung ultrasonography for early management of patients with respiratory symptoms during COVID-19 pandemic.

Publications

Lung ultrasonography for early management of patients with respiratory symptoms during COVID-19 pandemic.

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