Comparative Analysis of Hematological and Biochemical Changes in Neonates among Women with and without COVID-19 Infection during Pregnancy.

The aim of this study is to evaluate the test results of neonates delivered by COVID-19-positive mothers during pregnancy with those of neonates born to unvaccinated mothers who are COVID-19-free. A cohort study was conducted on 367 pregnant women who gave birth at Premiere Hospital, Timisoara, Romania, between May 2021 and February 2022. Two groups were established: Group 1, with 167 pregnant women infected with COVID-19, and Group 2, with 200 pregnant women who were not affected by COVID-19 during pregnancy. Maternal laboratory examination did not exhibit significant variations except for platelet count. In neonatal blood tests, WBC had a significantly lower median value in the group born to COVID-19-free mothers. Neonatal anemia and leukocytosis showed slightly higher prevalence in Group 1, but the differences were not statistically significant. This study suggests that maternal COVID-19 infection during pregnancy does not have significant associations with most maternal and neonatal characteristics.

The Effects of COVID-19 on Skeletal Muscles, Muscle Fatigue and Rehabilitation Programs Outcomes.

Background and Objectives: Consequences due to infection with SARS-CoV-2 virus can have a direct impact on skeletal muscle, due to the fact that both cardiac and skeletal muscle tissue show robust ACE2(angiotensin-converting enzyme 2) expression, suggesting a potential susceptibility to SARS-CoV-2 infection in both types of tissues. From the articles analyzed we concluded that the musculoskeletal damage is firstly produced by the inflammatory effects, cytokine storm and muscle catabolism. However, myopathy, polyneuropathy and therapies such as corticoids were also considered important factors in muscle fatigue and functional incapacity. Pulmonary rehabilitation programs and early mobilization had a highly contribution during the acute phase and post-illness recovery process and helped patients to reduce dyspnea, increase the capacity of physical effort, overcome psychological disorders and improved the quality of their life. Materials and Methods: We have included in this review 33 articles that contain data on muscle damage following SARS-CoV-2 infection. We used the following keywords to search for articles: SARS-CoV-2, COVID-19, muscle weakness, muscle disease, muscle fatigue, neurological disorders. As a search strategy we used PubMed, Cochrane Database of Systematic Reviews; Database of Abstracts of Reviews of Effects and Health Technology Assessment Database to collect the information. We also have chosen the most recent articles published in the last 5 years. Conclusions: Muscular damage, as well as the decrease in the quality of life, are often a consequence of severe SARS-CoV-2 infection through: systemic inflammation, corticotherapy, prolonged bed rest and other unknown factors. Pulmonary rehabilitation programs and early mobilization had a highly contribution during the acute phase and post-illness recovery process and helped patients to reduce dyspnea, increase the capacity of physical effort, overcome psychological disorders and improve the quality of their life.

Enhancing Imagistic Interstitial Lung Disease Diagnosis by Using Complex Networks.

Background and Objectives: Diffuse interstitial lung diseases (DILD) are a heterogeneous group of over 200 entities, some with dramatical evolution and poor prognostic. Because of their overlapping clinical, physiopathological and imagistic nature, successful management requires early detection and proper progression evaluation. This paper tests a complex networks (CN) algorithm for imagistic aided diagnosis fitness for the possibility of achieving relevant and novel DILD management data. Materials and Methods: 65 DILD and 31 normal high resolution computer tomography (HRCT) scans were selected and analyzed with the CN model. Results: The algorithm is showcased in two case reports and then statistical analysis on the entire lot shows that a CN algorithm quantifies progression evaluation with a very fine accuracy, surpassing functional parameters' variations. The CN algorithm can also be successfully used for early detection, mainly on the ground glass opacity Hounsfield Units band of the scan. Conclusions: A CN based computer aided diagnosis could provide the much-required data needed to successfully manage DILDs.

A Novel Method for Lung Image Processing Using Complex Networks.

The High-Resolution Computed Tomography (HRCT) detection and diagnosis of diffuse lung disease is primarily based on the recognition of a limited number of specific abnormal findings, pattern combinations or their distributions, as well as anamnesis and clinical information. Since texture recognition has a very high accuracy percentage if a complex network approach is used, this paper aims to implement such a technique customized for diffuse interstitial lung diseases (DILD). The proposed procedure translates HRCT lung imaging into complex networks by taking samples containing a secondary lobule, converting them into complex networks and analyzing them in three dimensions: emphysema, ground glass opacity, and consolidation. This method was evaluated on a 60-patient lot and the results showed a clear, quantifiable difference between healthy and affected lungs. By deconstructing the image on three pathological axes, the method offers an objective way to quantify DILD details which, so far, have only been analyzed subjectively.