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.

A Systematic Review of Telemedicine-Driven Pulmonary Rehabilitation after the Acute Phase of COVID-19.

The acute phase of COVID-19 often leaves patients with persistent pulmonary deficits. Pulmonary Rehabilitation (PR) has been recommended as an essential part of post-acute COVID-19 management. In light of the global pandemic, telerehabilitation has been increasingly employed to deliver PR.

Massive Spontaneous Pneumomediastinum-A Form of Presentation for Severe COVID-19 Pneumonia.

For COVID-19 pneumonia, many manifestations such as fever, dyspnea, dry cough, anosmia and tiredness have been described, but differences have been observed from person to person according to age, pulmonary function, damage and severity. In clinical practice, it has been found that patients with severe forms of infection with COVID-19 develop serious complications, including pneumomediastinum. Although two years have passed since the beginning of the pandemic with the SARS-CoV-2 virus and progress has been made in understanding the pathophysiological mechanisms underlying the COVID-19 infection, there are also unknown factors that contribute to the evolution of the disease and can lead to the emergence some complications.

Enhancing Imagistic Interstitial Lung Disease Diagnosis by Using Complex Networks.

: 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.

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.

Deep learning in interstitial lung disease-how long until daily practice.

Interstitial lung diseases are a diverse group of disorders that involve inflammation and fibrosis of interstitium, with clinical, radiological, and pathological overlapping features. These are an important cause of morbidity and mortality among lung diseases. This review describes computer-aided diagnosis systems centered on deep learning approaches that improve the diagnostic of interstitial lung diseases.