Back

Follow-Up In Patients With Respiratory Disability After ARDS Related To COVID-19: A Systematic Review

Triantafyllaki, P.; Charalampopoulos, M.; Sampani, C.-A.; Triantafyllou, C.; Papageorgiou, D.

2023-06-27 intensive care and critical care medicine
10.1101/2023.06.24.23291855 medRxiv
Show abstract

IntroductionAcute Respiratory Distress Syndrome (ARDS) is an acute inflammatory pulmonary process that leads to protein-rich, non-hydrostatic pulmonary edema, undesirable hypoxemia, and lung stiffness. Due to COVID-19, a significant proportion of people who will require hospitalization to treat COVID-19, between 15%-30%, will develop severe respiratory failure, ARDS, and an increased likelihood of intubation for mechanical respiratory support. AimTo investigate the pulmonary function in COVID-19-related ARDS survivors after hospitalization. MethodsA search was performed on the Greek and international literature, as well as at the online Databases PubMed, Cochrane, Embase, and Google Scholar. Exclusion and integration criteria were set for the studies found, and a flow chart was created for the studies included. ResultsThrough the search, 352 articles were found matching the subject under study, and after further evaluation, four articles were included. The majority of the articles highlight that after ARDS occurs due to COVID-19, patients face impaired pulmonary function in combination with other physical and psychological symptoms like weakness, anxiety, depression, and generalized functional disability. ConclusionsIt is a fact that COVID-19 disease, in severe form and following the need for hospitalization due to the development of ARDS, results in an increased likelihood of prolonged occurrence of some symptoms of impaired respiratory function. Impaired CO2 diffusion is observed in the majority of studies as well as impaired respiratory function regarding prolonged imaging findings and impaired physical function.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.