Intensive care unit-acquired weakness - preventive, and therapeutic aspects; future directions and special focus on lung transplantation.
World J Clin Cases
; 12(19): 3665-3670, 2024 Jul 06.
Article
in En
| MEDLINE
| ID: mdl-38994273
ABSTRACT
In this editorial, comments are made on an interesting article in the recent issue of the World Journal of Clinical Cases by Wang and Long. The authors describe the use of neural network model to identify risk factors for the development of intensive care unit (ICU)-acquired weakness. This condition has now become common with an increasing number of patients treated in ICUs and continues to be a source of morbidity and mortality. Despite identification of certain risk factors and corrective measures thereof, lacunae still exist in our understanding of this clinical entity. Numerous possible pathogenetic mechanisms at a molecular level have been described and these continue to be increasing. The amount of retrievable data for analysis from the ICU patients for study can be huge and enormous. Machine learning techniques to identify patterns in vast amounts of data are well known and may well provide pointers to bridge the knowledge gap in this condition. This editorial discusses the current knowledge of the condition including pathogenesis, diagnosis, risk factors, preventive measures, and therapy. Furthermore, it looks specifically at ICU acquired weakness in recipients of lung transplantation, because - unlike other solid organ transplants- muscular strength plays a vital role in the preservation and survival of the transplanted lung. Lungs differ from other solid organ transplants in that the proper function of the allograft is dependent on muscle function. Muscular weakness especially diaphragmatic weakness may lead to prolonged ventilation which has deleterious effects on the transplanted lung - ranging from ventilator associated pneumonia to bronchial anastomotic complications due to prolonged positive pressure on the anastomosis.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
World J Clin Cases
Year:
2024
Document type:
Article
Affiliation country:
India