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Clinical performance of lung ultrasound in predicting time-dependent changes in lung aeration in ARDS patients.

Authors :
Andrea, Costamagna
Irene, Steinberg
Emanuele, Pivetta
Pietro, Arina
Simona, Veglia
Luca, Brazzi
Vito, Fanelli
Source :
Journal of Clinical Monitoring & Computing; Apr2023, Vol. 37 Issue 2, p473-480, 8p
Publication Year :
2023

Abstract

To evaluate whether lung ultrasound is reliable bedside tool to monitor changes of lung aeration at the early and late stages of ARDS. LUS was performed in ARDS patients that underwent at least two consecutive CT scan at ICU admission and at least 1 week after admission. Twelve fields were evaluated and graded from 0 (normal) to 3 (consolidation). Changes of LUS score in twelve fields (ΔLUS<subscript>tot</subscript>) and in four ventral (ΔLUS<subscript>V</subscript>), intermediate (ΔLUS<subscript>I</subscript>) and dorsal (ΔLUS<subscript>D</subscript>) zones were calculated at each time points. Three categories were described: Improve (ΔLUS < 0), Equal (ΔLUS = 0) or Worse (ΔLUS > 0). LUS scores were correlated with total changes in lung CT aeration (ΔCT<subscript>air</subscript>) and with normally, poorly and not aerated regions (ΔCT<subscript>norm</subscript>, ΔCT<subscript>poor</subscript> and ΔCT<subscript>not</subscript>, respectively). Eleven patients were enrolled. ΔLUS<subscript>tot</subscript> had significant correlation with ΔCT<subscript>air</subscript> (r = − 0.74, p < 0.01). ΔLUS<subscript>V</subscript>, ΔLUS<subscript>I</subscript> and ΔLUS<subscript>D</subscript> showed significant correlations with ΔCT<subscript>air</subscript> (r = − 0.66, r = − 0.69, r = − 0.63, respectively; p < 0.05). Compared to Equal, Improve and Worse categories had significantly higher (p < 0.01) and lower (p < 0.05) ΔCTair values, respectively. Compared to Equal, Improve and Worse categories had lower (p < 0.01) and higher (p < 0.01) ΔCT<subscript>not</subscript> values, respectively. LUS score had a good correlation with lung CT in detecting changes of lung aeration. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13871307
Volume :
37
Issue :
2
Database :
Complementary Index
Journal :
Journal of Clinical Monitoring & Computing
Publication Type :
Academic Journal
Accession number :
162871148
Full Text :
https://doi.org/10.1007/s10877-022-00902-5