RT Journal Article
T1 Inter-Rater Variability in the Evaluation of Lung Ultrasound in Videos Acquired from COVID-19 Patients
A1 López Herraiz, Joaquín
A1 Freijo Escudero, Clara
A1 otros, ...
AB Lung ultrasound (LUS) allows for the detection of a series of manifestations of COVID-19, such as B-lines and consolidations. The objective of this work was to study the inter-rater reliability (IRR) when detecting signs associated with COVID-19 in the LUS, as well as the performance of the test in a longitudinal or transverse orientation. Thirty-three physicians with advanced experience in LUS independently evaluated ultrasound videos previously acquired using the ULTRACOV system on 20 patients with confirmed COVID-19. For each patient, 24 videos of 3 s were acquired (using 12 positions with the probe in longitudinal and transverse orientations). The physicians had no information about the patients or other previous evaluations. The score assigned to each acquisition followed the convention applied in previous studies. A substantial IRR was found in the cases of normal LUS (kappa = 0.74), with only a fair IRR for the presence of individual B-lines (kappa = 0.36) and for confluent B-lines occupying < 50% (kappa = 0.26) and a moderate IRR in consolidations and B-lines > 50% (kappa = 0.50). No statistically significant differences between the longitudinal and transverse scans were found. The IRR for LUS of COVID-19 patients may benefit from more standardized clinical protocols.
PB MDPI
SN 2076-3417
YR 2023
FD 2023-02
LK https://hdl.handle.net/20.500.14352/72232
UL https://hdl.handle.net/20.500.14352/72232
LA eng
NO Artículo firmado por 42 autores. This research was partially funded by CDTI (Spanish acronym: Centre for Industrial Technological Development), funding number COI-20201153. Partially supported by the Google Cloud Research Credits program with the funding number GCP19980904, by the project RTI2018-099118-A-I00 founded by MCIU/AEI/FEDER UE and by the European Commission-NextGenerationEU, through CSIC's Global Health Platform (PTI Salud Global).
NO Centre for Industrial Technological Development (CDTI)
NO Google Cloud Research Credits program
NO MCIU/AEI/FEDER UE
NO European Commission-NextGenerationEU, through CSIC's Global Health Platform (PTI Salud Global)
DS Docta Complutense
RD 12 abr 2025