Lung ultrasound score in dogs and cats: A reliability study

犬猫肺部超声评分:一项可靠性研究

阅读:1

Abstract

BACKGROUND: Lung ultrasound (LUS) is a noninvasive tool for examining respiratory distress patients. The lung ultrasound score (LUSS) can be used to quantify and monitor lung aeration loss with good reliability. HYPOTHESIS/OBJECTIVES: Assess the reliability of a new LUSS among raters with different levels of experience and determine how well the same raters agree on identifying patterns of LUS abnormalities. ANIMALS: Forty LUS examinations of dogs and cats and 320 videos were reviewed from a digital database. METHODS: Retrospective reliability study with post hoc analysis. Protocolized LUS were randomly selected; intrarater and interrater reliability of the LUSS and pattern recognition agreement among 4 raters with different levels of experience in LUS were tested. RESULTS: The intrarater intraclass correlation coefficient (ICC) single measurement, absolute agreement, and 2-way mixed effects model was 0.967 for the high-experience rater (H-Exp), 0.963 and 0.952 for the medium-experience raters (M-Exp-1; M-Exp-2), and 0.950 for the low-experience rater (L-Exp). The interrater ICC average measurement, absolute agreement, and 2-way random effects model among the observers was 0.980. The Fleiss' kappa (k) values showed almost perfect agreement (k = 1) among raters in identifying pleural effusion and translobar tissue-like pattern, strong agreement for A-lines (k = 0.881) and B-lines (k = 0.806), moderate agreement (k = 0.693) for subpleural loss of aeration, and weak agreement (k = 0.474) for irregularities of the pleural line. CONCLUSIONS AND CLINICAL IMPORTANCE: Our results indicate excellent intra- and interrater reliability for LUS scoring and pattern identification, providing a foundation for the use of the LUSS in emergency medicine and intensive care.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。