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Prediction of gastric fluid volume by ultrasonography in infants undergoing general anaesthesia

仰卧位 医学 体积热力学 相关系数 核医学 超声科 麻醉 协议限制 肺吸入 内科学 外科 数学 统计 物理 量子力学
作者
Eun‐Hee Kim,Hee-Chul Yoon,Ji‐Hyun Lee,Hee‐Soo Kim,Young‐Eun Jang,Sang‐Hwan Ji,Sung-Ae Cho,Jin‐Tae Kim
出处
期刊:BJA: British Journal of Anaesthesia [Elsevier]
卷期号:127 (2): 275-280 被引量:10
标识
DOI:10.1016/j.bja.2021.03.039
摘要

Abstract

Background

Point-of-care ultrasonography can estimate gastric contents and volume to assess the risk of pulmonary aspiration; however, its use in infants has not been well validated. We aimed to develop a predictive model for estimating gastric fluid volume using ultrasonography in infants.

Methods

This prospective observational study enrolled 200 infants (≤12 months) undergoing general anaesthesia. After anaesthetic induction, while preserving spontaneous respiration, we measured gastric antral cross-sectional area using ultrasonography in both the supine and right lateral decubitus positions. We then suctioned the gastric content and measured its volume. The primary outcome was development of a gastric fluid volume prediction model with multiple regression analysis. Agreement between the predicted volume and the suctioned volume was evaluated using a Bland–Altman plot.

Results

Overall, 192 infants were included in the final analysis. Pearson correlation analysis showed that the gastric antral cross-sectional area in the supine (P<0.001; correlation coefficient: 0.667) and right lateral decubitus (P<0.001; correlation coefficient: 0.845) positions and qualitative antral grade (P<0.001; correlation coefficient: 0.581) correlated with suctioned volume. We developed a predictive model: predicted volume (ml)=–3.7+6.5 × (right lateral decubitus cross-sectional area [cm2])–3.9 (supine cross-sectional area [cm2])+1.7 × grade (P<0.01). When comparing the predicted volume and suctioned volume, the mean bias was 0.01 ml kg−1 and the limit of agreement was –0.58 to 0.62 ml kg−1.

Conclusions

Gastric fluid volume can be estimated using a predictive model based on ultrasonography data in infants.

Clinical trial registration

NCT03155776.
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