Ultrasound assessment of gastric volumes of thick fluids: Validating a prediction model

Autor: Peter Van de Putte, Marijn C T Tacken, Anahi Perlas, Christiaan Keijzer, Tristan A J van Leest
Rok vydání: 2021
Předmět:
Zdroj: European Journal of Anaesthesiology, 38, 1223-1229
European Journal of Anaesthesiology, 38, 12, pp. 1223-1229
ISSN: 0265-0215
DOI: 10.1097/eja.0000000000001465
Popis: Item does not contain fulltext BACKGROUND: Enteral nutrition is essential in the treatment of critically ill patients. Current methods to monitor enteral nutrition such as aspiration of residual volume may be inaccurate. Gastric ultrasonography estimates total gastric fluid volume using the Perlas model, but this model is validated for clear fluids only, and its accuracy for measuring thick fluids is unknown. OBJECTIVES: The primary aim of this study was to evaluate the Perlas model for gastric volume estimation of enteral nutrition, a thick fluid product. DESIGN: A single-centre, single blinded, randomised controlled study. SETTING: Single university hospital, from May to July 2019. PARTICIPANTS: Seventy-two healthy fasted volunteers were randomly allocated to different fluid volume groups. INTERVENTION: Participants randomly ingested predetermined volumes between 50 and 400 ml of a feeding-drink (Nutricia Nutridrink). Following a standardised gastric ultrasound scanning protocol, a blinded sonographer measured the antral cross-sectional area in the supine and right-lateral decubitus positions. MAIN OUTCOME MEASURES: Measurements were performed at baseline, 5 min postingestion and 20 min postingestion. Gastric volumes were predicted using the previously established Perlas model and compared with total gastric fluid volumes after ingestion of the study drink. RESULTS: The Perlas model underestimated the volume of thick gastric fluid and yielded a suboptimal fit for our data. However, antral cross-sectional area and total gastric thick fluid volumes were significantly correlated (Pearson's correlation coefficient 0.73, P
Databáze: OpenAIRE