Pregnancy Clinical Trial
Official title:
Quantitative Ultrasound Assessment of Gastric Volume in Pregnant Women at Term
Solid food or fluid residue in the stomach is always a major concern when patients need
medical procedures under sedation or general anesthesia, due to the high risk of pulmonary
aspiration of the stomach contents. This is especially important in emergency procedures,
when a fasting period is not observed. The aspiration of the stomach contents into one's
lungs can lead to serious complications (such as severe respiratory failure). Information
from a bedside ultrasound assessment of the stomach may be a very useful tool to decide
whether or not it's safe to proceed, cancel or delay a surgical procedure.
The investigotrs hypothesize that a mathematical model can be constructed to predict clear
fluid volume in the stomach of non-labouring pregnant patients, as it has been developed in
healthy adult volunteers.
Food residue in the stomach of patients scheduled to have surgery is considered a major risk
factor for pulmonary aspiration of gastric contents. The resulting respiratory compromise
after aspiration is associated with significant morbidity and mortality. The risk of
pulmonary aspiration is especially important in pregnant women, as they may often require
surgery without having observed appropriate fasting. A bedside ultrasound assessment of the
status of the gastric content would be of great value for the clinician. This technique has
recently been shown very promising in non-pregnant patients and it is important to study its
feasibility in the pregnant population.
In this study, patients fast overnight and are randomized to the following groups: empty, or
various volumes of fluid (50, 100, 200, 300 or 400mL of apple juice before scanning). Their
gastric contents are then assessed by an anesthesiologist, using ultrasound. The
investigators aim to evaluate a standardized quantitative ultrasound assessment of gastric
volume in non-labouring pregnant women.
;
Allocation: Randomized, Intervention Model: Parallel Assignment, Masking: Single Blind (Investigator)
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