Methods and systems for assessing fluid reactivity using multimodal data

Abstract

A system (100) for assessing fluid responsiveness comprising: an infusion pump (24) in communication with at least one processor (32); and a plurality of physiological monitors (40, 42, 44, 46), It can be used to receive physiological signals from an associated patient. synchronizing physiological signals (48, 50) acquired from said associated patient (10) during a solution burst with a timing signal (54) of said infusion pump (24) administering said solution burst, according to One or more dynamic indicators and / or features (58) are calculated from the synchronized physiological signals (50) and based on the baseline physiological signals (48) collected from the associated patient (10) prior to administration of the solution burst to calculate one or more dynamic indicators and / or characteristics (50), based on the dynamic indicators and / or characteristics (58) from the synchronized physiological signal (50) and from the baseline physiological signal (48) The fluid responsiveness probability value (64) of said patient (10) is determined by the dynamic indication and / or characteristic (50) of said patient (10).

Description

technical field [0001] This application relates generally to the field of medicine. It is specifically applied in conjunction with medical monitoring, patient treatment, etc., in hospitals, urgent care centers, emergency and / or trauma treatment, fluid resuscitation, etc. However, it should be understood that the present application is also applicable to other usage scenarios and is not necessarily limited to the above-mentioned applications. Background technique [0002] Fluid resuscitation is the first step in the management of a critically ill patient who has been deemed hemodynamically unstable. Unfortunately, only 50% of critically ill patients in the operating room (OR), intensive care unit (ICU) or emergency department (ED) respond positively to fluid resuscitation. Furthermore, patients who do not respond aggressively may be harmed by the treatment itself, and thus develop other clinical problems such as pulmonary edema or tissue edema. A predictive algorithm for f...

AI Technical Summary

Problems solved by technology

Unfortunately, these dynamic indicators are inaccurate in predicting fluid responsiveness in spontaneously breathing patients, mainly because ABP, ECG, or PPG do not vary very dramatically with respiratory cycles (ie, very low signal-to-noise ratios)

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