Evolution of Perioperative Hemodynamic Monitoring from the Hand on Pulse to Hypotension Prediction Index

Authors: Shiraboina M , Ayya SS , Garre S , Anna AC , Gajagouni N , Shashikanth T and Ramachandran G

DOI: 10.23880/accmj-16000250

Volume 10, Issue 1

Abstract

This manuscript describes the evolution of hemodynamic monitoring from simple manual methods to artificial intelligence integrated monitoring and prediction systems. Manual methods, like palpation of peripheral pulse, capillary refill time and auscultation are simple and crucial in detecting hemodynamic changes during surgery. However, these methods are time consuming, difficult to monitor continuously and have limited reliability in critical situations like hypotension or hypothermia. Over time, advances in technology have improved perioperative monitoring through the invention of various non-invasive monitors like electrocardiogram, pulse oximetry, oscillometric blood pressure measurement, capnography, echocardiography, tissue oximetry, etc. and invasive monitors to measure arterial pressures, venous pressures and cardiac output. These monitors have improved the accuracy of hemodynamic measurements and fluid management in critically ill patients. Recently, there has been a growing emphasis on non-invasive or minimally invasive monitoring approaches, which have fewer complications than invasive techniques. However, most of these techniques show limited accuracy during major surgeries involving major hemodynamic changes and in critically ill patients. Monitors incorporating artificial intelligence (AI)-based tools, such as the hypotension prediction index (HPI), automated echocardiographic measurements (AEM), etc., have been demonstrated to be effective in making quick and accurate diagnoses as well as in predicting perioperative complications.

Keywords: Hand on Pulse; Hypotension; Hemodynamic Monitoring; Artificial Intelligence

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