Intraoperative Hypotension Prediction: Proactive Perioperative
Hemodynamic Management
Affiliations
1
Department of Anesthesia and Intensive Care, Bangabandhu Sheikh Mujib Medical University (BSMMU), Shahbag, Dhaka-1205, Bangladesh
2
Department of Occupational and Environmental Health, Bangladesh University of Health Science, 125, Technical Mor, 1 Darus Salam Rd, Dhaka 1216
Abstract
Intraoperative hypotension (IOH) is a frequent complication during surgery, associated with
adverse outcomes such as acute kidney injury, myocardial infarction, and increased mortality.
Recent developments have proactively improved the ability to manage IOH in hemodynamic
monitoring and predictive analytics. Clinicians can anticipate hypotensive episodes up to 15
minutes in advance thanks to predictive tools like the Hypotension Prediction Index (HPI), which
analyzes arterial pressure waveforms using machine learning algorithms. In various surgical
settings, including major abdominal and orthopedic procedures, these instruments have shown
significant decreases in the incidence and duration of IOH when paired with goal-directed
therapy and decision-support systems. Research also shows how crucial continuous noninvasive
blood pressure monitoring is for detecting hemodynamic changes in real time, which improves
patient stability and lowers consequences.
Additionally, precision and customized hemodynamic control are provided by closed-loop
devices for fluid treatment and vasopressor infusion management, which greatly surpass manual
adjustments. Despite these developments, there are still issues with clinicians following alert
systems and converting predictive insights into prompt actions. The importance of integrated
systems that combine enhanced hemodynamic monitoring, tailored treatment plans, and artificial
intelligence to strengthen perioperativ...
Keywords:
Intraoperative Hypotension (IOH),
Predictive Analytics, Artificial
Intelligence, Goal-Directed Therapy,
Hypotension Prediction Index (HPI)