To better predict PIH, we can gather more data. We can start by monitoring the patient’s heart rate variability (HRV) and cardiac output to get real-time insights into their cardiovascular status. This can help us spot early signs of hypotension. We should also keep an eye on oxygen saturation levels during induction to catch any sudden drops that could cause low blood pressure. Detailed information on anesthetic drug dosing can show how specific drugs affect blood pressure changes. Understanding the type and duration of surgery is important since different surgeries pose varying risks for hypotension. Lastly, being aware of operating room conditions helps us consider environmental and circadian factors, which can influence a patient’s physiological response.

To improve predictive models for PIH and address current limitations, future research should focus on a few key areas. First, studies should be conducted at multiple sites and include a variety of surgical procedures, such as orthopedic, cardiovascular, and neurosurgical operations, to make the models relevant to different types of patients and surgeries. Long-term studies and real-time monitoring are important for understanding outcomes over time and continuously updating the models during surgeries. To ensure these models are effectively integrated into clinical workflows, we need to include clinical expertise through Clinical Decision Support Systems (CDSS) and create user-friendly interfaces. Ethical and regulatory considerations, including obtaining patient consent and ensuring data privacy, must be strictly followed. Continuous model improvement can be achieved by establishing feedback loops with clinicians and developing adaptive learning models that evolve with new data. By focusing on these future research directions, we can make PIH predictive models more accurate, reliable, and applicable across various surgical procedures and patient populations.

Thanks for your presentation, Teeraboon. You explained clearly on things that I didn’t understand when I read the article.