DR. MANOJ ADITYA B,DR. ASHOK KUMAR B,DR. GANESH RAMESH
DOI: https://doi.org/Subarachnoid block (spinal anesthesia) is widely employed for lower limb and lower abdominal surgeries but is frequently complicated by hypotension, posing risks to patient safety and surgical outcomes. Predicting hypotension risk preoperatively is essential for tailored anesthesia management. We designed and developed a user-friendly application that integrates multiple clinical and radiological patient parameters—including age, body mass index, pre-existing hypertension, type of surgery, antihypertensive medication use, echocardiography findings, mean arterial pressure, perfusion index, inferior vena cava collapsibility, and autonomic dysfunction—to estimate individualized hypotension risk during spinal anesthesia. Major parameters receive double weighting in the risk calculation. The application features secure, password-protected data entry and storage, supporting clinical decision-making at the point of care. This tool can enhance anesthesiologists’ ability to anticipate and manage hemodynamic changes, personalize perioperative care, and improve patient safety. Future developments aim to refine predictive accuracy, expand clinical integration, and adapt the application for broader anesthetic and surgical contexts.
