ABSTRACT
BACKGROUND: Postoperative analgesia is widely used for patients undergoing major surgeries. Individual differences in genetic polymorphisms may be obstructive factors for accurately anesthetics using. However, the equation for predicting sufentanil dosage postoperatively based on genetic design has been established yet. Our aim was to establish sufentanil dosage postoperatively prediction equation based on patients' genetic polymorphisms. METHODS: One hundred forty patients with total gastrectomy and radical resection of pulmonary carcinoma were included. To establish sufentanil dosage postoperatively for patients with gastric cancer, we collected patients' basic information and CYP3A4*1G, COMTVal158Met, OPRM1A118G, and ABCB1C3435T gene sequencing results. To verify this equation, we put patients' with lung cancer surgeries information into it. RESULTS: The sufentanil dosage prediction equation postoperatively was y = 4.104 - 0.222 × (gender) + 0.021 × (OPRM1A118G) + 0.249 × (ABCB1C3435T). Patients' with lung cancer surgeries information were substituted into it. The results showed no significant differences between predicted and actual sufentanil dosage (p > 0.05). CONCLUSION: We established the prediction equation for individual sufentanil dosage postoperatively based on gene polymorphisms. The results showed this prediction equation was valid, which might be used for different types of surgeries. We established an equation for individual dosage of sufentanil for postoperative analgesia based on gene polymorphisms. The results show that the prediction equation is valid, the information might be used for different types of postoperative analgesia, and the painful patients will have great potential safe and personalized pain control after analgesic therapy. It might also have potential as a clinical tool.
