Abstract
OBJECTIVES: To elucidate the correlation between preoperative pupillary parameters, obtained via automated pupillometry, and postoperative pain outcomes in patients undergoing thoracoscopic surgery. METHODS: Between July and October 2023, 116 patients scheduled for thoracoscopic procedures under general anesthesia were prospectively enrolled. Preoperative pupillary metrics were systematically recorded using an automated pupillometer. Postoperative acute and chronic pain were rigorously assessed using the Numerical Rating Scale (NRS) and structured telephone follow-ups. Logistic regression analyses were employed to examine the association between perioperative pupillary variables and postoperative pain intensity. Receiver operating characteristic (ROC) curve analyses and clinical prediction models were constructed to evaluate the predictive capacity of these parameters. RESULTS: Multivariate analysis identified age, gender, American Standards Association (ASA) classification, minimum pupil diameter [Odd Ratio (OR) = 0.37, P = 0.006], contraction latency (OR = 1.38, P = 0.007), and average dilation velocity (ADV; OR = 15.62, P = 0.003) as independent predictors of acute postoperative pain. The composite clinical prediction model demonstrated good predictive efficacy, with area under the ROC curve values of 0.802 in the training set and 0.819 in the validation cohort. Notably, average dilation velocity (ADV) emerged as a robust independent predictor of both chronic postoperative pain (OR = 223.13, 95% CI = 13.16-3782.33, P < 0.001) and acute-to-chronic pain transition (OR = 59.75, 95% CI = 1.81-1969.32, P = 0.022). CONCLUSION: This study establishes novel pupillometric biomarkers as independent risk factors for post-thoracoscopic pain, providing valuable insights for targeted pain management strategies.