Evidence map›Paper›PMID 41113019›Full record

ArticleAmerican journal of translational research2025

Preoperative pupillary metrics as predictors of postoperative acute and chronic pain following thoracoscopic surgery: a prospective study.

Jinjian Zhu, Qiang Song, Leying Sun, Yawen Zhang, Dan Sheng, Cunxian Shi, Jin Jin

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Article in American journal of translational research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Jinjian ZhuCollege of Anesthesiology, Shandong Second Medicine University Weifang 264021, Shandong, China.
Qiang SongDepartment of Anesthesiology, PLA 960th Hospital Jinan 250000, Shandong, China.
Leying SunDepartment of Anesthesiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Yantai 264000, Shandong, China.
Yawen ZhangCollege of Clinical Medicine, Binzhou Medical University Yantai 264000, Shandong, China.
Dan ShengCollege of Anesthesiology, Shandong Second Medicine University Weifang 264021, Shandong, China.
Cunxian ShiDepartment of Anesthesiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Yantai 264000, Shandong, China.
Jin JinDepartment of Anesthesiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Yantai 264000, Shandong, China.

Funding

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6 · The paper itself

Abstract

objectivesTo elucidate the correlation between preoperative pupillary parameters, obtained via automated pupillometry, and postoperative pain outcomes in patients undergoing thoracoscopic surgery.

methodsBetween 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.

resultsMultivariate 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).

conclusionThis study establishes novel pupillometric biomarkers as independent risk factors for post-thoracoscopic pain, providing valuable insights for targeted pain management strategies.

Indexed as

acute postoperative painchronicization of acute painchronic postoperative painPupil

Identifiers

PMID41113019
PMCPMC12531525

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