Saccade Tasks: A Noninvasive Approach for Predicting Postoperative Delirium in Elderly Arthroplasty Patients.

Journal: Anesthesiology
Published Date: Dec 4, 2025

Abstract

BACKGROUND: Postoperative delirium (POD) is a prevalent complication in elderly surgical patients. It is associated with long-term cognitive impairment and increased dementia risk. However, reliable tools to predict POD are currently lacking. METHODS: The study enrolled 316 arthroplasty patients (aged 65 yr or older) in this study. Preoperative assessments comprised neuropsychological tests ( i.e. , Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]), molecular biomarkers of serum/cerebrospinal fluid, and saccadic tasks. POD was diagnosed by expert persons based on the Confusion Assessment Method test. The effectiveness of abovementioned three types of assessments in predicting the occurrence of POD were compared. RESULTS: The incidence of POD was 8.2% (26 of 316). The MMSE and MoCA scales, serum neurofilament light chain levels, and five saccadic parameters values (reaction time, primary saccade error, saccadic gains in pro-saccades; peak velocity in anti-saccades and memory-guided saccades) differed significantly ( P < 0.05) between POD and non-POD participants. The logistic regression classifier model revealed higher predictive accuracy when using saccadic parameters (area under the receiver operating characteristic curve [AUROC], 0.81; 95% CI, 0.70 to 0.92) than when using MMSE and MoCA scores (AUROC, 0.64; 95% CI, 0.53 to 0.76) or neurofilament light chain levels (AUROC, 0.61; 95% CI, 0.50 to 0.72). The multilayer perceptron machine learning classifier model further increased the accuracy (AUROC, 0.89; 95% CI, 0.82 to 0.94) by using saccadic parameters to predict POD occurrence. CONCLUSIONS: Saccadic parameters exhibited higher accuracy in predicting the occurrence of POD than MMSE and MoCA scores and molecular test results. Therefore, saccadic parameters may serve as a complementary behavioral biomarker for predicting the occurrence of POD in elderly arthroplasty patients.

Authors

  • Meng Kang
    Key Laboratory of Symbolic Computation and Knowledge Engineering (Jilin University), Changchun 130012, China; College of Computer Science and Technology, Jilin University, Changchun 130012, China. Electronic address: [email protected].
  • Xuan Lai
    Department of Geriatrics, Peking University Third Hospital, Beijing, China.
  • Junru Wu
  • Qian Xiang
    Department of Anesthesiology, Peking University Third Hospital, Beijing, China.
  • Liwen Chen
    Shanghai Engineering Research Center of Ultra-precision Optical Manufacturing, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Green Photoelectron Platform, Department of Optical Science and Engineering, Fudan University, 220 Handan Road, Shanghai, 200433, China.
  • Xiang Li
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Jiawen Su
    Department of Anesthesiology, Peking University Third Hospital, Beijing, China.
  • Zhe Ma
    Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Abdominal Medical Imaging, Jinan, 250014, China. [email protected].
  • Yalin Wang
    Comp.Sci.& Engin, Arizona State Univ, Arizona, USA.
  • Wuji Zhao
    State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Division of Psychology, Beijing Normal University, Beijing, China.
  • Yang Li
    Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.
  • Hua Zhang
    School of Clinical Medicine, Hangzhou Medical College, Hangzhou, China.
  • Jiansuo Zhou
    Department of Laboratory Medicine, Peking University Third Hospital, Beijing, China.
  • Mingsha Zhang
    College of Preschool Education, Capital Normal University, Beijing, China.
  • Xiangyang Guo
    Department of Anesthesiology, Peking University Third Hospital, Beijing, China.
  • Yongzheng Han
    Department of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Road, Haidian District, Beijing 100191, China.

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