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Updated: Nov 3, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Preoperative Serum Metabolites and Potential Biomarkers for Perioperative Cognitive Decline in Elderly Patients
Wenbin Lu1, Zhengyu Jiang1,2, Jie Huang1
1Faculty of Anesthesiology, Changhai Hospital, Naval Medical University, Shanghai, China.
Abstract:
Perioperative cognitive decline is one of the perioperative neurocognitive disorders common to see in elderly patients. Although POCD increases patient mortality and hospitalization time, the exact inflammatory and related mechanisms are still unknown. Besides, the diagnosis of POCD lacks a unified and straightforward evaluation neuropsychological scale. Metabolites could reveal chemical fingerprints left behind by the cellular process, which provides a new aspect to understand the biological process behind. According to the post-operative MMSE score, 56 patients who received elective orthopedics surgery were included and divided into POCD and Non-POCD groups. Preoperative serum metabolites in both groups and post-operative serum metabolites were analyzed. We then performed an SVM model using 10 differential metabolites in preoperative samples as features to evaluate the patients' risk of POCD, which appeared to be positively associated with POCD and could be a potential biomarker. We also analyzed differential serum metabolites from preoperative and post-operative samples of POCD patients. By analyzing their overlap differential metabolites with between POCD and Non-POCD patients, we further inferred seven metabolites positively related to the POCD mechanism. Our results provide a more convenient method to aid POCD diagnosis and prevention using biomarkers and explore the possible mechanism behind.
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