• Ling-Xia Song, Yi Qin, Li Yang, Ding-Bi Xing, Ying Li, Fu-Qi Lei, and Lian-Hong Wang.
• Department of Orthopedics, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
• Medicine (Baltimore). 2024 Jun 28; 103 (26): e38745e38745.

AbstractThis study aimed to establish an effective predictive model for postoperative delirium (POD) risk assessment after total knee arthroplasty (TKA) in older patients. The clinical data of 446 older patients undergoing TKA in the Orthopedics Department of our University from January to December 2022 were retrospectively analyzed, and the POD risk prediction model of older patients after TKA was established. Finally, 446 patients were included, which were divided into training group (n = 313) and verification group (n = 133). Logistic regression method was used to select meaningful predictors. The prediction model was constructed with nomographs, and the model was evaluated with correction curve and receiver operating characteristic curve. The logistic regression analysis showed that age, educational level, American Society of Anesthesiologists grade, accompaniment of chronic obstructive pulmonary disease, accompaniment of cerebral stroke, postoperative hypoxemia, long operation time, and postoperative pain were independent risk factors for POD after TKA (P < .05). The nomogram prediction model established. The area under receiver operating characteristic curve of the model group and the validation group were 0.954 and 0.931, respectively. The calibration curve of the prediction model has a high consistency between the 2 groups. The occurrence of POD was associated with age, educational level, American Society of Anesthesiologists grade, accompaniment of chronic obstructive pulmonary disease, accompaniment of cerebral stroke, postoperative hypoxemia, long operation time, and postoperative pain in TKA patients.Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.

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