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Inflammatory and nutritional markers predict the risk of post-operative delirium in elderly patients following total hip arthroplasty

Authors :
Wenhao Hu
Ziyi Song
Houlai Shang
Jingcheng Wang
Yuedong Hao
Source :
Frontiers in Nutrition, Vol 10 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

ObjectivesThis study intended to explore whether albumin-associated inflammatory and nutritional markers could predict post-operative delirium (POD) in older patients after total hip arthroplasty (THA). In addition, we established a nomogram model for POD prediction.MethodsTotally, 254 elderly cases who received THA were included. Clinical and laboratory data of these patients were retrospectively collected. Albumin-associated inflammatory and nutritional markers included neutrophil-to-albumin ratio (NAR), CRP-to-albumin ratio (CAR), prognostic nutritional index (PNI), and systemic inflammation score (SIS). The LASSO, univariate and multivariate logistic regression analyses were utilized to screen risk factors. A nomogram model was developed according to the results of multivariate regression analyses.ResultsAmong 254 patients, 49 cases had POD with an incidence of 19.3%. LASSO regression and multivariate logistic analyses suggested that preoperative NAR, preoperative PNI, preoperative SIS, and age >75 years were risk factors for POD. A nomogram model was developed according to the results of multivariate logistic analyses. The calibration curve suggested that the predicted probability of this nomogram model was in good line with the actual probability. The DCA showed that this nomogram model had net benefits for the prediction of POD for elderly patients following THA.ConclusionAlbumin-associated inflammatory and nutritional markers including NAR, PNI, and SIS could predict POD in elderly patients following THA.

Details

Language :
English
ISSN :
2296861X
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Nutrition
Publication Type :
Academic Journal
Accession number :
edsdoj.9634b03bb0b5425795f3ebf3053195f1
Document Type :
article
Full Text :
https://doi.org/10.3389/fnut.2023.1158851