Changes in Serum Inflammatory Factors After Hip Arthroplasty and Analysis of Risk Factors for Prosthesis Loosening

Overview

Journal Am J Transl Res

Specialty General Medicine

Date 2024 Mar 11

PMID 38463599

Authors

Ming He

Qingsheng Zhu

Dayu Yin

Yonghong Duan

Pengxiao Sun

Qing Fang

Affiliations

Soon will be listed here.

Abstract

Objective: To explore the relationship of serum levels of IL-1β, IL-6, and TNF-α with prosthesis loosening after hip arthroplasty, and to establish a predictive model for prosthesis loosening.

Methods: We retrospectively analyzed the data of 501 patients who underwent hip arthroplasty in Xi'an International Medical Center Hospital from January 2020 to August 2022. Based on radiological diagnosis, the patients were divided into a prosthesis loosening group and a non-loosening group. Clinical data including postoperative serum levels of inflammatory cytokines were collected. Univariant analysis, Lasso regression, decision tree, and random forest models were used to screen feature variables. Based on the screening results, a nomogram model for predicting the risk of prosthesis loosening was established and then validated using ROC curve, and calibration curve, and other methods.

Results: There were 50 cases in the loosening group and 451 cases in the non-loosening group. Postoperative levels of IL-1β, IL-6, and TNF-α were found to be significantly higher in the loosening group (P<0.0001). Univariant analysis showed that osteoporosis and postoperative infection were risk factors for prosthesis loosening (P<0.001). The machine learning algorithm identified osteoporosis, postoperative infection, IL-1β, IL-6, and TNF-α as 5 relevant variables. The predictive model based on these 5 variables exhibited an area under the ROC curve of 0.763. The calibration curve and DCA curve verified the accuracy and practicality of the model.

Conclusion: Serum levels of IL-1β, IL-6, and TNF-α were significantly elevated in patients with postoperative prosthesis loosening. Osteoporosis, postoperative infection, and inflammatory cytokines are independent risk factors for prosthesis loosening. The predictive model we established through machine learning can effectively determine the risk of prosthesis loosening. Monitoring inflammatory cytokines and postoperative infections, combined with prevention of osteoporosis, can help reduce the risk of prosthesis loosening.

Citing Articles

Effects of electrical stimulation with alternating fields on the osseointegration of titanium implants in the rabbit tibia - a pilot study.

Klinder A, Mows F, Ziebart J, Su Y, Gabler C, Jonitz-Heincke A Front Bioeng Biotechnol. 2024; 12:1395715.

PMID: 39113790 PMC: 11303232. DOI: 10.3389/fbioe.2024.1395715.

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