Chinese Journal of Tissue Engineering Research ›› 2024, Vol. 28 ›› Issue (30): 4837-4841.doi: 10.12307/2024.646

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Risk factors and establishment of a nomogram prediction model for hypoproteinemia after hip revision

Chen Junfeng1, Xie Rongzhen2, Hong Weishi3, Sun Yu3   

  1. 1School of Medicine, Yangzhou University, Yangzhou 225000, Jiangsu Province, China; 2School of Medicine and Technologe, Zunyi Medical University, Zunyi 563000, Guizhou Province, China; 3Department of Orthopedics, Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou 225000, Jiangsu Province, China
  • Received:2023-06-25 Accepted:2023-08-30 Online:2024-10-28 Published:2023-12-27
  • Contact: Sun Yu, MD, Associate chief physician, Department of Orthopedics, Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou 225000, Jiangsu Province, China
  • About author:Chen Junfeng, Chief physician, School of Medicine, Yangzhou University, Yangzhou 225000, Jiangsu Province, China

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Abstract: BACKGROUND: The high rate of postoperative hypoproteinemia in patients undergoing hip revision is associated with severe trauma, which affects the rapid recovery of patients.
OBJECTIVE: To investigate the risk factors of perioperative hypoproteinemia in patients with hip revision, and to provide guidance for early screening of high-risk patients with postoperative hypoproteinemia. 
METHODS: According to the inclusion and exclusion criteria, 161 patients who underwent hip revision were divided into hypoproteinemia group (76 cases) and normal group (85 cases). The rate of hypoproteinemia was 47.2%. Data such as age, gender, body mass index, osteoporosis, operation time, preoperative erythrocytes, preoperative hemoglobin, preoperative leukocytes, preoperative platelets, preoperative fibrinogen, preoperative C-reaction protein, preoperative sedimentation rate, preoperative blood calcium, preoperative albumin, postoperative drainage tube placement, American Society of Anesthesiologists score, and postoperative hypoproteinemia were collected. SPSS software was used to analyze the independent risk factors of hypoproteinemia after hip revision using multivariate binary logistic regression analysis. R software was used to construct the nomogram prediction model. Receiver operating characteristic curve and calibration curve and decision curve were drawn to evaluate the model. 
RESULTS AND CONCLUSION: (1) Univariate analysis results showed that body mass index, preoperative erythrocytes, preoperative hemoglobin, preoperative platelets, preoperative fibrinogen, preoperative C-reaction protein, and operation time were significantly different between the two groups (P < 0.05). (2) Multivariate binary Logistic regression analysis results showed that body mass index (OR=0.859, P=0.021), operation time (OR=1.010, P=0.002), preoperative erythrocytes (OR=0.424, P=0.036), and preoperative C-reaction protein (OR=1.043, P=0.032) levels were independent risk factors for postoperative hypoproteinemia in patients with hip revision. (3) Based on four independent risk factors: body mass index, operation time, preoperative erythrocytes and preoperative C-reaction protein, the nomogram can effectively predict the risk of hypoproteinemia after hip revision. This nomogram prediction model has good differentiation and accuracy, and may lead to better clinical net benefits for patients.

Key words: hip revision, hypoproteinemia, risk factor, nomogram, prediction model

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