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Li ZY, Li Z, Xu C, Fu J, Maimaiti Z, Hao LB, Zhang QM, Chen JY. Hypoalbuminemia is Highly Prevalent in Patients with Periprosthetic Joint Infection and Strongly Associated with Treatment Failure. Orthop Surg 2024. [PMID: 39054735 DOI: 10.1111/os.14162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/16/2024] [Accepted: 06/18/2024] [Indexed: 07/27/2024] Open
Abstract
OBJECTIVE The role of hypoalbuminemia throughout the course of chronic periprosthetic joint infection (PJI) remains poorly understood. This study aimed to determine the prevalence and risk factors of hypoalbuminemia in periprosthetic joint infection (PJI) patients and to explore the association between hypoalbuminemia and treatment outcomes. METHODS This retrospective cohort study included 387 PJI cases who underwent two-stage exchange arthroplasty between January 2007 and August 2020, of which 342 were reimplanted. The mean follow-up period was 7.9 years. Multivariate logistic regression analyses were performed to identify risk factors for hypoalbuminemia and to assess the effect of hypoalbuminemia at 1st- and 2nd-stage exchange on the treatment outcome. Furthermore, the impact of dynamic changes in hypoalbuminemia was investigated. RESULTS The prevalence of hypoalbuminemia at 1st- and 2nd-stage exchange was 22.2% and 4.7%, respectively. Patients with age ≥ 68 years and those with isolation of Staphylococcus aureus, Streptococcus, or Gram-negative bacteria exhibited a higher risk of hypoalbuminemia. Hypoalbuminemia at 1st-stage was significantly related to treatment failure (OR = 3.3), while hypoalbuminemia at 2nd-stage raised the OR to 10.0. Patients with persistent hypoalbuminemia at both the 1st- and 2nd-stage exchanges had a significantly higher rate of treatment failure than patients with hypoalbuminemia at the 1st-stage but normal albumin levels at the 2nd-stage exchange (55.6% vs 20.0%, p = 0.036). CONCLUSION One in five patients with chronic PJI exhibits hypoalbuminemia. Hypoalbuminemia is more likely to develop in patients of advanced age and those infected by specific highly virulent organisms. Also, our results highlight the close association between hypoalbuminemia and treatment outcomes.
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Affiliation(s)
- Zhi-Yuan Li
- Medical School of Chinese PLA, Beijing, China
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Zhuo Li
- Department of Joint Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- School of Medicine, Nankai University, Tianjin, China
| | - Chi Xu
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jun Fu
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Zulipikaer Maimaiti
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, Beijing Luhe Hospital, Capital Medical University, Beijing, China
| | - Li-Bo Hao
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Qing-Meng Zhang
- Department of Orthopaedics, Qilu Hospital of Shandong University, Jinan, China
| | - Ji-Ying Chen
- Medical School of Chinese PLA, Beijing, China
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, China
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Telang S, Mayfield CK, Palmer R, Liu KC, Wier J, Hong K, Lieberman JR, Heckmann ND. Preoperative Laboratory Values Predicting Periprosthetic Joint Infection in Morbidly Obese Patients Undergoing Total Hip or Knee Arthroplasty. J Bone Joint Surg Am 2024; 106:1317-1327. [PMID: 38941451 DOI: 10.2106/jbjs.23.01360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
BACKGROUND Morbidly obese patients are an ever-growing high-risk population undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA) for end-stage osteoarthritis. This study sought to identify preoperative laboratory values that may serve as predictors of periprosthetic joint infection (PJI) in morbidly obese patients undergoing THA or TKA. METHODS All morbidly obese patients with preoperative laboratory data before undergoing primary elective TKA or THA were identified using the Premier Healthcare Database. Patients who developed PJI within 90 days after surgery were compared with patients without PJI. Laboratory value thresholds were defined by clinical guidelines or primary literature. Univariate and multivariable regression analyses were utilized to assess the association between PJI and preoperative laboratory values, including total lymphocyte count, neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), albumin level, platelet count, albumin-globulin ratio, hemoglobin level, and hemoglobin A1c. RESULTS Of the 6,780 patients identified (TKA: 76.67%; THA: 23.33%), 47 (0.69%) developed PJI within 90 days after surgery. The rate of PJI was 1.69% for patients with a hemoglobin level of <12 g/dL (for females) or <13 g/dL (for males), 2.14% for those with a platelet count of <142,000/µL or >417,000/µL, 1.11% for those with an NLR of >3.31, 1.69% for those with a PLR of >182.3, and 1.05% for those with an SII of >776.2. After accounting for potential confounding factors, we observed an association between PJI and an abnormal preoperative NLR (adjusted odds ratio [aOR]: 2.38, 95% confidence interval [CI]: 1.04 to 5.44, p = 0.039), PLR (aOR: 4.86, 95% CI: 2.15 to 10.95, p < 0.001), SII (aOR: 2.44, 95% CI: 1.09 to 5.44, p = 0.029), platelet count (aOR: 3.50, 95% CI: 1.11 to 10.99, p = 0.032), and hemoglobin level (aOR: 2.62, 95% CI: 1.06 to 6.50, p = 0.038). CONCLUSIONS This study identified preoperative anemia, abnormal platelet count, and elevated NLR, PLR, and SII to be associated with an increased risk of PJI among patients with a body mass index of ≥40 kg/m 2 . These findings may help surgeons risk-stratify this high-risk patient population. LEVEL OF EVIDENCE Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.
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Affiliation(s)
- Sagar Telang
- Department of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | - Cory K Mayfield
- Department of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | - Ryan Palmer
- Department of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | - Kevin C Liu
- Department of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | - Julian Wier
- Department of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | - Kurt Hong
- Department of Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | - Jay R Lieberman
- Department of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | - Nathanael D Heckmann
- Department of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California
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Li Z, Li ZY, Maimaiti Z, Yang F, Fu J, Hao LB, Chen JY, Xu C. Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection. Heliyon 2024; 10:e26062. [PMID: 38370241 PMCID: PMC10867348 DOI: 10.1016/j.heliyon.2024.e26062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 02/06/2024] [Accepted: 02/07/2024] [Indexed: 02/20/2024] Open
Abstract
Background The immune response associated with periprosthetic joint infection (PJI) is an emerging but relatively unexplored topic. The aim of this study was to investigate immune cell infiltration in periprosthetic tissues and identify potential immune-related biomarkers. Methods The GSE7103 dataset from the GEO database was selected as the data source. Differentially expressed genes (DEGs) and significant modular genes in weighted correlation network analysis (WGCNA) were identified. Functional enrichment analysis and transcription factor prediction were performed on the overlapping genes. Next, immune-related genes from the ImmPort database were matched. The protein-protein interaction (PPI) analysis was performed to identify hub genes. CIBERSORTx was used to evaluate the immune cell infiltration pattern. Spearman correlation analysis was used to evaluate the relationship between hub genes and immune cells. Results A total of 667 DEGs were identified between PJI and control samples, and 1847 PJI-related module genes were obtained in WGCNA. Enrichment analysis revealed that the common genes were mainly enriched in immune and host defense-related terms. TFEC, SPI1, and TWIST2 were the top three transcription factors. Three hub genes, SDC1, MMP9, and IGF1, were identified in the immune-related PPI network. Higher levels of plasma cells, CD4+ memory resting T cells, follicular helper T cells, resting mast cells, and neutrophils were found in the PJI group, while levels of M0 macrophages were lower. Notably, the expression of all three hub genes correlated with the infiltration levels of seven types of immune cells. Conclusion The present study revealed immune infiltration signatures in the periprosthetic tissues of PJI patients. SDC1, MMP9, and IGF1 were potential immune-related biomarkers for PJI.
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Affiliation(s)
- Zhuo Li
- Medical School of Chinese PLA, Beijing, China
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- School of Medicine, Nankai University, Tianjin, China
- Department of Joint Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Zhi-Yuan Li
- Medical School of Chinese PLA, Beijing, China
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Zulipikaer Maimaiti
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, Beijing Luhe Hospital, Capital Medical University, Beijing, China
| | - Fan Yang
- Medical School of Chinese PLA, Beijing, China
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- School of Medicine, Nankai University, Tianjin, China
| | - Jun Fu
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Li-Bo Hao
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Ji-Ying Chen
- Medical School of Chinese PLA, Beijing, China
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- School of Medicine, Nankai University, Tianjin, China
| | - Chi Xu
- Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, China
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Chen W, Hu X, Gu C, Zhang Z, Zheng L, Pan B, Wu X, Sun W, Sheng P. A machine learning-based model for "In-time" prediction of periprosthetic joint infection. Digit Health 2024; 10:20552076241253531. [PMID: 38766360 PMCID: PMC11100394 DOI: 10.1177/20552076241253531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 04/22/2024] [Indexed: 05/22/2024] Open
Abstract
Background Previous criteria had limited value in early diagnosis of periprosthetic joint infection (PJI). Here, we constructed a novel machine learning (ML)-derived, "in-time" diagnostic system for PJI and proved its validity. Methods We filtered "in-time" diagnostic indicators reported in the literature based on our continuous retrospective cohort of PJI and aseptic prosthetic loosening patients. With the indicators, we developed a two-level ML model with six base learners including Elastic Net, Linear Support Vector Machine, Kernel Support Vector Machine, Extra Trees, Light Gradient Boosting Machine and Multilayer Perceptron), and one meta-learner, Ensemble Learning of Weighted Voting. The prediction performance of this model was compared with those of previous diagnostic criteria (International Consensus Meeting in 2018 (ICM 2018), etc.). Another prospective cohort was used for internal validation. Based on our ML model, a user-friendly web tool was developed for swift PJI diagnosis in clinical practice. Results A total of 254 patients (199 for development and 55 for validation cohort) were included in this study with 38.2% of them diagnosed as PJI. We included 21 widely accessible features including imaging indicators (X-ray and CT) in the model. The sensitivity and accuracy of our ML model were significantly higher than ICM 2018 in development cohort (90.6% vs. 76.1%, P = 0.032; 94.5% vs. 86.7%, P = 0.020), which was supported by internal validation cohort (84.2% vs. 78.6%; 94.6% vs. 81.8%). Conclusions Our novel ML-derived PJI "in-time" diagnostic system demonstrated significantly improved diagnostic potency for surgical decision-making compared with the commonly used criteria. Moreover, our web-based tool greatly assisted surgeons in distinguishing PJI patients comprehensively. Level of evidence Diagnostic Level III.
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Affiliation(s)
- Weishen Chen
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xuantao Hu
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Chen Gu
- School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China
| | - Zhaohui Zhang
- Department of Diagnostic Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Linli Zheng
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Baiqi Pan
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xiaoyu Wu
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Wei Sun
- School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China
| | - Puyi Sheng
- Department of Joint Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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Choe H, Kamono E, Abe K, Hieda Y, Ike H, Kumagai K, Kobayashi N, Inaba Y. Accuracy of Albumin, Globulin, and Albumin-Globulin Ratio for Diagnosing Periprosthetic Joint Infection: A Systematic Review and Meta-Analysis. J Clin Med 2023; 12:7512. [PMID: 38137581 PMCID: PMC10743640 DOI: 10.3390/jcm12247512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 12/24/2023] Open
Abstract
Periprosthetic joint infection (PJI) is one of the most intractable orthopedic diseases, partly because of the difficulty in differentiating septic from aseptic conditions. We aimed to evaluate and consolidate the diagnostic accuracy of the quantitative assessment of serum albumin (Alb), globulin (Glb), and albumin-globulin ratio (AGR), alone or in combination with the inflammatory marker, C-reactive protein (CRP), for PJI. We searched the PubMed, CINAHL, and Cochrane Library databases for studies that quantitatively measured Alb, Glb, or AGR for the diagnosis of PJI up until the 30 April 2023. A total of 2339 patients were included from 10 studies, including 845 patients with a definitive diagnosis of PJI and 1494 with non-PJI. The pooled sensitivity, specificity, and area under the curve (AUC) in the summary receiver-operating characteristic curve were as follows: 0.625, 0.732, and 0.715 for Alb; 0.815, 0.857, and 0.887 for Glb; 0.753, 0.757, and 0.875 for AGR; 0.788, 0.837, and 0.876 for CRP; 0.879, 0.890, and 0.917 for the CRP-Alb ratio; and 0.845, 0.855, and 0.908 for the CRP-AGR ratio. Serum Alb, Glb, and AGR levels are feasible and accurate diagnostic markers for PJI, and the combination of these markers with CRP levels may potentially improve preoperative serum diagnostic accuracy. Future prospective studies are required to verify these findings because of the small numbers of included studies.
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Affiliation(s)
- Hyonmin Choe
- Department of Orthopedic Surgery, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama City 236-0004, Japan; (K.A.); (Y.H.); (H.I.); (K.K.); (Y.I.)
| | - Emi Kamono
- Department of Orthopedic Surgery, Yokohama City University Medical Center, 4-57 Urahune-cho, Minami-ku, Yokohama City 232-0024, Japan; (E.K.); (N.K.)
| | - Koki Abe
- Department of Orthopedic Surgery, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama City 236-0004, Japan; (K.A.); (Y.H.); (H.I.); (K.K.); (Y.I.)
| | - Yuta Hieda
- Department of Orthopedic Surgery, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama City 236-0004, Japan; (K.A.); (Y.H.); (H.I.); (K.K.); (Y.I.)
| | - Hiroyuki Ike
- Department of Orthopedic Surgery, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama City 236-0004, Japan; (K.A.); (Y.H.); (H.I.); (K.K.); (Y.I.)
| | - Ken Kumagai
- Department of Orthopedic Surgery, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama City 236-0004, Japan; (K.A.); (Y.H.); (H.I.); (K.K.); (Y.I.)
| | - Naomi Kobayashi
- Department of Orthopedic Surgery, Yokohama City University Medical Center, 4-57 Urahune-cho, Minami-ku, Yokohama City 232-0024, Japan; (E.K.); (N.K.)
| | - Yutaka Inaba
- Department of Orthopedic Surgery, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama City 236-0004, Japan; (K.A.); (Y.H.); (H.I.); (K.K.); (Y.I.)
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Wang Z, Mao H, Xu G. Fibrinogen, albumin-to-globulin ratio, and fibrinogen to albumin-to-globulin ratio may be potential diagnostic biomarkers for infected tibial nonunion. Int Immunopharmacol 2023; 121:110542. [PMID: 37356122 DOI: 10.1016/j.intimp.2023.110542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/02/2023] [Accepted: 06/17/2023] [Indexed: 06/27/2023]
Abstract
AIM The accurate preoperative diagnosis of infected tibial nonunion remains challenging. Hence, we evaluated the diagnostic potential of novel biomarkers for infected tibial nonunion. METHODS This single-center retrospective study was conducted in 252 patients divided into two groups: infected tibial nonunion (67 patients) and aseptic tibial nonunion (185 patients). The preoperative clinical biomarkers included D-dimer, fibrinogen, albumin, globulin, total protein, and C-reactive protein (CRP) levels; albumin-to-globulin ratio (AGR); erythrocyte sedimentation rate (ESR); and white blood cell (WBC) count. Receiver operating characteristic (ROC) curves, sensitivity, and specificity were utilized to compare the biomarkers' diagnostic potential. RESULTS The area under the curve (AUC) values for fibrinogen and AGR were 0.829 and 0.821, respectively, suggesting similarly good diagnostic potentials for infected tibial nonunion. Fibrinogen and AGR were better diagnostic biomarkers for infected tibial nonunion than the WBC count; ESR; D-dimer, albumin, globulin, CRP, and total protein levels, whose AUC values were 0.623, 0.684, 0.741, 0.797, 0.765, 0.715, and 0.554, respectively. The sensitivity and specificity of fibrinogen with a cut-off value of 3.35 g/L were 71.64% and 84.86%, respectively. The corresponding values for AGR with a cut-off value of 1.33 were 73.13% and 86.49%. Moreover, the fibrinogen-AGR (FAGR), i.e., the combination of fibrinogen and AGR, had the highest diagnostic accuracy for infected tibial nonunion (AUC = 0.906). The optimal FAGR cut-off was 2.69, with fair sensitivity (74.63%) but the highest specificity (94.59%). CONCLUSION Fibrinogen, AGR, and FAGR are promising biomarkers for the diagnosis of infected tibial nonunion.
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Affiliation(s)
- Zhen Wang
- Department of Orthopedic Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Haijun Mao
- Department of Orthopedic Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Guangyue Xu
- Department of Orthopedic Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
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