Evaluation of Radiographic Outcomes after Core Decompression for Osteonecrosis of the Femoral Head: The Beijing University of Chinese Medicine X-ray Evaluation Method

Relationship between lipid metabolism, coagulation and other blood indices and etiology and staging of non-traumatic femoral head necrosis: a multivariate logistic regression-based analysis

BACKGROUND

To analyze the relationship between lipid metabolism, coagulation function, and bone metabolism and the contributing factor and staging of non-traumatic femoral head necrosis, and to further investigate the factors influencing the blood indicators related to the staging of non-traumatic femoral head necrosis.

METHODS

The medical records of patients with femoral head necrosis were retrieved from the inpatient medical record management system, and the lipid metabolism, bone metabolism, and coagulation indices of non-traumatic femoral head necrosis (including alcoholic, hormonal, and idiopathic group) were obtained according to the inclusion and exclusion criteria, including Low-Density Lipoprotein Cholesterol, Triglycerides, Non-High-Density Lipoprotein Cholesterol, Apolipoprotein A1, Apolipoprotein (B), Apolipoprotein (E), Uric Acid, Alkaline Phosphatase, Bone-specific Alkaline Phosphatase, Activated Partial Thromboplastin Time, Prothrombin Time, D-dimer, Platelet count. The relationship between these blood indices and the different stages under different causative factors was compared, and the factors influencing the stages of non-traumatic femoral head necrosis were analyzed using multivariate logistic regression.

RESULTS

(i) Gender, Age and BMI stratification, Low-density Lipoprotein Cholesterol, Triglycerides, Non-High-density Lipoprotein Cholesterol, Apolipoprotein (B), Apolipoprotein (E), Uric Acid, Bone-specific Alkaline Phosphatase, Activated Partial Thromboplastin Time, Plasminogen Time, D-dimer, and Platelet count of the alcohol group were statistically different when compared among the different ARCO staging groups; (ii) The differences in Age and BMI stratification, Triglycerides, Non-High-density Lipoprotein Cholesterol, Apolipoprotein A1, Apolipoprotein B, Apolipoprotein E, Uric Acid, Bone-specific Alkaline Phosphatase, Activated Partial Thromboplastin Time, Plasminogen Time, D-dimer, and Platelet count were statistically significant when compared among the different phases in the hormone group (P < 0.05); (iii) The differences in Age and BMI stratification, Non-High-Density Lipoprotein Cholesterol, Apolipoprotein A1, Apolipoprotein (B), Apolipoprotein (E), Uric Acid, Activated Partial Thromboplastin Time, D-dimer, and Platelet count were statistically significant when compared among the different stages in the idiopathic group (P < 0.05); (v) Statistically significant indicators were included in the multivariate logistic regression analysis, excluding the highly correlated bone-specific alkaline phosphatase, and the results showed that Low-density lipoprotein was negatively correlated with changes in the course of ARCO, and Non-High-Density Lipoprotein cholesterol, Apo B, Activated Partial Thromboplastin Time, and Platelet count were significantly and positively correlated with disease progression.

CONCLUSION

An abnormal hypercoagulable state as well as an abnormal hyperlipidemic state are risk factors for the progression of non-traumatic femoral head necrosis under various exposure factors, as indicated by Non-High-Density Lipoprotein Cholesterol, Apolipoprotein B, Activated Fractional Thromboplastin Time, and Platelet Counts.

Development of a risk-predicting score for hip preservation with bone grafting therapy for osteonecrosis

Identification and differentiation of appropriate indications on hip preserving with bone grafting therapy remains a crucial challenge in the treatment of osteonecrosis of the femoral head (ONFH). A prospective cohort study on bone grafting therapy for ONFH aimed to evaluate hip survival rates, and to establish a risk scoring derived from potential risk factors (multivariable model) for hip preservation. Eight variables were identified to be strongly correlated with a decreased rate of hip survival post-therapy, and a comprehensive risk scoring was developed for predicting hip-preservation outcomes. The C-index stood at 0.72, and the areas under the receiver operating characteristics for the risk score's 5- and 10-year hip failure event predictions were 0.74 and 0.72, respectively. This risk score outperforms conventional methods in forecasting hip preservation. Bone grafting shows sustained benefits in treating ONFH when applied under the right indications. Furthermore, the risk scoring proves valuable as a decision-making tool, facilitating risk stratification for ONFH treatments in future.

Exploring the potential mechanism of Taohong Siwu decoction in the treatment of avascular necrosis of the femoral head based on network pharmacology and molecular docking

Based on network pharmacology and molecular docking, this study seeks to investigate the mechanism of Taohong Siwu decoction (THSWD) in the treatment of avascular necrosis of the femoral head (AVNFH). The Traditional Chinese Medicine Systems Pharmacology database was used in this investigation to obtain the active ingredients and related targets for each pharmaceutical constituent in THSWD. To find disease-related targets, the terms "avascular necrosis of the femoral head," "necrosis of the femoral head," "steroid-induced necrosis of the femoral head," "osteonecrosis," and "avascular necrosis of the bone" were searched in the databases DisGeNET, GeneCards, Comparative Toxicogenomics Database, and MalaCards. Following the identification of the overlap targets of THSWD and AVNFH, enrichment analysis using gene ontology, Kyoto Encyclopedia of Genes and Genomes, Reactome, and WikiPathways was conducted. The "THSWD-drug-active compound-intersection gene-hub gene-AVNFH" network and protein-protein interaction network were built using Cytoscape 3.9.1 and string, and CytoHubba was used to screen hub genes. The binding activities of hub gene targets and key components were confirmed by molecular docking. 152 prospective therapeutic gene targets were found in the bioinformatics study of ONFH treated with THSWD, including 38 major gene targets and 10 hub gene targets. The enrichment analysis of 38 key therapeutic targets showed that the biological process of gene ontology analysis mainly involved cytokine-mediated signaling pathway, angiogenesis, cellular response to reactive oxygen species, death-inducing signaling complex. The Kyoto Encyclopedia of Genes and Genomes signaling pathway mainly involves TNF signaling pathway, IL-17 signaling pathway, and the Recactome pathway mainly involves Signaling by Interleukins, Apoptosis, and Intrinsic Pathway for Apoptosis. WikiPathways signaling pathway mainly involves TNF-related weak inducer of apoptosis signaling pathway, IL-18 signaling pathway. According to the findings of enrichment analysis, THSWD cured AVNFH by regulating angiogenesis, cellular hypoxia, inflammation, senescence, apoptosis, cytokines, and cellular proliferation through the aforementioned targets and signaling pathways. The primary component of THSWD exhibits a strong binding force with the key protein of AVNFH. This study sheds new light on the biological mechanism of THSWD in treating AVNFH by revealing the multi-component, multi-target, and multi-pathway features and molecular docking mechanism of THSWD.

Systematic analysis of hip-preserving treatment for early osteonecrosis of the femoral head from the perspective of bibliometrics (2010-2023)

BACKGROUND

Osteonecrosis of the femoral head (ONFH) is a serious condition that causes bone tissue death, femoral head collapse, and hip joint destruction. Early intervention through hip-preserving treatment is crucial to slow down disease progression, preserve hip joint function, and improve the quality of life of patients. We analyzed the knowledge map, research gaps, and future research directions in the field of hip-preserving treatment for early ONFH.

METHODS

All publications related to hip-preserving treatment for early ONFH published between 2010 and 2023 were identified from the Web of Science Core Collection and analyzed using VOSviewer 1.6.19, CiteSpace 6.2.R2, and Scimago Graphica 1.0.35.

RESULTS

In total, 234 articles were analyzed. The results showed an exponential growth trend in the number of publications related to hip-preserving treatment for early ONFH in the past decade. China and the USA were the main contributors. International Orthopaedics published the most papers in this field, whereas Bone and Joint Surgery-American Volume had the highest average citation count per article. Several stable research topics were noted in this field, including core decompression (CD), osteotomy, bone transplantation in hip-preserving surgery, and cell therapy, which have become research hotspots in hip-preserving treatment.

CONCLUSIONS

Hip-preserving treatment for early ONFH has received increasing attention, and research in this field is expected to grow. Stable research topics include core decompression (CD), osteotomy, bone transplantation, and cell therapy. Future research is predicted to focus on cell therapy and combination therapy, resulting in an increasing number of publications on hip-preserving treatment for early ONFH.

Deep Learning Approach for Diagnosing Early Osteonecrosis of the Femoral Head Based on Magnetic Resonance Imaging

BACKGROUND

The diagnosis of early osteonecrosis of the femoral head (ONFH) based on magnetic resonance imaging (MRI) is challenging due to variability in the surgeon's experience level. This study developed an MRI-based deep learning system to detect early ONFH and evaluated its feasibility in the clinic.

METHODS

We retrospectively evaluated clinical MRIs of the hips that were performed in our institution from January 2019 to June 2022 and collected all MRIs diagnosed with early ONFH. An advanced convolutional neural network (CNN) was trained and optimized; then, the diagnostic performance of the CNN was evaluated according to its accuracy, sensitivity, and specificity. We also further compared the CNN's performance with that of orthopaedic surgeons.

RESULTS

Overall, 11,061 images were retrospectively included in the present study and were divided into three datasets with ratio 7:2:1. The area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity of the CNN model for identifying early ONFH were 0.98, 98.4, 97.6, and 98.6%, respectively. In our review panel, the averaged accuracy, sensitivity, and specificity for identifying ONFH were 91.7, 87.0, and 94.1% for attending orthopaedic surgeons; 87.1, 84.0, and 89.3% for resident orthopaedic surgeons; and 97.1, 96.0, and 97.9% for deputy chief orthopaedic surgeons, respectively.

CONCLUSION

The deep learning system showed a comparable performance to that of deputy chief orthopaedic surgeons in identifying early ONFH. The success of deep learning diagnosis of ONFH might be conducive to assisting less-experienced surgeons, especially in large-scale medical imaging screening and community scenarios lacking consulting experts.