Tripterygiumwilfordii Hook F (TwHF) is one of the most commonly used and effective traditional Chinese herbal medicines against rheumatoid arthritis (RA). Both Tripterygium Glycoside Tablets (TGT) and Tripterygium wilfordii Tablets (TWT) are the representative TwHF-based agents enrolled into the 2019 edition of Medicine Catalog for National Basic Medical Insurance, Injury Insurance, and Maternity Insurance. However, individual differences in TGT/TWT response across patients usually exist in the process of treating RA, implying that the clinical application of the two agents may not be standardized leading to the ineffective treatment and the risk of side effects. Growing evidence show that the bioactive constituents of TwHF may often have toxicity, the package insert of TGT and TWT may not be described in detail, and the therapeutic windows of the two agents are narrow. Thus, it is an urgent task to develop a standardized clinical practice guideline for TGT and TWT in the treatment of RA. In the current study, a group of clinical experts of traditional Chinese medicine and Western medicine in the research field of rheumatism diseases, pharmacists, and methodologists of evidence-based medicine were invited to select the clinical questions, to determine the levels of the evidence and the strength of the recommendations, and to develop the recommendations and good practice points. The guideline is formed based on the combination of clinical research evidence and expert experience (evidence-based, consensus, supplemented by experience). The clinical problems which are supported by clinical evidence may form recommendations, and the clinical problems without clinical evidence may form experts’ suggestions. Both recommendations and experts' suggestions in this guideline summarized the clinical indications, usage, dosage, combined medication, and safety of TGT and TWT against RA systematically and comprehensively, which may offer a professional guidance in the context of the clinical application of the two TwHF-based agents.
Objective To develop a prediction method for femoral head collapse by using patient‐specific finite element analysis of osteonecrosis of the femoral head (ONFH). Methods The retrospective study recruited 40 patients with ARCO stage‐II ONFH (40 pre‐collapse hips). Patients were divided into two groups according to the 1‐year follow‐up outcomes: patient group without femoral head collapse (noncollapse group, n = 20) and patient group with collapse (collapse group, n = 20). CT scans of the hip were performed for all patients once they joined the study. Patient‐specific finite element models were generated based on these original CT images following the same procedures: segmenting the necrotic lesion and viable proximal femur, meshing the computational models, assigning different material properties according to the Hounsfield unit distribution, simulating the stress loading of the slow walking gait, and measuring the distribution of the von Mises stress. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of the maximum level of the von Mises stress. The optimal cut‐off value was selected based on the Youden index and the corresponding predictive accuracy was reported as well. Results The mean level of the maximum von Mises stress in the collapse group was 2.955 ± 0.539 MPa, whereas the mean stress level in the noncollapse group was 1.923 ± 0.793 MPa (P < 0.01). ROC analysis of the maximum von Mises stress found that the area under the ROC curve was 0.842 (95% CI: 0.717–0.968, P < 0.01). The maximum Youden index was 0.60, which corresponded to two optimal cut‐off values: 2.7801 MPa (sensitivity: 0.70; specificity: 0.90; predictive accuracy: 80.00%; LR+: 7), and 2.7027 MPa (sensitivity: 0.75; specificity: 0.85; predictive accuracy: 77.50%; LR+: 5). Conclusion Finite element analysis is a potential method for femoral head collapse prediction among pre‐collapse ONFH patients. The maximum level of the von Mises stress on the weight‐bearing surface of the femoral head could be a good biomechanical marker to classify the collapse risk. The collapse prediction method based on patient‐specific finite element analysis is, thus, suitable to apply to clinical practice, but further testing on a larger dataset is desirable.
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