Anterior cruciate ligament injury should not be considered a contraindication for medial unicompartmental knee arthroplasty: Finite element analysis.

PURPOSE: The research objective of this study is to use finite element analysis to investigate the impact of anterior cruciate ligament (ACL) injury on medial unicompartmental knee arthroplasty (UKA) and explore whether patients with ACL injuries can undergo UKA. METHODS: Based on the morphology of the ACL, models of ACL with diameters ranging from 1 to 10mm are created. Finite element models of UKA include ACL absence and ACLs with different diameters. After creating a complete finite element model and validating it, four different types of loads are applied to the knee joint. Statistical analysis is conducted to assess the stress variations in the knee joint structure. RESULTS: A total of 11 finite element models of UKA were established. Regarding the stress on the ACL, as the diameter of the ACL increased, when a vertical load of 750N was applied to the femur, combined with an anterior tibial load of 105N, the stress on the ACL increased from 2.61 MPa to 4.62 MPa, representing a 77.05% increase. Regarding the equivalent stress on the polyethylene gasket, a notable high stress change was observed. The stress on the gasket remained between 12.68 MPa and 14.33 MPa in all models. the stress on the gasket demonstrated a decreasing trend. The equivalent stress in the lateral meniscus and lateral femoral cartilage decreases, reducing from the maximum stress of 4.71 MPa to 2.61 MPa, with a mean value of 3.73 MPa. This represents a reduction of 44.72%, and the statistical significance is (P < 0.05). However, under the other three loads, there was no significant statistical significance (P > 0.05). CONCLUSION: This study suggests that the integrity of the ACL plays a protective role in performing medial UKA. However, this protective effect is limited when performing medial UKA. When the knee joint only has varying degrees of ACL injury, even ACL rupture, and the remaining structures of the knee joint are intact with anterior-posterior stability in the knee joint, it should not be considered a contraindication for medial UKA.

Age and flexors as risk factors for cervical radiculopathy: A new machine learning method.

This study aimed to investigate the risk factors for cervical radiculopathy (CR) along with identifying the relationships between age, cervical flexors, and CR. This was a retrospective cohort study, including 60 patients with CR enrolled between December 2018 and June 2020. In this study, we measured C2 to C7 Cobb angle, disc degeneration, endplate degeneration, and morphology of paraspinal muscles and evaluated the value of predictive methods using receiver operating characteristic curves. Next, we established a diagnostic model for CR using Fisher discriminant model and compared different models by calculating the kappa value. Age and cervical flexor factors were used to construct clinical predictive models, which were further evaluated by C-index, receiver operating characteristic curve, calibration curve, and decision curve analysis. Multivariate analysis showed that age and cervical flexors were potential risk factors for CR, while the diagnostic model indicated that both exerted the best diagnostic effect. The obtained diagnostic equation was as follows: y1 = 0.33 × 1 + 10.302 × 2-24.139; y2 = 0.259 × 1 + 13.605 × 2-32.579. Both the C-index and AUC in the training set reached 0.939. Moreover, the C-index and AUC values in the external validation set reached 0.961. We developed 2 models for predicting CR and also confirmed their validity. Age and cervical flexors were considered potential risk factors for CR. Our noninvasive inspection method could provide clinicians with a more potential diagnostic value to detect CR accurately.

Comparison of Endoscopic and Minimally Invasive Transforaminal Lumbar Interbody Fusion for Lumbar Degenerative Diseases: A Meta-analysis.

STUDY DESIGN: Systematic review and meta-analysis. OBJECTIVE: To compare the results of endoscopic transforaminal lumbar interbody fusion (Endo-TLIF) and minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) for patients with lumbar degenerative diseases. SUMMARY OF BACKGROUND DATA: The MIS-TLIF has been widely used in lumbar degenerative diseases and achieved favorable clinical effects. The main disadvantage is the limited working space and visualization, especially in the deeper operational field, for preparing fusion bed. In recent years, with the development of surgical techniques, optical technology, and special instruments, Endo-TLIF has gradually been applied. MATERIALS AND METHODS: A systematic review and meta-analysis of cohort studies between Endo-TLIF and MIS-TLIF in the lumbar degenerative diseases. The following outcome measures were extracted: visual analog scale (VAS), Oswestry Disability Index, fusion rate, disk height, segmental lordosis, operative time, length of hospital stay and complications. Data analysis was performed by RevMan 5.3. RESULTS: Eight studies comprising 687 patients were included in this meta-analysis. The pooled result revealed there was no significant differences in the VAS of leg, Oswestry Disability Index, fusion rate, disk height, segmental lordosis, and complication rate between the 2 groups ( P >0.05). However, the VAS of back in the Endo-TLIF group was significantly less than those in the MIS-TLIF group within 2 weeks after surgery [weighted mean difference (WMD)=-1.33 (-1.98, -0.68), P <0.0001] and at 3 months postoperatively [WMD=-0.72(-0.85, -0.59), P <0.00001]. The Endo-TLIF group also seemed to fewer VAS of back at the last follow-up (≥12 mo) [WMD=-0.12 (-0.25, -0.00), P =0.05]. Compared with the MIS-TLIF group, the Endo-TLIF group was associated with longer operation time [WMD=26.74 (2.14, 51.34), P =0.03], but shorter length of hospital stay [WMD=-1.98(-2.91, -1.05), P <0.0001]. CONCLUSIONS: Compared with minimally invasive TLIF, endoscopic TLIF achieved comparable improvement of symptoms and intervertebral fusion, longer operation time, and smaller surgical trauma. Endoscopic TLIF, which requires a demanding learning curve, maybe a feasible and effective technique for the patients with symptomatic lumbar degenerative diseases.

Exploring the causal relationship between inflammatory cytokines and inflammatory arthritis: A Mendelian randomization study.

OBJECTIVES: Previous studies have reported an association between inflammatory cytokines and inflammatory arthritis, including Ankylosing spondylitis (AS), rheumatoid arthritis (RA), and psoriatic arthritis (PsA). This study aims to explore the causal relationship between inflammatory cytokines and AS, RA, and PsA using Mendelian randomization (MR). METHODS: We conducted a bidirectional two-sample MR analysis using genetic summary data from a publicly available genome-wide association study (GWAS) that included 41 genetic variations of inflammatory cytokines, as well as genetic variant data for AS, RA, and PsA from the FinnGen consortium. The main analysis method used was Inverse variance weighted (IVW) to investigate the causal relationship between exposure and outcome. Additionally, other methods such as MR Egger, weighted median (WM), simple mode, and weighted mode were employed to strengthen the final results. Sensitivity analysis was also performed to ensure the reliability of the findings. RESULTS: The results showed that macrophage colony-stimulating factor (MCSF) was associated with an increased risk of AS (OR = 1.163, 95 % CI = 1.016-1.33, p = 0.028). Conversely, high levels of TRAIL and beta nerve growth factor (ß-NGF) were associated with a decreased risk of AS (OR = 0.892, 95 % CI = 0.81-0.982, p = 0.002; OR = 0.829, 95 % CI = 0.696-0.988, p = 0.036). Four inflammatory cytokines were found to be associated with an increased risk of PsA: vascular endothelial growth factor (VEGF) (OR = 1.161, 95 % CI = 1.057-1.275, p = 0.002); Interleukin 12p70 (IL12p70) (OR = 1.189, 95 % CI = 1.049-1.346, p = 0.007); IL10 (OR = 1.216, 95 % CI = 1.024-1.444, p = 0.026); IL13 (OR = 1.159, 95 % CI = 1.05-1.28, p = 0.004). Interleukin 1 receptor antagonist (IL-1rα) was associated with an increased risk of seropositive RA (OR = 1.181, 95 % CI = 1.044-1.336, p = 0.008). Similarly, genetic susceptibility to inflammatory arthritis was found to be causally associated with multiple inflammatory cytokines. Lastly, the sensitivity analysis supported the robustness of these findings. CONCLUSIONS: This study provides additional insights into the relationship between inflammatory cytokines and inflammatory arthritis, and may offer new clues for the etiology, diagnosis, and treatment of inflammatory arthritis.

Comprehensive AI-assisted tool for ankylosing spondylitis based on multicenter research outperforms human experts.

Introduction: The diagnosis and treatment of ankylosing spondylitis (AS) is a difficult task, especially in less developed countries without access to experts. To address this issue, a comprehensive artificial intelligence (AI) tool was created to help diagnose and predict the course of AS. Methods: In this retrospective study, a dataset of 5389 pelvic radiographs (PXRs) from patients treated at a single medical center between March 2014 and April 2022 was used to create an ensemble deep learning (DL) model for diagnosing AS. The model was then tested on an additional 583 images from three other medical centers, and its performance was evaluated using the area under the receiver operating characteristic curve analysis, accuracy, precision, recall, and F1 scores. Furthermore, clinical prediction models for identifying high-risk patients and triaging patients were developed and validated using clinical data from 356 patients. Results: The ensemble DL model demonstrated impressive performance in a multicenter external test set, with precision, recall, and area under the receiver operating characteristic curve values of 0.90, 0.89, and 0.96, respectively. This performance surpassed that of human experts, and the model also significantly improved the experts' diagnostic accuracy. Furthermore, the model's diagnosis results based on smartphone-captured images were comparable to those of human experts. Additionally, a clinical prediction model was established that accurately categorizes patients with AS into high-and low-risk groups with distinct clinical trajectories. This provides a strong foundation for individualized care. Discussion: In this study, an exceptionally comprehensive AI tool was developed for the diagnosis and management of AS in complex clinical scenarios, especially in underdeveloped or rural areas that lack access to experts. This tool is highly beneficial in providing an efficient and effective system of diagnosis and management.

Risk Factors in the Prediction of Leg Numbness after Spinal Endoscopic Surgery: Evaluation and Development of a Nomogram.

Purpose: This study aims at constructing a clinical predictive model that predicted the risk factors for leg numbness after spinal endoscopic surgery. Methods: We collected the clinical data of patients, including general information, imaging parameters, and clinical score, from our hospital's electronic database. Based on the postoperative leg numbness visual analog scale (LN-VAS), the clinical data were divided into the leg numbness group (≥25) and the improvement group (<25). All parameters were included in the least absolute shrinkage and selection operator (LASSO) regression analysis, while the parameters with the area under the curve (AUC) greater than 0.7 were selected to construct nomograms. Furthermore, the accuracy and validity of the model were evaluated using the C-index, decision curve analysis (DCA), calibration curve, and receiver operating characteristic curve (ROC). Results: A total of 73 patients' clinical data were included in the training set, where 51 patients were assigned to the improvement group and 22 to the leg numbness group. The nomogram was constructed using four selected parameters, including symptom duration, lumbar spinal stenosis (LSS), pelvic incidence (PI), and preoperative low back pain visual analog scale (LBP-VAS). The nomogram predictions were found to range between 0.01 and 0.99. The values of the C-index, AUC, and internally validated C-index were 0.96, 0.96, and 0.94, respectively. Our result showed that the clinical net benefit of the nomogram ranged between 0.01 and 0.99. Conclusion: Our clinical prediction model demonstrated high predictive ability and clinical validity. Moreover, we found that symptom duration, LSS, PI, and preoperative LBP-VAS were the predictive risk factors for leg numbness after spinal endoscopic surgery.

A seven-gene signature and the C-C motif chemokine receptor family genes are the sarcoma-related immune genes.

Cells of the tumor microenvironment exert a vital influence on sarcoma prognosis. This study aimed to analyze and identify differentially expressed genes (DEGs) related to immunity and their significance as immune biomarkers for the accurate prediction of overall survival of patients with sarcoma. The Cancer Genome Atlas was adopted for obtaining sarcoma gene microarray and corresponding clinical information. ESTIMATE algorithm was used to calculate tumor immune microenvironment indices. Immune-associated DEGs were identified using the limma packages and were further analyzed using the ClusterProfiler package and STRING website. Based on the results of these analyses, we constructed a prognostic model. Furthermore, we assessed the prognosis prediction model through functional evaluation and analysis of GSE17674. The functional analysis revealed that the upregulated immune DEGs were related to immune-related aspects. Chemokine ligands/receptors and immune-related genes were found to be vital for sarcoma formation and progression. We established a prognostic signature of seven genes, which indicated that high-risk cases exhibit poor prognostic outcome. The prognostic signature constructed in this study can accurately predict the overall prognosis in patients with sarcoma. Moreover, the novel immune gene expression analysis may provide clinical guidance for predicting prognosis in patients with sarcoma.

A modified rotating isosceles triangle osteotomy using a 3D-printed patient-specific guide for the treatment of cubitus varus in children: a case report and literature review.

After corrective osteotomy of cubitus varus, the lateral condylar prominence is a common problem, which is believed to be due to the unequal relative cuts of the lateral base wedge osteotomy. Therefore, several related solutions have been proposed, such as dome osteotomy and step-cut osteotomies, which solve the above problems to a certain extent. This study aimed to: (I) use a modified corpectomy to correct the deformity, and (II) present a new corpectomy method that uses a 3D-printed specific guide with an isosceles triangle osteotomy. A 12-year-old male presented with a -30-degree cubitus varus deformity 5 years after a supracondylar fracture of the right humerus. The degree of correction was determined from the varus angle and the normal carrying angle on the normal side. A rotating isosceles triangle osteotomy was determined by using Mimics software. The accuracy of the osteotomy angle was confirmed by postoperative radiography. The mean postoperative carrying angle was found to be preserved at the 10-month follow-up, with no complications. A rotating isosceles triangle osteotomy with a 3D-printed patient-specific guide may be providing a relative accurate result. However, in order to obtain more rigorous research conclusions, more cases should be added to examine this methodology for bone deformity surgery in the near future.