Objective To review the research progress of surgical methods of osteotomy around the knee in the treatment of valgus knee osteoarthritis. MethodsThe relevant literature on the surgical treatment of valgus knee osteoarthritis at home and abroad in recent years was reviewed, and the advantages, disadvantages, and effectiveness of different surgical methods of osteotomy around the knee were summarized. Results For young and active patients with symptomatic valgus knee osteoarthritis, osteotomy around the knee is a safe and reliable treatment option. At present, the main surgical methods include medial closing wedge distal femoral osteotomy, lateral opening wedge distal femoral osteotomy, medial closing wedge high tibial osteotomy, and lateral opening wedge high tibial osteotomy. The indications, advantages, and disadvantages of different osteotomies are different, and the selection of appropriate surgical method is the key to achieve good effectiveness. ConclusionThere are many osteotomies in the treatment of valgus knee osteoarthritis. In order to achieve good results, improve survival rate, and reduce postoperative complications, the most reasonable surgical strategy needs to be developed according to different situations.
Aiming at the problem that the feature extraction ability of forehead single-channel electroencephalography (EEG) signals is insufficient, which leads to decreased fatigue detection accuracy, a fatigue feature extraction and classification algorithm based on supervised contrastive learning is proposed. Firstly, the raw signals are filtered by empirical modal decomposition to improve the signal-to-noise ratio. Secondly, considering the limitation of the one-dimensional signal in information expression, overlapping sampling is used to transform the signal into a two-dimensional structure, and simultaneously express the short-term and long-term changes of the signal. The feature extraction network is constructed by depthwise separable convolution to accelerate model operation. Finally, the model is globally optimized by combining the supervised contrastive loss and the mean square error loss. Experiments show that the average accuracy of the algorithm for classifying three fatigue states can reach 75.80%, which is greatly improved compared with other advanced algorithms, and the accuracy and feasibility of fatigue detection by single-channel EEG signals are significantly improved. The results provide strong support for the application of single-channel EEG signals, and also provide a new idea for fatigue detection research.
ObjectiveTo analyze the perioperative safety and the short-term prognosis of non-small cell lung cancer (NSCLC) patients with preoperative arrhythmia. MethodsThe clinical data of NSCLC patients treated in the Department of Cardiothoracic Surgery, the First Affiliated Hospital of Chongqing Medical University from August 2020 to March 2021 were collected and observed. The patients were divided into an arrhythmia group and a control group according to whether there was arrhythmia in the 24 h ambulatory electrocardiogram examination report before operation. The incidence of intraoperative and postoperative cardiovascular events and short-term prognosis were compared between the two groups. Results A total of 466 patients were included in this study, including 338 patients in the arrhythmia group, 176 males and 162 females, with a median age of 68.0 (63.0, 72.0) years, and 128 patients in the control group, 59 males and 69 females, with a median age of 66.5 (60.0, 72.0) years. A total of 26 patients (7.7%) in the arrhythmia group were placed with temporary pacemakers before operation. There was no significant difference in the incidence of cardiovascular related events between the two groups [100 (29.6%) vs. 28 (21.9%), P=0.096]. The incidence of postoperative arrhythmia events in the arrhythmia group was higher than that in the control group [112 (33.1%) vs. 11 (8.6%), P<0.001]. The average postoperative ICU stay in the arrhythmia group was longer than that in the control group (1.1±0.7 d vs. 1.0±0.6 d, P=0.039). ConclusionPreoperative arrhythmia does not increase the risk of intraoperative cardiovascular events in NSCLC patients, but increases the incidence of postoperative arrhythmia events and prolongs ICU stay.
Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, making accurate and objective diagnosis challenging when relying solely on clinical assessments. Therefore, there is an urgent need to develop reliable and objective auxiliary diagnostic models to provide effective diagnosis for PTSD patients. Currently, the application of graph neural networks for representing PTSD is limited by the expressiveness of existing models, which does not yield optimal classification results. To address this, we proposed a multi-graph multi-kernel graph convolutional network (MK-GCN) model for classifying PTSD data. First, we constructed functional connectivity matrices at different scales for the same subjects using different atlases, followed by employing the k-nearest neighbors algorithm to build the graphs. Second, we introduced the MK-GCN methodology to enhance the feature extraction capability of brain structures at different scales for the same subjects. Finally, we classified the extracted features from multiple scales and utilized graph class activation mapping to identify the top 10 brain regions contributing to classification. Experimental results on seismic-induced PTSD data demonstrated that our model achieved an accuracy of 84.75%, a specificity of 84.02%, and an AUC of 85% in the classification task distinguishing between PTSD patients and non-affected subjects. The findings provide robust evidence for the auxiliary diagnosis of PTSD following earthquakes and hold promise for reliably identifying specific brain regions in other PTSD diagnostic contexts, offering valuable references for clinicians.