ObjectivesTo analyze the application value of 6-minute walking test (6MWT) in the clinical evaluation of chronic heart failure (CHF).MethodsPubMed, EMbase, The Cochrane Library, CBM, VIP, WanFang Data and CNKI databases were searched online to collect randomized controlled trials (RCTs) of 6-minute walking distance (6MWD) as the CHF evaluation index. Two reviewers independently screened literature, extracted data, and then analyzed data by using SPSS 17.0 statistical software. The 6MWD with symptom, quality of life, exercise tolerance (ETT), left ventricular ejection fraction (LVEF), peak oxygen consumption (pVO2) were analyzed by Kappa consistency test, and the possible influencing factors of 6MWD were analyzed by logistic regression.ResultsA total of 158 RCTs involving 17 853 patients were included. The results of statistical analysis showed that: 6MWD was consistent with the improvement of symptoms, quality of life, ETT, LVEF and pVO2 (Kappa>0.4). Baseline 6MWD (OR=2.91, 95%CI 1.278 to 6.634,P=0.011) and NYHA Ⅲ-Ⅳ ratio (OR=2.59, 95%CI 1.091 to 6.138, P=0.031) were the independent influencing factors for 6MWD improvement separately.ConclusionsThe 6MWT is an objective and reliable indicator of CHF evaluation.
Lung cancer is the most threatening tumor disease to human health. Early detection is crucial to improve the survival rate and recovery rate of lung cancer patients. Existing methods use the two-dimensional multi-view framework to learn lung nodules features and simply integrate multi-view features to achieve the classification of benign and malignant lung nodules. However, these methods suffer from the problems of not capturing the spatial features effectively and ignoring the variability of multi-views. Therefore, this paper proposes a three-dimensional (3D) multi-view convolutional neural network (MVCNN) framework. To further solve the problem of different views in the multi-view model, a 3D multi-view squeeze-and-excitation convolution neural network (MVSECNN) model is constructed by introducing the squeeze-and-excitation (SE) module in the feature fusion stage. Finally, statistical methods are used to analyze model predictions and doctor annotations. In the independent test set, the classification accuracy and sensitivity of the model were 96.04% and 98.59% respectively, which were higher than other state-of-the-art methods. The consistency score between the predictions of the model and the pathological diagnosis results was 0.948, which is significantly higher than that between the doctor annotations and the pathological diagnosis results. The methods presented in this paper can effectively learn the spatial heterogeneity of lung nodules and solve the problem of multi-view differences. At the same time, the classification of benign and malignant lung nodules can be achieved, which is of great significance for assisting doctors in clinical diagnosis.
For the questions of deeply researching abnormal neuromuscular coupling and better evaluating motor function of stroke patients with motor dysfunction, an effective intermuscular coherence analysis method and index are studied to explore the neuromuscular oscillation and the pathomechanism of motor dysfunction, based on which an assessment standard of muscle function is established. Firstly, the contrastive analysis about the intermuscular coherence of antagonistic muscle of affected and intact upper limbs of stroke patients was conducted. Secondly, a significant indicator of Fisher's Z-transformed coherence significant indicator was defined to quantitatively describe the coupling differences in certain functional frequency domain between surface electromyogram (sEMG) of affected and intact sides. Further more, the relationship between intermuscular coherence and motor task was studied. Through the analysis of intermuscular coherence during elbow flexion-extension of affected and intact sides, we found that the intermuscular coherence was associated with motor task and the stroke patients exhibited significantly lower beta-band intermuscular coherence in performing the task with their affected upper limbs. More conclusion can be drawn that beta-band intermuscular coherence has been found concerned with Fugle-Meyer scale, which indicates that beta-band intermuscular coherence could be an index assisting in evaluating motor function of patients.
The gait acquisition system can be used for gait analysis. The traditional wearable gait acquisition system will lead to large errors in gait parameters due to different wearing positions of sensors. The gait acquisition system based on marker method is expensive and needs to be used by combining with the force measurement system under the guidance of rehabilitation doctors. Due to the complex operation, it is inconvenient for clinical application. In this paper, a gait signal acquisition system that combines foot pressure detection and Azure Kinect system is designed. Fifteen subjects are organized to participate in gait test, and relevant data are collected. The calculation method of gait spatiotemporal parameters and joint angle parameters is proposed, and the consistency analysis and error analysis of the gait parameters of proposed system and camera marking method are carried out. The results show that the parameters obtained by the two systems have good consistency (Pearson correlation coefficient r ≥ 0.9, P < 0.05) and have small error (root mean square error of gait parameters is less than 0.1, root mean square error of joint angle parameters is less than 6). In conclusion, the gait acquisition system and its parameter extraction method proposed in this paper can provide reliable data acquisition results as a theoretical basis for gait feature analysis in clinical medicine.
ObjectiveTo observe the interobserver agreement of classification of macular degeneration in severe pathological myopia (PM) by ophthalmologists with different clinical experience. MethodsA retrospective study. From January 2019 to December 2021, 171 eyes of 102 patients with severe PM macular degeneration who were examined at Eye Center of Beijing Tongren Hospital of Capital Medical University were included in the study. The clinical data such as age, gender, axial length, spherical equivalent power, fundus color photography, and optical coherence tomography (OCT) were collected in detail. Six independent ophthalmologists (A, B, C, D, E, F) classified each fundus photography based on META-PM and ATN classification of atrophy (A) system and interobserver agreement was assessed by Kappa statistics. According to the classification standard of traction (T) in the ATN classification, the OCT images were interpreted and classified, in which T0 was subdivided into retinal pigment epithelium (RPE) and choroidal thinning, choroidal neovascularization (CNV) with partial RPE and choroidal atrophy, RPE, and choroidal atrophy. Lamellar macular hole can't be classified by ATN system, which was defined as TX. Kappa (κ) test was used to analyze the consistency of classification results between physicians A, B, C, D, E and F. κ value ≤0.4 indicates low consistency, 0.4＜κ value ≤ 0.6 indicates moderate consistency, and κ value ＞0.6 indicates strong consistency. ResultsAmong the 171 eyes of 102 cases, there were 20 males with 37 eyes (19.6%, 20/102), and 82 females with 134 eyes (80.4%, 82/102); age was 61.97±8.78 years; axial length was (30.87±1.93) mm; equivalent spherical power was (－16.56±7.00) D. Atrophy (A) classification results in META-PM classification and ATN classification, the consistency of physician A, B, C, D, E and physician F were 73.01%, 77.19%, 81.28%, 81.28%, 88.89%; κ value were 0.472, 0.538, 0.608, 0.610, 0.753, respectively. In the ATN classification, the T0, T1, T2, T3, T4, and T5 were in 109, 18, 11, 12, 9, and 8 eyes, respectively; TX was in 4 eyes. ConclusionsThere are differences in the consistency of classification of severe PM macular lesions among physicians with different clinical experience, and the consistency will gradually improve with the accumulation of clinical experience.
A great number of studies have demonstrated functional abnormalities in children with attention-deficit/hyperactivity disorder (ADHD), although conflicting results have also been reported. And few studies analyzed homotopic functional connectivity between hemispheres. In this study, resting-state functional magnetic resonance imaging (MRI) data were recorded from 45 medication-na?ve ADHD children and 26 healthy controls. The regional homogeneity (ReHo), degree centrality (DC) and voxel-mirrored homotopic connectivity (VMHC) values were compared between the two groups to depict the intrinsic brain activities. We found that ADHD children exhibited significantly lower ReHo and DC values in the right middle frontal gyrus and the two values correlated with each other; moreover, lower VMHC values were found in the bilateral occipital lobes of ADHD children, which was negatively related with anxiety scores of Conners' Parent Rating Scale (CPRS-R) and positively related with completed categories of Wisconsin Card Sorting Test (WCST). Our results might suggest that less spontaneous neuronal activities of the right middle frontal gyrus and the bilateral occipital lobes in ADHD children.
Objective To compare the inter-observer agreement, consistency with the gold standard, and accuracy of the 2007 and 2018 versions of the AO/OTA classification in femoral intertrochanteric fractures, and to identify easily confused fracture types. Methods X-ray images of patients with femoral intertrochanteric fractures at Daping Hospital, Army Medical University between 2017 and 2021 were retrospectively collected. Three senior orthopedic trauma surgeons independently classified the fractures using both the 2007 and 2018 AO/OTA versions. A committee of five experts established the gold standard. Kappa coefficients were used to evaluate inter-observer agreement and consistency with the gold standard, while a confusion matrix was used to analyze accuracy and confusion points. Results A total of 236 patients were included. Regarding inter-observer agreement, the 2007 version was superior to the 2018 version at the subtype level [Kappa value: (0.473-0.739) vs. (0.322-0.658)], with no significant difference at the subgroup level [Kappa value: (0.234-0.453) vs. (0.204-0.442)]. Regarding consistency with the gold standard, the 2018 version was slightly better than the 2007 version [Kappa value: (0.332-0.629) vs. (0.269-0.581)] at the subgroup level. In terms of accuracy, the 2007 version showed higher accuracy at the subtype level (72.50% vs. 70.11%), whereas the 2018 version demonstrated better accuracy at the subgroup level (59.04% vs. 51.99%). The most easily confused subtypes in both versions were A1 and A2. At the subgroup level, A2.2 was the most easily confused type in both versions. Conclusions There is inconsistency in the application of both classification versions by surgeons. The 2007 version demonstrates slightly better inter-observer agreement at the subtype level, while the 2018 version shows better accuracy at the subgroup level. The A2.2 subgroup is a major point of confusion, suggesting that clinical attention should be focused on this type or that auxiliary tools may be needed to improve accuracy.
