Objective To develop a Matlab toolbox to improve the efficiency of musculoskeletal kinematics analysis while ensuring the consistency of musculoskeletal kinematics analysis process and results. Methods Adopted the design concept of “Batch processing tedious operation”, based on the Matlab connection OpenSim interface function ensures the consistency of musculoskeletal kinematics analysis process and results, the functional programming was applied to package the five steps for scale, inverse kinematics analysis, residual reduction algorithm, static optimization analysis, and joint reaction analysis of musculoskeletal kinematics analysis as functional functions, and command programming was applied to analyze musculoskeletal movements in large numbers of patients. A toolbox called LLMKA (Lower Limbs Musculoskeletal Kinematics Analysis) was developed. Taking 120 patients with medial knee osteoarthritis as the research object, a clinical researcher was selected using the LLMKA toolbox and OpenSim to test whether the analysis process and results were consistent between the two methods. The researcher used the LLMKA toolbox again to conduct musculoskeletal kinematics analysis in 120 patients to verify whether the use of this toolbox could improve the efficiency of musculoskeletal kinematics analysis compared with using OpenSim. Results Using the LLMKA toolbox could analyze musculoskeletal kinematics analysis in a large number of patients, and the analysis process and results were consistent with the use of OpenSim. Compared to using OpenSim, musculoskeletal kinematics analysis was completed in 120 patients using the LLMKA toolbox with only 2 operations were needed to enter the patient body mass data, operating steps decreased by 99.19%, total analysis time by 66.84%, and manual participation time by 99.72%, just need 0.079 1 hour (4 minutes and 45 seconds). Conclusion The LLMKA toolbox can complete a large number of musculoskeletal kinematics analysis in patients with one click in a way that is consistent in process and results with using OpenSim, reducing the total time of musculoskeletal kinematics analysis, and liberating clinical researchers from cumbersome steps, making more energy into the clinical significance of musculoskeletal kinematics analysis results.
The aim of this paper is to reveal the change of the brain function for nicotine addicts after smoking cessation, and explore the basis of neural physiology for the nicotine addicts in the process of smoking cessation. Fourteen subjects, who have a strong dependence on nicotine, have agreed to give up smoking and insist on completing the test, and 11 volunteers were recruited as the controls. The resting state functional magnetic resonance imaging and the regional homogeneity (ReHo) algorithm have been used to study the neural activity before and after smoking cessation. A two factors mixed design was used to investigate within-group effects and between-group effects. After 2 weeks’ smoking cessation, the increased ReHo value were exhibited in the brain area of supplementary motor area, paracentral lobule, calcarine, cuneus and lingual gyrus. It suggested that the synchronization of neural activity was enhanced in these brain areas. And between-group interaction effects were appeared in supplementary motor area, paracentral lobule, precentral gyrus, postcentral gyrus, and superior frontal gyrus. The results indicate that the brain function in supplementary motor area of smoking addicts would be enhanced significantly after 2 weeks’ smoking cessation.
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.
ObjectiveTo introduce sensitivity and homogeneity tests in network meta-analysis and its implementation in R software. MethodsUsing an example, we performed sensitivity analysis by comparing the random effect model with the fixed effect model. Homogeneity analysis was performed using metaphor package and combinat package in R software. ResultsThe results of the two models were similar, and the data was steady. The results of homogeneity analysis showed that the confidential intervals in all loops were crossed over with blank value; and direct and indirect estimates of the effects in network meta-analysis were not significantly different, with good homogeneity. ConclusionNetwork meta-analysis is a kind of indirect comparison analysis method, and its sensitivity is especially important. The introduction of homogeneity makes network meta-analysis more accurate. Using R software for sensitivity and homogeneity analysis in network meta-analysis is a feasible method.
This study sought to reveal the difference of brain functions at resting-state between subjects with sub-health and normal controls by using the functional magnetic resonance imaging (fMRI) technology. Resting-state fMRI scans were performed on 24 subjects of sub-health and on 24 healthy controls with gender, age and education matched with the sub-health persons. Compared to the healthy controls, the sub-health group showed significantly higher regional homogeneity (ReHo) in the left post-central gyrus and the right post-central gyrus. On the other hand, the sub-health group showed significantly lower ReHo in the left superior frontal gyrus, in the right anterior cingulated cortex and ventra anterior cingulate gyrus, in the left dorsolateral frontal gyrus, and in the right middle temporal gyrus. The Significant difference in ReHo suggests that thebsub-health persons have abnormalities in certain brain regions. It is proved that its specific action and meaning deserves further assessment.
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.
Objectives To evaluate the reporting quality of Bland-Altman method consistency evaluation in China from 2014 to 2016. Methods WanFang Data, VIP and CNKI databases were electronically searched to collect literature about the application of Bland-Altman method from 2014 to 2016 in China. Two reviewers screened literature, extracted data, and the data were then statistically analyzed by SPSS 22.0 software. Results A total of 376 articles were included. The published articles on Bland-Altman method had major flaws (not conforming to reporting standards) in the application conditions, evaluation indexes, graphic depiction and so on. Merely 11.4% of the literature set the clinically acceptable consensus values in the pre-period studies. Merely one literature (0.3%) correctly compared the 95%CI of 95%LoA with the clinically acceptable threshold which had been set previously. The offer rates of the differences between the two measurements and the 95%CI, 95%LoA and 95%CI of 95%LoA in the figure were 95.9%, 9.5%, 94.6% and 4.4%, respectively. Conclusions The reporting quality of Bland-Altman method consistency evaluation in China is of low quality, specifically not conforming to reporting standards. We should strengthen the introduction of Bland-Altman methodology to improve the reporting quality.
Objective To investigate an evaluation method of medical literature applicability to clinical work， and provide a convenient way for physicians to search for the best evidence. Methods Delphi method was used to choose appropriate evaluating indexes， analytic hierarchy process was performed to determine the weighing of each index， and the formula to calculate medical literature applicability was formed. The practicability of this formula was evaluated by consistency checking between the formula’s results and experts’ opinions on literature applicability. Results Five evaluating indexes were determined， including literature’s publishing year （X1）， whether the target questions were covered （X2）, sample size （X3）， trial category （X4）， and journal level （X5）. The formula to calculate medical literature applicability was Y=3.93 X1＋11.78 X2＋14.83 X3＋44.53 X4＋24.93 X5. The result of consistency checking showed that the formula’s results were highly consistent with experts’ opinions （Kappa=0.75， P＜0.001）. Conclusion The applicability formula is a valuable tool to evaluate medical literature applicability.
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.
本文针对二分类变量结局指标相对（而非绝对）治疗效果的不一致性。证据本身不会因不同研究结果具有一致性而升级，但可能因不一致而降低质量级别。衡量一致性的标准包括点估计值的相似性、可信区间的重叠程度以及统计学判定标准包括异质性检验和I2。系统评价作者应提出并检验少数几个与患者、干预措施、结局指标以及方法学相关的先验假设以探寻异质性来源。当不一致性很大且无法解释时，因不一致性而降低质量级别是恰当的，特别当某些研究显示有显著益处而其他显示无益甚至有害时（而非仅是疗效大与疗效小的比较）。明显的亚组效应可能不可靠。如果亚组效应满足以下条件，其可信度将会增加：基于少数几个有具体方向的先验假设、亚组比较来自研究内而非研究间、交互检验的P值小、结果有生物学意义。