Types of publication bias and its background are introduced in this paper, and publication bias can be investigated and deal with three methods: funnel plot, trim and filling method, and formula method. Those methods can be used to detect publication bias in conducting systematic reviews.
Subpopulation treatment effect pattern plot (STEPP) method is a method for examining the relationship between treatment effects and continuous covariates and is characterized by dividing the study population into multiple overlapping subpopulations to be analyzed based on continuous covariate values. STEPP method has a different purpose than traditional subgroup analyses, and STEPP has a clear advantage in exploring the relationship between treatment effects and continuous covariates. In this study, the concepts, advantages, and subpopulation delineation methods of the STEPP method are introduced, and the specific operation process and result interpretation methods of STEPP method analysis using the STEPP package in R language are presented with examples.
Calculation of linear parameters, such as time-domain and frequency-domain analysis of heart rate variability (HRV), is a conventional method for assessment of autonomic nervous system activity. Nonlinear phenomena are certainly involved in the genesis of HRV. In a seemingly random signal the Poincaré plot can easily demonstrate whether there is an underlying determinism in the signal. Linear and nonlinear analysis methods were applied in the computer words inputting experiments in this study for physiological measurement. This study therefore demonstrated that Poincaré plot was a simple but powerful graphical tool to describe the dynamics of a system.
Predicting the termination of paroxysmal atrial fibrillation (AF) may provide a signal to decide whether there is a need to intervene the AF timely. We proposed a novel RdR RR intervals scatter plot in our study. The abscissa of the RdR scatter plot was set to RR intervals and the ordinate was set as the difference between successive RR intervals. The RdR scatter plot includes information of RR intervals and difference between successive RR intervals, which captures more heart rate variability (HRV) information. By RdR scatter plot analysis of one minute RR intervals for 50 segments with non-terminating AF and immediately terminating AF, it was found that the points in RdR scatter plot of non-terminating AF were more decentralized than the ones of immediately terminating AF. By dividing the RdR scatter plot into uniform grids and counting the number of non-empty grids, non-terminating AF and immediately terminating AF segments were differentiated. By utilizing 49 RR intervals, for 20 segments of learning set, 17 segments were correctly detected, and for 30 segments of test set, 20 segments were detected. While utilizing 66 RR intervals, for 18 segments of learning set, 16 segments were correctly detected, and for 28 segments of test set, 20 segments were detected. The results demonstrated that during the last one minute before the termination of paroxysmal AF, the variance of the RR intervals and the difference of the neighboring two RR intervals became smaller. The termination of paroxysmal AF could be successfully predicted by utilizing the RdR scatter plot, while the predicting accuracy should be further improved.
Extraction and analysis of electroencephalogram (EEG) signal characteristics of patients with autism spectrum disorder (ASD) is of great significance for the diagnosis and treatment of the disease. Based on recurrence quantitative analysis (RQA)method, this study explored the differences in the nonlinear characteristics of EEG signals between ASD children and children with typical development (TD). In the experiment, RQA method was used to extract nonlinear features such as recurrence rate (RR), determinism (DET) and length of average diagonal line (LADL) of EEG signals in different brain regions of subjects, and support vector machine was combined to classify children with ASD and TD. The research results show that for the whole brain area (including parietal lobe, frontal lobe, occipital lobe and temporal lobe), when the three feature combinations of RR, DET and LADL are selected, the maximum classification accuracy rate is 84%, the sensitivity is 76%, the specificity is 92%, and the corresponding area under the curve (AUC) value is 0.875. For parietal lobe and frontal lobe (including parietal lobe, frontal lobe), when the three features of RR, DET and LADL are combined, the maximum classification accuracy rate is 82%, the sensitivity is 72%, and the specificity is 92%, which corresponds to an AUC value of 0.781. The research in this paper shows that the nonlinear characteristics of EEG signals extracted based on RQA method can become an objective indicator to distinguish children with ASD and TD, and combined with machine learning methods, the method can provide auxiliary evaluation indicators for clinical diagnosis. At the same time, the difference in the nonlinear characteristics of EEG signals between ASD children and TD children is statistically significant in the parietal-frontal lobe. This study analyzes the clinical characteristics of children with ASD based on the functions of the brain regions, and provides help for future diagnosis and treatment.
ObjectiveTo investigate the association between tumor necrosis factor (TNF)-α gene polymorphism and susceptibility to chronic obstructive pulmonary disease (COPD) in eastern Heilongjiang province.MethodsA total of 347 COPD patients in the Department of Respiratory Medicine, the First Affiliated Hospital of Jiamusi University, were enrolled from January 2016 to January 2017. In the same period, 338 healthy subjects in the hospital physical examination center were selected as controls. The genotype of the two groups was analyzed by high resolution melting (HRM) and gene sequencing. The genotype and allele probability of the two groups were compared and analyzed by the SHEsis genetic imbalance haplotype analysis.ResultsBoth TNF-a –308 G/A co-dominant model and recessive model have significant differences between COPD patients and healthy subjects (P=0.036, OR 1.512, 95%CI 1.023 – 2.234; P=0.027, OR 1.202, 95%CI 1.024 – 1.741). –850G/A co-dominant model (P=0.000, OR 1.781, 95%CI 1.363 – 2.329), dominant model (P=0.000, OR 0.391 7, 95%CI 1.363 – 2.329) and hyper-dominant model (P=0.000, OR 2.680, 95%CI 1.728 – 4.156) in the two groups were statistically different. The haploid analysis and haploid genotype analysis showed statistically significant differences (all P<0.05, OR>1, 95%CI>1) at +489, –308, –850 sites by allele A, G, A, respectively between the two groups. There was a significant difference in the lung function between the –308G/A, –863C/A mutant genome and the wild type (P=0.038, P=0.02) in COPD patients according to the classification of lung function.ConclusionsA allele in TNF-α –308 and G allele in TNF-α –850 locus may be risk factors for COPD in the eastern Heilongjiang Province, and the risk of homozygous genotype is higher. +489A, –308G and –850A respectively may be the predisposing factor of COPD while the three genotypes of AGA patients were at higher risk. TNF-α –308 A allele and –863 A allele are related to lung function deterioration, and the two sites with A allele in patients with COPD indicate poor lung function.
Deep brain stimulation (DBS), which usually utilizes high frequency stimulation (HFS) of electrical pulses, is effective for treating many brain disorders in clinic. Studying the dynamic response of downstream neurons to HFS and its time relationship with stimulus pulses can reveal important mechanisms of DBS and advance the development of new stimulation modes (e.g., closed-loop DBS). To exhibit the dynamic neuronal firing and its relationship with stimuli, we designed a two-dimensional raster plot to visualize neuronal activity during HFS (especially in the initial stage of HFS). Additionally, the influence of plot resolution on the visualization effect was investigated. The method was then validated by investigating the neuronal responses to the axonal HFS in the hippocampal CA1 region of rats. Results show that the new design of raster plot is able to illustrate the dynamics of indexes (such as phase-locked relationship and latency) of single unit activity (i.e., spikes) during periodic pulse stimulations. Furthermore, the plots can intuitively show changes of neuronal firing from the baseline before stimulation to the onset dynamics during stimulation, as well as other information including the silent period of spikes immediately following the end of HFS. In addition, by adjusting resolution, the raster plot can be adapted to a large range of firing rates for clear illustration of neuronal activity. The new raster plot can illustrate more information with a clearer image than a regular raster plot, and thereby provides a useful tool for studying neuronal behaviors during high-frequency stimulations in brain.
ObjectiveTo explore the application of enhanced funnel plots (EFP) and trial sequential analysis (TSA) in robustness assessment of meta-analysis results.MethodsData were extracted from published meta-analysis. The EFP was used to evaluate the robustness of the significance and heterogeneity of the current meta-analysis. The TSA was used to judge the sufficiency of the cumulative sample size of the current meta-analysis and to assess the robustness of conclusions based on current evidence.ResultsThe EFP showed that the meta-analysis results of low-density lipoprotein (LDL) was robust, and the meta-analysis results of triglyceride (TG), total cholesterol (TC) and high-density lipoprotein (HDL) were not stable. The TSA showed that the cumulative sample size of LDL had reached the required information size (RIS), and the current conclusion was stable. The cumulative Z value of TG, TC and HDL neither reached the RIS nor passed through the TSA monitoring boundary or futility boundary, indicating that current conclusions were not robust.ConclusionsThe combination of EFP and TSA can make a comprehensive judgment on the robustness of current meta-analysis results, and provide methodological support in the robustness assessment of results for future systematic reviews and meta-analyses.
With the rapidly growing literature across the surgical disciplines, there is a corresponding need to critically appraise and summarize the currently available evidence so they can be applied appropriately to patient care. The interpretation of systematic reviews is particularly challenging in cases where few robust clinical trials have been performed to address a particular question. However, risk of bias can be minimized and potentially useful conclusions can be drawn if strict review methodology is adhered to, including an exhaustive literature search, quality appraisal of primary studies, appropriate statistical methodology, assessment of confidence in estimates and risk of bias. Therefore, the following article aims to: (Ⅰ) summarize to the important features of a thorough and rigorous systematic review or meta-analysis for the surgical literature; (Ⅱ) highlight several underused statistical approaches which may yield further interesting insights compared to conventional pair-wise data synthesis techniques; and (Ⅲ) propose a guide for thorough analysis and presentation of results.
ObjectiveTo review recent literature on three-dimensional (3-D) plotting as a rapid prototyping method for the manufacturing of patient specific biomaterial scaffolds and tissue engineering constructs. MethodsLiterature review and description of own recent work. ResultsIn contrast to many other rapid prototyping technologies which can be used only for the processing of distinct materials, 3-D plotting can be utilized for all pasty biomaterials and therefore opens up many new options for the manufacturing of bi- or multiphasic scaffolds or even tissue engineering constructs, containing e. g. living cells. Conclusion3-D plotting is a rapid prototyping technology of growing importance which provides flexibility concerning choice of material and allows integration of sensitive biological components.