There are so many biomechanical risk factors related with glaucoma and their relationship is much complex. This paper reviewed the state-of-the-art research works on glaucoma related mechanical effects. With regards to the development perspectives of studies on glaucoma biomechanics, a completely novel biomechanical evaluation factor -- Fractional Flow Reserve (FPR) for glaucoma was proposed, and developing clinical application oriented glaucoma risk assessment algorithm and application system by using the new techniques such as artificial intelligence and machine learning were suggested.
This study aims to determine the salient brain regions with abnormal changes in white matter structures from diffusion tensor imaging (DTI) images of the patients with temporal lobe epilepsy (TLE), and to discriminate the patients with TLE from normal controls (NCs). Firstly, the DTI images from 50 subjects (28 NCs and 22 TLE) were acquired. Secondly, the four measures including the fractional anisotropy (FA), the mean diffusivity (MD), the axial diffusivity (AD) and the radial diffusivity (RD) were calculated. Thirdly, the tract-based spatial statistics (TBSS) was adopted to extract the measures in brain regions with significant differences between the two compared groups. Fourthly, the obtained measures were used as input features of the support vector machine (SVM) for classification, and the support vector machine-recursive feature elimination (SVM-RFE) was compared with the support vector machine-tract-based spatial statistics (SVM-TBSS) method. Finally, the essential brain regions and their spatial distribution were analyzed and discussed. The experimental results showed that the FA measures of the TLE group decreased significantly in the corpus callosum, superior longitudinal fasciculus, corona radiata, external capsule, internal capsule, inferior fronto-occipital fasciculus, fasciculus uncinatus and sagittal stratum, which were nearly bilaterally distributed, while the MD and RD increased significantly in most of these brain regions of the TLE group. Although the AD also increased, the differences were not statistically significant. The SVM-TBSS classifier obtained accuracies of 82%, 76% and 76% using the FA, MD and RD for classification, respectively, and 80% using combined measures. The SVM-RFE classifier obtained accuracies of 90%, 90% and 92% using the FA, MD and RD respectively, while the highest accuracy was 100% using combined measures. These results demonstrated that the SVM-RFE outperformed the SVM-TBSS, and the dominant characteristic influencing classification in brain regions were in associative and commissural fibers. These results illustrated that the measures of DTI images could reveal the abnormal changes in white matter structure of patients with TLE, providing effective information to clarify its pathological mechanism, localize the focus and diagnose automatically.
Objective To investigate confidence interval estimation for the amount of heterogeneity in meta-analysis. Methods On the basis of BT’s method, the approximate Q-statistic distribution following linear transformation of Chi-square was applied to improve the accuracy of Q-statistic distribution, and to obtain the confidence interval for the amount of heterogeneity in meta-analysis. Results In case, the Q1 distribution obtained 95%CI 0.07 to 2.20, while the Q2 distribution obtained 95%CI 0.00 to 1.41; The proposed method Q2 narrowed down the range of confidence interval. Conclusion On account of improving the accuracy of Q-statistic distribution, the proposed method effectively strengthens the coverage probabilities of the confidence interval for the amount of heterogeneity. And the proposed method can also improve the precision of the confidence interval estimation for the amount of heterogeneity.
ObjectiveTo analyze the risk factors of severe retinopathy of prematurity (ROP) and provide consultable evidence for the rational establishment of screening standard.MethodsThe clinical data of 168 prematureinfants (gestational age less than 37 weeks) who was diagnosed in our department from Dec 2002 to Apr 2004 was analyzed retrospectively. Gender, birth count (BC), gestational age (GA), birth weight (BW), duration of oxygen therapy and vascularization devlopment of posterior and peripheral retina examined by binocular indirect ophthalmoscope after mydriasis were recorded. The results were recorded by the international classification of ROP (ICROP), and stage 1, 2 and 3 were mild ROP while threshold disease, stage 4 and 5 were severe ROP. Logistic regression was appliedto analyze the relationship of ROP and gender, BC, GA, BW, and oxygen therapy. ResultsSevere ROP was found in 91 eyes (27.1%) of 47 infants (28.0%) in 336 eyes of 168 premature infants, including threshold disease in 20 eyes (6.0%) and disease at stage 4 in 11 eyes (3.3%) in which the diseases at stage 4A was foundin 2 eyes (0.6%) and stage 4B in 9 eyes (2.7%). There were 60 eyes (17.8%) at stage 5. In all of the factors, GA, BW and oxygen therapy were found to have a significant impact on severe ROP (P=0.000, 0.000 and 0.015,α=0.05) while gender and BC were not (P=0.640 and 0.084, α=0.05). Statistic analysis of subgroupshowed that the risk of severe ROP in premature infants would increase significantly when GA≤30 weeks, BW≤1500 g or oxygen therapy gt;4 days. Conclusions Severe ROP relates to GA, BW and oxygen therapy instead of gender and BC. The risk of occurrence of severe ROP in premature infants increases significantly when GA≤30 weeks, BW≤1500g or oxygen therapy gt;4 days, so it is recommended to screen such premature infants carefully. (Chin J Ocul Fundus Dis,2005,21:271-274)
The "bnma" package is a Bayesian network meta-analysis software package developed based on the R programming language. The network meta-analysis was performed utilizing JAGS software, which yielded relevant results and visual graphs. Moreover, this software package provides support for various data structures and types, while also providing the advantages of flexible utilization, user-friendly operation, and deliver of rich and accurate outcomes. In this paper, using a network meta-analysis example of different therapies for androgenetic alopecia, the operational process of conducting network meta-analysis using the "bnma" package is briefly introduced.
Multivariate time series problems widely exist in production and life in the society. Anomaly detection has provided people with a lot of valuable information in financial, hydrological, meteorological fields, and the research areas of earthquake, video surveillance, medicine and others. In order to quickly and efficiently find exceptions in time sequence so that it can be presented in front of people in an intuitive way, we in this study combined the Riemannian manifold with statistical process control charts, based on sliding window, with a description of the covariance matrix as the time sequence, to achieve the multivariate time series of anomaly detection and its visualization. We made MA analog data flow and abnormal electrocardiogram data from MIT-BIH as experimental objects, and verified the anomaly detection method. The results showed that the method was reasonable and effective.
Through collecting and synthesizing the paper concerning the method of dealing with heterogeneity in the meta analysis, to introduce the multi-levels statistical models, such as meta regression and baseline risk effect model based on random effects, and random effects model based on hierarchical bayes, and to introduce their application of controlling the meta analysis heterogeneity. The multi-levels statistical model will decompose the single random error in the traditional model to data structure hierarchical. Its fitting effect can not only make the meta-analysis result more robust and reasonable, but also guide clinical issues through the interpretation of association variable.
Objective
To establish a risk prediction model of diabetic retinopathy (DR) for type 2 diabetic patients (T2DM).
Methods
A total of 315 T2DM patients (600 eyes) were enrolled in the study. There were 132 males (264 eyes) and 183 females (366 eyes). The mean age was (67.28±12.17) years and the mean diabetes duration was (10.86±7.81) years. The subjects were randomly assigned to model group and check group, each had 252 patients (504 eyes) and 63 patients (126 eyes) respectively. Some basic information including gender, age, education degree and diabetes duration were collected. The probable risk factors of DR including height, weight, blood pressure, fasting glucose, glycosylated hemoglobin (HbA1c), blood urea, serum creatinine, uric acid, triglyceride, total cholesterol, high-density lipoprotein, low density lipoprotein cholesterol and urinary protein. The fundus photograph and the axial length were measured. Multivariate logistic regression was used to analyze the correlative factors of DR and establish the regression equation (risk model). Receiver operating characteristic (ROC) curves were used to determine the cut-off point for the score. The maximum Youden Index was used to determine the threshold of the equation. The check group was used to check the feasibility of the predictive model.
Results
Among 504 eyes in the model group, 170 eyes were DR and 334 eyes were not. Among 126 eyes in the check group, 45 eyes were DR and 81 eyes were not. Multivariate logistic regression analysis revealed that axial length [β=–0.196, odds ratio (OR)=0.822,P＜0.001], age (β=-0.079,OR=0.924,P＜0.001), diabetes duration (β=0.048,OR=1.049,P=0.001), HbA1c (β=0.184,OR=1.202,P=0.020), urinary protein (β=1.298,OR=3.661,P＜0.001) were correlated with DR significantly and the simplified calculation of the score of DR were as follows:P=7.018–0.196X1–0.079X2+0.048X3+0.148X4+1.298X5 (X1= axial length, X2=age, X3=diabetes duration, X4=glycosylated hemoglobin, X5= urinary protein). The area under the ROC curve for the score DR was 0.800 and the cut-off point of the score was -1.485. The elements of the check group were substituted into the equation to calculate the scores and the scores were compared with the diagnostic threshold to ensure the patients in high-risk of DR. The result of the score showed 84% sensitivity and 59% specificity. ROC curve for the score to predict DR was 0.756.
Conclusion
Axial length, age, diabetes duration, HbA1c and urinary protein have significant correlation with DR. The sensitivity and specificity of the risk model to predict DR are 84.0% and 59.0% respectively. The area under the ROC curve was 0.756.
This article systematically reviews the series of articles on randomized controlled trial (RCT) methodology guidance published in JAMA Surgery between 2022 and 2023. It focuses on providing an overview and guidance on critical aspects such as trial implementation and oversight, participant recruitment, statistical applications, and key points in manuscript publication. The aim is to offer valuable insights and references for surgeons to conduct efficient clinical trials and successfully publish their research findings.
The selection of summary statistics to use in a meta-analysis is very important for the interpretation and application of its results. This paper introduces some basic concepts of summary statistics in meta-analysis. The selection of a summary statistic for a meta-analysis depends on the following factors: design of the studies being combined, type of data, consistency among the included studies, mathematical properties and ease of interpretation. For continuous data, the weighted mean difference (WMD) is recommended when all trials use the same scale to report their outcomes, while standardized mean difference (SMD) is more appropriate when trials use different scales to report their outcomes, or the means of their outcomes differ greatly. For dichotomous data, rate ratio or relative risk (RR) is bly recommended to be the summary statistics for meta-analyses of randomized trials. The use of odds ratio (OR) as the summary statistic is similar to that of RR, if the event being studied in both the intervention (exposure) and the control group is rare. There is no single measurement that is uniformly best for all meta-analyses.
