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.
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.
Patient-specific volumetric modulated arc therapy (VMAT) quality assurance (QA) process is an important component of the implementation process of clinical radiotherapy. The tolerance limit and action limit of discrepancies between the calculated dose and the delivered radiation dose are the key parts of the VMAT QA processes as recognized by the AAPM TG-218 report, however, there is no unified standard for these two values among radiotherapy centers. In this study, based on the operational recommendations given in the AAPM TG-218 report, treatment site-specific tolerance limits and action limits of gamma pass rate in VMAT QA processes when using ArcCHECK for dose verification were established by statistical process control (SPC) methodology. The tolerance limit and action limit were calculated based on the first 25 in-control VMAT QA for each site. The individual control charts were drawn to continuously monitor the VMAT QA process with 287 VMAT plans and analyze the causes of VMAT QA out of control. The tolerance limits for brain, head and neck, abdomen and pelvic VMAT QA processes were 94.56%, 94.68%, 94.34%, and 92.97%, respectively, and the action limits were 93.82%, 92.54%, 93.23%, and 90.29%, respectively. Except for pelvic, the tolerance limits for the brain, head and neck, and abdomen were close to the universal tolerance limit of TG-218 (95%), and the action limits for all sites were higher than the universal action limit of TG-218 (90%). The out-of-control VMAT QAs were detected by the individual control chart, including one case of head and neck, two of the abdomen and two of the pelvic site. Four of them were affected by the setup error, and one was affected by the calibration of ArcCHECK. The results show that the SPC methodology can effectively monitor the IMRT/VMAT QA processes. Setting treatment site-specific tolerance limits is helpful to investigate the cause of out-of-control VMAT QA.
Objective
To assess the completion of the under 5 mortality rate (U5MR) of Millennium Development Goals in 194 member countries of WHO, and to analyze the present situation of the global U5MR.
Methods
Based on the U5MR and the proportion of main causes of death in the "World Health Statistics 2015", the Millennium Development Goals of the decline of U5MR from 1990 to 2013 was assessed, the U5MR was analyzed by comparison between 2000 and 2013. Bivariate Pearson correlation analysis was used to determine the correlation between mortality and the ratio of infection to non infectious diseases and GDP per person in U5MR.
Results
By 2013, in 194 WHO member states, the U5MR in 46 (23.71%) countries achieved the millennium development goals. Comparison between 2000 and 2013, there was significant difference between low and high mortality groups in six continents (P<0.05), there was no significant difference between the moderate death groups (P>0.05), there was no significant difference in the ratio of infection to non infectious diseases between the middle and low mortality groups (P>0.05), however there was significant difference between the high mortality groups (P<0.05). There was significant difference in the average decline of U5MR and the ratio of non infectious diseases between low and medium, middle and high mortality groups (P<0.05). The Global U5MR had significant regional differences, the highest U5MR was in Africa, the lowest U5MR was in Europe, the medium U5MR was in North America, Oceania, South America, Asia was becoming the middle level. The U5MR was highly correlated with the ratio of infection to non-infectious diseases in every country (r2000y=0.934,r2013y=0.911,P<0.05), and it was low negatively correlated with GDP per capita (r2000y=–0.443,r2013y=–0.433,P<0.05).
Conclusions
There is a long way to reduce global child mortality. Prevention and control should focus on Africa and Asia. Prevention and control of infectious diseases is an effective measure for middle and high mortality countries. Prevention and control of non-infectious diseases is an important measure for low mortality countries. Increasing health investment is an important means to further reduce global U5MR.
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.
The study aims to investigate whether there is difference in pre-treatment white matter parameters in treatment-resistant and treatment-responsive schizophrenia. Diffusion tensor imaging (DTI) was acquired from 60 first-episode drug-na?ve schizophrenia (39 treatment-responsive and 21 treatment-resistant schizophrenia patients) and 69 age- and gender-matched healthy controls. Imaging data was preprocessed via FSL software, then diffusion parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were extracted. Besides, structural network matrix was constructed based on deterministic fiber tracking. The differences of diffusion parameters and topology attributes between three groups were analyzed using analysis of variance (ANOVA). Compared with healthy controls, treatment-responsive schizophrenia showed altered white matter mainly in anterior thalamus radiation, splenium of corpus callosum, cingulum bundle as well as superior longitudinal fasciculus. While treatment-resistant schizophrenia patients showed white matter abnormalities in anterior thalamus radiation, cingulum bundle, fornix and pontine crossing tract relative to healthy controls. Treatment-resistant schizophrenia showed more severe white matter abnormalities in anterior thalamus radiation compared with treatment-responsive patients. There was no significant difference in white matter network topological attributes among the three groups. The performance of support vector machine (SVM) showed accuracy of 63.37% in separating the two patient subgroups (P = 0.04). In this study, we showed different patterns of white matter alterations in treatment-responsive and treatment-resistant schizophrenia compared with healthy controls before treatment, which may help guiding patient identification, targeted treatment and prognosis improvement at baseline drug-na?ve state.
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.
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 deoxyribonucleic acid (DNA) molecule damage simulations with an atom level geometric model use the traversal algorithm that has the disadvantages of quite time-consuming, slow convergence and high-performance computer requirement. Therefore, this work presents a density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm based on the spatial distributions of energy depositions and hydroxyl radicals (·OH). The algorithm with probability and statistics can quickly get the DNA strand break yields and help to study the variation pattern of the clustered DNA damage. Firstly, we simulated the transportation of protons and secondary particles through the nucleus, as well as the ionization and excitation of water molecules by using Geant4-DNA that is the Monte Carlo simulation toolkit for radiobiology, and got the distributions of energy depositions and hydroxyl radicals. Then we used the damage probability functions to get the spatial distribution dataset of DNA damage points in a simplified geometric model. The DBSCAN clustering algorithm based on damage points density was used to determine the single-strand break (SSB) yield and double-strand break (DSB) yield. Finally, we analyzed the DNA strand break yield variation trend with particle linear energy transfer (LET) and summarized the variation pattern of damage clusters. The simulation results show that the new algorithm has a faster simulation speed than the traversal algorithm and a good precision result. The simulation results have consistency when compared to other experiments and simulations. This work achieves more precise information on clustered DNA damage induced by proton radiation at the molecular level with high speed, so that it provides an essential and powerful research method for the study of radiation biological damage mechanism.
