The key for performing meta-analysis using WinBUGS software is to construct a model of Bayesian statistics. The hand-written code model and Doodle model are two major methods for constructing it. The approach of hand-written code is flexible and convenient, but the language programming is fallibility. The Doodle is complicated, but it is benefit to understand the structure of hand-written code model and prevent error. This article briefly describes how to construct the Doodle model for binary and continuous data of head to head meta-analysis, indirect comparison and network meta-analysis, and ordinal variables meta-analysis.
ObjectiveTo establish an appropriate diabetic retinopathy (DR) risk assessment model for patients with type 2 diabetes mellitus (T2DM).MethodsA retrospective clinical analysis. From January 2016 to December 2017, 753 T2DM patients in the Third Affiliated Hospital of Southern Medical University were analyzed retrospectively. Digital fundus photography was taken in all patients. Fasting plasma glucose (FPG), HbA1c, total bilirubin (TB), blood platelet, total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-c), low density lipoprotein cholesterol (LDL-c), apolipoprotein-A (apoA), apolipoprotein-B (apoB), serum creatinine, blood urea nitrogen (BUN), blood uric acid, fibrinogen (Fg), estimated glomerular filtration (eGFR) were collected. The patients were randomly assigned to model group and testify group, each had 702 patients and 51 patients respectively. Logistic regression was used to screen risk factors of DR and develop an assessment scale that can be used to predict DR. Goodness of fit was examined using the Hosmer-Lemeshow test and the area under the receiver operating characteristic (ROC) curve.ResultsAmong 702 patients in the model group, 483 patients were DR, 219 patients were NDR. The scores for DR risk were duration of diabetes ≥4.5 years, 4 points; total bilirubin ＜6.65 mol/L, 2 points; apoA≥1.18 g/L, 2 points; blood urea≥6.46 mmol/L, 1 points; HbA1c ≥7.75%, 2 points; HDL-c＜1.38 mmol/L, 2 points; diabetic nephropathy, 3 points; fibrinogen, 1 point. The area under the receiver operating characteristic curve was 0.787. The logistic regression analysis showed that the risk factors independently associated with DR were duration of diabetes (β=1.272, OR=3.569, 95%CI 2.283−5.578, P＜0.001), TB (β=0.744, OR=2.104, 95%CI 1.404−3.152, P＜0.001, BUN (β=0.401, OR=1.494, 95%CI 0.996−2.240, P=0.052), HbA1c (β=0.545, OR=1.724, 95%CI 1.165−2.55, P=0.006), HDL-c (β=0.666, OR=1.986, 95%CI 1.149−3.298, P=0.013), diabetic nephropathy (β=1.151, OR=3.162, 95%CI 2.080−4.806, P=0.013), Fg (β=0.333, OR=1.396, 95%CI 0.945−2.061, P=0.094). The risk model was P=1/[1+exp−(−3.799+1.272X1+0.744X2+0.769X3+0.401X4+0.545X5+0.666X6+1.151X7+0.333X8)]. X1= duration of diabetes, X2=TB, X3=apoA, X4=BUN, X5=HbA1c, X6=HDL-c, X7=diabetic nephropathy, X8=Fg. The area under the ROC curve was 0.787 and the Hosmer-Lemeshow test suggested excellent agreement (χ2=10.125, df=8, P=0.256) in model group. The area under the ROC curve was 0.869 and the Hosmer-Lemeshow test suggested excellent agreement (χ2=5.345, df=7, P=0.618) in model group.ConclusionThe area under the ROC curve for DR was 0.787. The duration of diabetes, TB, BUN, HbA1c, HDL-c, diabetic nephropathy, apoA, Fg are the risk factors of DR in T2DM patients.
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.
The valid results of Meta-analysis on biomedical data, will have an important value to clinical practice and health policy making. To review the validity of meta-analysis results, one should consider the following issues: The coverage ratio of included studies, quality of data, publication bias and its effect, heterogeneity, the correct selection of statistical methods as well as clinical significance and external validity of overall effect size. The results of Meta-analysis will keep on updating as new related studies are located and included.
Objective To analyze the status of applying diagnostic test in imaging scientific study internationally and domestically, and to compare the application of the image diagnostic studies of our country with that of abroad. Method We hand-searched the diagnosis tests published in the "Chinese Journal of Radiology", the most influential in China, and in "Radiology’’, the most influential abroad, from 1998 to 1999 respectively. Then we evaluated each of the diagnosis tests according to the international standards. Results We searched 408 original articles in "Chinese Journal of Radiology" in which the diagnostic test articles were 12%, and 796 original articles in "Radiology" with the diagnostic test articles 23% from 1998 to 1999 respectively. In these diagnosis tests, by comparing the "Chinese journal of radiology" with the "Radiology", it was found that 19% applied blind comparison with Gold Standard, 28% calculated sensitivity, specificity and accuracy, 9% both calculated negative predictive value and positive predictive value and none calculated likelihood ratios in the former versus 64%, 57%, 33% and 26% and 3% respectivdy in the latter. Conclusions Compared with the international level, both the quality and the quantity of the diagnosis tests applied in the specialty of imaging scientific study in China are much lower and far from meeting the clinical requirement. Improving the methods of scientific study and carrying on more diagnosis tests with high qualities are of important significance in improving the diagnostic level of imaging.
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.
Objective To explore the knowledge distribution, knowledge clustering, and the trend in development of wound therapy, by revealing the same keywords with multiple statistical method and social network analysis. Methods We searched the CNKI under the term " wound” , " therapy” , and " wound therapy” in February 2016. After the core keywords had been identified by Bicomb and Endnote X6 software in each stage, the co-occurrence matrix was built. Transformation, dimensionality reduction and clustering of the co-occurrence matrix were finished by SPSS 22.0 software, leading the strategic plot to be built. The visualized network images were drawn using Ucinet 6.0 software. Results The visualized domain knowledge-mapping was successfully built, and it directly reflected the structure of knowledge-mapping of the discipline, as well as key clusters. Boost development had been identified in this research. The subject developed own core research areas and clusters, but there was still lack of fitting characteristics. The newly wound therapeutic techniques had limited correlation with other clusters, while provided limited contributions to forward this subject. However, enriched core keywords had been demonstrated, and formed clear domain parts of this subject. Conclusions The analysis demonstrates that wound therapy has developed well, and hot research points follow the direction of medication treatment. The network of wound therapeutic subject has become mature and completed within a short period. Comprehensive therapy and long term follow-up results according to evidence-based nursing have become the domain field. Moreover, the newly therapeutic techniques should be paid more attention to shift the development of this subject. And the interactive research within this subject and among other regions should be enhanced.
For speech detection in Parkinson’s patients, we proposed a method based on time-frequency domain gradient statistics to analyze speech disorders of Parkinson’s patients. In this method, speech signal was first converted to time-frequency domain (time-frequency representation). In the process, the speech signal was divided into frames. Through calculation, each frame was Fourier transformed to obtain the energy spectrum, which was mapped to the image space for visualization. Secondly, deviations values of each energy data on time axis and frequency axis was counted. According to deviations values, the gradient statistical features were used to show the abrupt changes of energy value in different time-domains and frequency-domains. Finally, KNN classifier was applied to classify the extracted gradient statistical features. In this paper, experiments on different speech datasets of Parkinson’s patients showed that the gradient statistical features extracted in this paper had stronger clustering in classification. Compared with the classification results based on traditional features and deep learning features, the gradient statistical features extracted in this paper were better in classification accuracy, specificity and sensitivity. The experimental results show that the gradient statistical features proposed in this paper are feasible in speech classification diagnosis of Parkinson’s patients.
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.
In 2025, the American Cancer Society published "Cancer statistics, 2025", which projected cancer data for the upcoming year based on incidence data collected by central cancer registries (through 2021) and mortality data obtained from the National Center for Health Statistics (through 2022). Similarly, the National Cancer Center of China released "Cancer incidence and mortality in China, 2022" in December 2024, analyzing data from 22 cancer registries across the country. This study provides a comparative analysis of cancer incidence and mortality trends in China and the United States during the same period, with a focus on sex- and age-specific distributions and long-term changes in cancer patterns. Long-term trends indicate that lung and liver cancer mortality rates in China have declined, primarily due to tobacco control measures and hepatitis B vaccination programs. However, the burden of gastric and esophageal cancers remains substantial. In the United States, mortality rates for colorectal and lung cancers have continued to decline, largely attributed to widespread screening programs and advances in immunotherapy. As economic growth and social development, China’s cancer profile is gradually shifting towards patterns observed in countries with high human development index. However, the prevention and control of upper gastrointestinal cancers remains a critical public health challenge that requires further attention.