Evidence synthesis is the process of systematically gathering, analyzing, and integrating available research evidence. The quality of evidence synthesis depends on the quality of the original studies included. Validity assessment, also known as risk of bias assessment, is an essential method for assessing the quality of these original studies. Currently, there are numerous validity assessment tools available, but some of them lack a rigorous development process and evaluation. The application of inappropriate validity assessment tools to assessing the quality of the original studies during the evidence synthesis process may compromise the accuracy of study conclusions and mislead the clinical practice. To address this dilemma, the LATITUDES Network, a one-stop resource website for validity assessment tools, was established in September 2023, led by academics at the University of Bristol, U.K. This Network is dedicated to collecting, sorting and promoting validity assessment tools to improve the accuracy of original study validity assessments and increase the robustness and reliability of the results of evidence synthesis. This study introduces the background of the establishment of the LATITUDES Network, the included validity assessment tools, and the training resources for the use of validity assessment tools, in order to provide a reference for domestic scholars to learn more about the LATITUDES Network, to better use the appropriate validity assessment tools to conduct study quality assessments, and to provide references for the development of validity assessment tools.
The theoretical foundation of relevant packages of R software for network meta-analysis is mainly based on Bayesian statistical model and a few of them use generalized linear model. Network meta-analysis is performed using GeMTC R package through calling the corresponding rjags package, BRugs package, or R2WinBUGS package (namely, JAGS, OpenBUGS, and WinBUGS software, respectively). Meanwhile, GeMTC R package can generate data storage files for GeMTC software. Techonically, network meta-analysis is performed through calling the software based on Markov Chain Monte Carlo method. In this article, we briefly introduce how to use GeMTC R package to perform network meta-analysis through calling the OpenBUGS software.
Network plots can clearly present the relationships among the direct comparisons of various interventions in a network meta-analysis. Currently, there are some methods of drawing network plots. However, the information provided by a network plot and the interface-friendly degree to a user differ in the kinds of software. This article briefly introduces how to draw network plots using the network package and gemtc package that base on R Software, Stata software, and ADDIS software, and it also compares the similarities and differences among them.
The WinBUGS software can be called from either R (provided R2WinBUGS as an R package) or Stata software for network meta-analysis. Unlike R, Stata software needs to create relevant ADO scripts at first which simplify operation process greatly. Similar with R, Stata software also needs to load another package when drawing network plots. This article briefly introduces how to implement network meta-analysis using Stata software by calling WinBUGS software.
R Software is an open, free of use and charge statistical software which has a powerful graphic capability; however, it requires more complex codes and commands to perform network meta-analysis, which causes errors and difficulties in operation. WinBUGS software is based on Bayesian theory, which has a powerful data processing capability, and especially its codes are simple and easy to operate for dealing with network meta-analysis. However, its function of illustrating statistical results is very poor. In order to fully integrate the advantages of R software and WinBUGS software, an R2WinBUGS package based on R software has been developed which builds a “bridge” across two of them, making network meta-analysis process conveniently, quickly and result illustration more beautiful. In this article, we introduced how to use the R2WinBUGS package for performing network meta-analysis using examples.
The aggregate data drug information system (ADDIS) software is a non-programming software which is based on the Bayesian framework and using the Markov chain Monte Carlo (MCMC) method for prior assessment and implementation. The operation is fairly easy for users. The consequent results and relevant plots could be output automatically by the software after users assess the consistency of model and convergence diagnostics. The major disadvantage of ADDIS is the more complicated data entry. This article introduces how to perform network meta-analysis using ADDIS software.
OBJECTIVE: To study the stimulating effects of basic fibroblast growth factor(bFGF) on fibroblast function and its ability to expression of c-fos gene. Furthermore, to explore the possible network action between bFGF and oncogene in modulating wound healing. METHODS: Cultured rat fibroblasts were divided into bFGF stimulating group and control group. Fibroblasts in bFGF stimulating group were treated with bFGF in a dosage of 40 ng/culture hole, while the control fibroblasts were treated with the same vehicle without bFGF. The morphology, cell vitality and their ability to express c-fos gene in the fibroblasts in both groups were studied with MTT and immunohistochemical methods. RESULTS: All fibroblasts in bFGF treated groups were enlarged and showed increased vitality with MTT method. C-fos gene expression in bFGF stimulating group was increased, especially in nucleus when compared with those in control group. CONCLUSION: The results show that the function and the ability to express c-fos gene in bFGF treated fibroblasts are enhanced. Combined with our previous studies, it may make a conclusion that there is a network regulation mechanism between growth factors and some oncogenes.
Objectives To train postgraduate medical students the ability of effectively using network resources and independently studying, and to explore new model of clinical liver cancer teaching. Methods The teaching model of problembased learning (PBL) to clinical liver cancer teaching was applied. Results The teaching model of PBL changed graduate student the status of passive acceptance to active participation. The teaching process was full of livingness, and the teaching quality was improved.Conclusion The teaching model of PBL can break through the limitations of passive acceptance of book knowledge in traditional teaching model and improve the ability to handle the comprehensive clinical knowledge of liver cancer, which provides a new model to the teaching of liver cancer to graduate medical students in clinic.
Ambulatory electrocardiogram (ECG) monitoring can effectively reduce the risk and death rate of patients with cardiovascular diseases (CVDs). The Body Sensor Network (BSN) based ECG monitoring is a new and efficient method to protect the CVDs patients. To meet the challenges of miniaturization, low power and high signal quality of the node, we proposed a novel 50 mm×50 mm×10 mm, 30 g wireless ECG node, which includes the single-chip analog front-end AD8232, ultra-low power microprocessor MSP430F1611 and Bluetooth module HM-11. The ECG signal quality is guaranteed by the on-line digital filtering. The difference threshold algorithm results in accuracy of R-wave detection and heart rate. Experiments were carried out to test the node and the results showed that the proposed node reached the design target, and it has great potential in application of wireless ECG monitoring.