The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

We focus on the treatment of viral encephalitis and presence of protocol to analyze the effectiveness and safety of Angong Niuhuang pill in the treatment of viral encephalitis. The adjuvant efficacy of Angong Niuhuang pill in the treatment of viral encephalitis includes improving the total effective rates and shortening the disappearance time of clinical syndrome. However, due to the suboptimal quality of evidence, our findings are not definitive and require more high-quality randomized controlled trials.

Our laboratory will focus on the pharmacologic mechanism of Angong Niuhuang pill in the treatment of viral encephalitis. To begin, use the PROSPERO database to register the systematic review procedure. From EndNote's official website, purchase and download the EXE file as an installation program.

Double click the EXE file to start the installer. After purchasing Stata software from the official website, double click the Stata application program to start the installer. From the Copenhagen Trial Unit website, register and download the TSA software zip file, then double click the TSA executable jar file for installation.

In the EndNote, click my group, followed by create group, and type ANP. To import the retrieved literature, click the file menu, then sequentially select import, options, import options, EndNote import, and import. Select the included literature, right click on add references to, and select AP.Then click reference, find duplicates, and keep this record to remove the duplicates.

Fill the Excel spreadsheet with details like first author, publication year, baseline data of a patient with viral encephalitis, and outcome measures. Extract data from dichotomous variables using sample size and composition ratio. Use mean and standard deviation to extract data from the continuous variables.

Create a PRISMA flow chart visualizing the number of studies processed at each step and the reasons for removing them. Use the Cochrane risk of bias tool to evaluate the study's methodology. For analysis, include the terms of bias assessment, random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other biases.

To construct forest plots, open the Stata software. For continuous data entry, click user and select meta-analysis of binary and continuous, then select main and click continuous. Set the sample size, mean, and standard deviation of the treatment group as mean one, SD1 and N1.For the control group, set the sample size, mean, and standard deviation as mean two, SD2, and N2.To select a random model for high heterogenicity, click user and meta-analysis of binary and continuous, then select continuous and random IV heterogeneity.

Choose the appropriate effect model based on the I squared statistics. For calculating the weighted mean difference, under statistics, choose no standard, then to calculate the standardized mean difference, under statistics, choose Cohen. For dichotomous data entry, click on user and select meta-analysis of binary and continuous, then click main and select count.

Set the effective number and non-effective number of the treatment group as E1 and NE1, and for the control group as E2 and NE2. If the I squared statistics is lower than 50%select the fixed model. To do this, click user, then meta-analysis of binary and continuous, followed by binary and fixed inverse variance.

To perform sensitivity analysis in heterogeneity test, click on user, then meta-analysis, influence analysis. metan-based, mettaninf, and continuous. For continuous data, use the DB metabias command, then click main, choose underlying ES and underlying SEES, and select Egger for Egger's linear regression test.

For binary data, use the command metabias E1 NE1 E2 NE2, or Harvard to perform Harvard's weighted linear regression test. Enter the command DB metatrim, then click main and choose underline ES and underline SEES. Then, click linear, fixed, and funnel to adopt the trim and fill procedure to test the robustness of the effect size estimate.

To build a new meta-analysis from the file, select new meta-analysis, then select data type, import name, group one, and group two and choose the outcome type. Set effect measure and model. Use the constant continuous correction method and set the value to 0.5.

Under trial, fill in the study, year, effect, and total number of intervention and control groups, then click add trial. Go to TSA and alpha spending boundary. Enter the name, then set the boundary type as two-sided, the type one error rate alpha to 0.05, and power to 0.8.

For the meta-analysis of the dichotomous outcome, calculate the incidence in control arm, then calculate relative risk reduction according to the precious forest plot of total effective rate. For continuous data, choose mean difference and random effect BT according to the previous results of the forest plot. After clicking trial, fill in the study, year, mean response, standard deviation, and group size of intervention and control groups, then click add trial.

Click on TSA and select alpha spending boundary. Set the boundary type as two-sided, the type one error rate alpha to 0.05, and power to 0.8. Choose empirical in mean difference and variance.

Finally, click perform calculation and select graph to visualize the results.