report.Rmd

---
header-includes:
    - \usepackage{fancyhdr}
    - \fancyfoot[CO,CE]{OSC-Group - http://www.osc-lab.de - JMU Wuerzburg - Pharmazie}
    - \fancyfoot[LE,RO]{\thepage}
    - \usepackage{fontspec}
    - \setmainfont{OpenSans}
    - \usepackage{lscape}
    - \newcommand{\blandscape}{\begin{landscape}}
    - \newcommand{\elandscape}{\end{landscape}}
    
title: "TDM Report - Vancomycin"
output: 
  pdf_document:
    latexengine: xelatex
df_print: paged
date: "`r format(Sys.time(), '%d.%B %Y')`"


---
\setmainfont{OpenSans}
\addtolength{\headheight}{1.0cm} 
\pagestyle{fancyplain} 
\rhead{\includegraphics[height=1.2cm]{./logo_rechts.png}} 
\lhead{\includegraphics[height=1.2cm]{./logo_links.png}}
\renewcommand{\headrulewidth}{0pt}


```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# **Patient characteristics at baseline**

  
Patient ID: **`r input$pat_ID`** 
  
Body weight: **`r input$WT`** kg 

Creatinine Clearance: **`r input$CRCL`** mL/min

Receives Dialysis: **`r if(input$has_dialysis) {"Yes"}else{"No"}`**

  
    
``` {r ind_pars, echo=FALSE}


```


# **Pathogen Information**

Pathogen:  **`r names(GLOB_PATHOGENS[as.numeric(input$choose_pathogen)])`**

MIC: **`r input$MIC`** mg/L

``` {r scheme, echo=FALSE}

```

# **Clinical Recommendation**

**`r names(GLOB_RECOMMENDATIONS[as.numeric(input$choose_recommendation)])`**  
 
`r input$report_comment`

`r if(input$additional_tdm){
"Additional TDM sample should be obtained (see Graphic for further information)"
} ` 

`r if(input$add_dur_info){
"Infusion Duration should not fall below 60 min. CAVE: Red-Man-Syndrome!"
} ` 

\newpage

## **Recommended Dosing strategy**


`r if(app_data$forecast_advanced){
tmp <- app_data$user_forecast_data_set

colnames(tmp) <- c('Date', 'Time', 'Dose [mg]', 'Infusion duration [min]')
kable(tmp, format = "latex")  %>%
    kable_styling(position = "left")
} else {

tmp <- data.frame('Interdose Interval [h]'=input$adapt.ii,
                 'Dose [mg]'=input$adapt.dose,
                 'Infusion duration [min]'=input$adapt.dur)
colnames(tmp) <- c('Interdose Interval [h]', 'Dose [mg]', 'Infusion duration [min]')              
kable(tmp, format = "latex")  %>%
    kable_styling(position = "left")
} ` 



\newpage

\blandscape

## **Forecast for the next `r input$adapt.n` doses:**

``` {r recomm, echo=FALSE, warning=FALSE, fig.height = 7, fig.width = 12, fig.align = "center"}

  app_data$adapted_pk_plot_withTDM

```

\elandscape

\newpage

# **Dataset used**


``` {r tdm, echo=FALSE, warning=FALSE}

kable(app_data$user_data_set, format = "latex")  %>%
    kable_styling(position = "left")

```


\newpage
\blandscape

# **Simulated Plasmaconcentration from Dataset**


```{r simulation, echo=FALSE, warning=FALSE, fig.height = 7, fig.width = 12, fig.align = "center"}
if(app_data$tdm_samples_available){
  app_data$pk_plots[[1]]
} else {
  app_data$pk_plots[[2]]
}

```

\elandscape

\newpage

# **MCMC Diagnostic Plots (1/2) - Results of Gibbs-Sampling and prior vs posterior distribution**

```{r mcmc_diag, echo=FALSE, warning=FALSE}
if(app_data$tdm_samples_available){
gridExtra::grid.arrange(app_data$mcmc_result[[1]]$p_iter_ETA1, app_data$mcmc_result[[1]]$p_dens_ETA1,    
                              app_data$mcmc_result[[1]]$p_iter_ETA2, app_data$mcmc_result[[1]]$p_dens_ETA2, 
                              app_data$mcmc_result[[1]]$p_iter_ETA3, app_data$mcmc_result[[1]]$p_dens_ETA3, nrow=3, ncol=2, widths=c(3,1))  
}

```

\newpage

# **MCMC Diagnostic Plots (2/2) - distribution and correlation of random effects**

```{r mcmc_diag_2, echo=FALSE, warning=FALSE}
if(app_data$tdm_samples_available){
chart.Correlation(app_data$mcmc_result[[1]]$chain_data, histogram=TRUE)
}

```

\newpage

# **MC Diagnostic Plots - distribution and correlation of random effects**


```{r mc_diag, echo=FALSE, warning=FALSE}
    chart.Correlation(app_data$mc_result[[3]], histogram=TRUE)
```


\newpage

\blandscape

# **Simulated PK Parameter distributions** at baseline

```{r par_dist, echo=FALSE, warning=FALSE, fig.height = 7, fig.width = 16, fig.align = "center"}
    grid.arrange(app_data$dist_plots[[1]],app_data$dist_plots[[2]],app_data$dist_plots[[3]], nrow=1, ncol=3)
```

\elandscape