wolass / WTM2020

The data analysis compendium for the WTM2020 clinical study

WTM2020

A clinical observational study to verify the feasibility of WARMIE sensor in continuous skin temperature monitoring in surgical patients.

Introduction

Continuous temperature monitoring has been previously described to provide many diagnostic benefits over standard temperature point-measurements.

Aim

Validation of clinical feasibility of using WARMIE Sensor in an inpatient-care environment. We aimed to verify the ease of use, reliability, comfort, and correctness of the continuous skin temperature monitoring device.

This repository contains the data and code for our paper:

Francuzik et al., (2021). WTM2020: Validation of a continous skin temperature monitor - WARMIE sensor. Name of journal/book https://doi.org/xxx/xxx

How to cite

Please cite this compendium as:

Francuzik et al., (2023). Compendium of R code and data for WTM2020: Validation of a continous skin temperature monitor - WARMIE sensor. Accessed 01 Dez 2023. Online at https://doi.org/xxx/xxx

Contents

• The folder 1_data_cleaning contains scripts and a final database used in subsequent data analysis (This can either be an Rmd file or a R script).
• Exploratory data analysis is stored in the 2_EDA folder (this should be a .Rmd file).
• All exported objects from the EDA steps, as well as derived data, are stored in the analysis/data/derived_data folder
• All other R scripts are going to be stored in the R folder

The analysis directory contains:

• 📁 paper: R Markdown source document for manuscript. Includes code to reproduce the figures and tables generated by the analysis. It also has a rendered version, paper.docx, suitable for reading (the code is replaced by figures and tables in this file)
• 📁 data: Data used in the analysis.
• 📁 figures: Plots and other illustrations
• 📁 supplementary-materials: Supplementary materials including notes and other documents prepared and collected during the analysis.

How to run in your broswer or download and run locally

This research compendium has been developed using the statistical programming language R. To work with the compendium, you will need installed on your computer the R software itself and optionally RStudio Desktop.

The simplest way to explore the text, code and data is to click on binder to open an instance of RStudio in your browser, which will have the compendium files ready to work with. Binder uses rocker-project.org Docker images to ensure a consistent and reproducible computational environment. These Docker images can also be used locally.

You can download the compendium as a zip from from this URL: master.zip. After unzipping: - open the .Rproj file in RStudio - run devtools::install() to ensure you have the packages this analysis depends on (also listed in the DESCRIPTION file). - finally, open analysis/paper/paper.Rmd and knit to produce the paper.docx, or run rmarkdown::render("analysis/paper/paper.Rmd") in the R console

Licenses

Text and figures : CC-BY-4.0

Code : See the DESCRIPTION file

Data : CC-BY-4.0 attribution requested in reuse

Contributions

We welcome contributions from everyone. Before you get started, please see our contributor guidelines. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.