University of Manchester
Browse
1/1
4 files

ThRAll Challenge data set and associated coding information

dataset
posted on 2023-06-13, 09:51 authored by Clare MillsClare Mills, Chloe French, Chiara Nitride

  

As part of the European Food Safety Authority funded project (GP/EFSA/AFSCO/2017/03) entitled  “Detection and Quantification of Allergens in Foods and Minimum Eliciting Doses in Food-Allergic Individuals” (ThRAll)  an online database was built using REDCap (Research Electronic Data Capture). This is a web application for building and managing online surveys and databases which is free to use for REDCap consortium members an electronic clinical record system. The database comprises four instruments as follows which are designed to capture various different types of data:

(1) Protocol: this collates data on the allergenic food used for a food challenge, the matrix it was delivered in, the ingredients used to make the matrix, type of challenges study (e.g. double blind placebo controlled food challenge, open challenge, single dose challenge or one using interspersed doses), the dose progression, dosing interval and stopping criteria. 

(2) Demographics: this captures the data source, research ethics committee number and information on how the challenges are coded regarding whether objective or subjective symptoms were recorded, the country the data originated from, gender, age and BMI of study subject.   

(3) Challenge day: this captures data on a challenge day and the symptoms recorded during the dose progression and their time of development. This instrument is suitable for upload of clinical data collected during a food challenge.

(4) Threshold dose: this captures data that is only available in a summarised form where the lowest observed adverse effect level (LOAEL) and no observed adverse effect level (NOAEL) is provided. This is frequently the case for published data.


The annoymised data collated through the project is provided as an annoymised csv file together with the associated REDCap data dictionary file and code book. 

A coding system was also developed utilising a combination of SNOMED and FoodEx2 codes to support harmonisation of such data. 


Funding

GP/EFSA/AFSCO/2017/03

FS101206

History

Usage metrics

    School of Biological Sciences

    Categories

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC