Illustration of human lungs with bronchial tubes.

Acute COPD Exacerbation Prediction Tool (ACCEPT)

ABOUT:

The Acute COPD Exacerbation Prediction Tool (ACCEPT) is a validated clinical prediction model that predicts rate and severity of COPD exacerbations.

Video

The ACCEPT model aims to inform treatment decisions among people with Chronic Obstructive Pulmonary Disease (COPD). Learn how with this 90-second video, Produced by the Peer Models Network: The ACCEPT Model in 90 Seconds

Interview

Model developer Amin Adibi explains ideas behind developing the Acute COPD Exacerbation Prediction Tool: Amin Adibi on the ACCEPT Model for COPD: Why and How

Web App

An interactive web app for ACCEPT is available at http://resp.core.ubc.ca/ipress/accept

R Package

The R package 'accept' is available from CRAN and can be installed directly from R:

install.packages("accept")

Lastest development version of the package is available from GitHub at https://github.com/resplab/accept/

Peer Models Network: ACCEPT on the Cloud

ACCEPT is accessible through the PRISM clould platform of the Peer Models Network. For more information, please refer to the Peer Models Network home page.

Excel Spreadsheet

A MACRO-enalbed Excel Spreadsheet for ACCEPT can be downloaded from the Peer Models Repository.

SAS Codes

SAS code used to fit the model and R code for figures in the manuscript can be found on GitHub at https://github.com/resplab/accept-codes

User Manual

For more information about the model and how to access it, please refer to the ACCEPT user manual.

Study Protocol

The study protocol for ACCEPT is available at http://resp.core.ubc.ca/show/accept_protocol

Citation

Adibi A, Sin DD, Safari A, Jonhson KM, Aaron SD, FitzGerald JM, Sadatsafavi M. The Acute COPD Exacerbation Prediction Tool (ACCEPT): a modelling study. The Lancet Respiratory Medicine. Published Online First 2020 March 13th; doi:10.1016/S2213-2600(19)30397-2

PARTNERS:

Canadian Institutes of Health Research

PUBLICATIONS:

To see publications related to the study, please go here and select the appropriate filter.

Adibi A, Sin DD, Safari A, et al. The Acute COPD Exacerbation Prediction Tool (ACCEPT): a modelling study. Lancet Respir Med. 2020;8(10):1013-1021. doi:10.1016/S2213-2600(19)30397-2

Michaux KD, Metcalfe RK, Burns P, et al. IMplementing Predictive Analytics towards efficient COPD Treatments (IMPACT): protocol for a stepped-wedge cluster randomized impact study. Diagn Progn Res. 2023;7(1):3. Published 2023 Feb 14. doi:10.1186/s41512-023-00140-6

Sadatsafavi M, Adibi A, Puhan M, Gershon A, Aaron SD, Sin DD. Moving beyond AUC: decision curve analysis for quantifying net benefit of risk prediction models. Eur Respir J. 2021;58(5):2101186. Published 2021 Nov 4. doi:10.1183/13993003.01186-2021

Sadatsafavi M, McCormack J, Petkau J, Lynd LD, Lee TY, Sin DD. Should the number of acute exacerbations in the previous year be used to guide treatments in COPD?. Eur Respir J. 2021;57(2):2002122. Published 2021 Feb 11. doi:10.1183/13993003.02122-2020