This repository contains the source code of Classify Chagas, a web application designed for the harmonization and standardization of the classification systems of cardiac clinical inputs related to Chagas disease.
Chagas disease is one of the 21 NTDs (Neglected Tropical Diseases) recognized by the WHO (World Health Organization) as of 2026. It is caused by the parasite Trypanosoma cruzi, and it is a significant health issue in regions of Latin America, where the parasite is endemic.
Its clinical presentation is variable, although it is often characterized by an initial acute phase that may be asymptomatic or present with mild, non-specific symptoms, followed by a long-standing chronic phase.
The disease’s evolution is complex, and accurately staging the severity of the infection is a challenge for healthcare professionals. Additionally, the countries where the disease is endemic often do not have the resources necessary to research or provide precise results.
Classify Chagas aims to provide a solution for the standardization of clinical classification using different but relevant classification systems based on cardiac clinical parameters often found on Chagas disease infection cases.
The tool currently generates results according to the following classification frameworks (stages ordered from highest to lowest severity):
| Classification System | Stages |
|---|---|
| Kuschnir classification system | III → II → I → 0 |
| Second Brazilian Consensus | D → C → B2 → B1 → A → 0 |
| I Latin American Guidelines | D → C → B2 → B1 → A |
| Brazilian Society of Cardiology (SBC) Guidelines | D → C → B2 → B1 → A |
As stated earlier, these classification systems were chosen because of their current relevance in the clinical management of Chagas disease. Further methodological and clinical details on how they were translated into algorithms can be found and are discussed in the following article: Losada Galván I, García M, Hasslocher-Moreno AM, Ortiga A, Sanz S, Molina I et al. How do we classify organ involvement in Chagas disease? A systematic review of organ involvement since 1909, Highlighting the urgent need for a universal classification system in Chronic Chagas disease. 2024 PLoS Negl Trop Dis
The application is implemented and developed using a lightweight, zero-dependency [1] technology stack based on Hypertext Preprocessor (PHP) and JavaScript (JS). It follows a modular three-layer architecture based on a Model-View-Controller web paradigm.
From the user perspective, the application provides a questionnaire-based graphical interface that emulates a clinical assessment form. Through this interface, users can enter the requested parameters for the classification of Chagas disease and obtain the corresponding severity level for each evaluated system explained previously.
Even though it is based on a MVC architecture, the app is executed on the client-side only and does NOT interact nor send any information to internal DDBB of any sorts [2].
[1] TailwindCSS and Google Fonts are imported via external CDN resources in the application's main index file for styling purposes only
[2] Third-party cookies (Google Analytics) are used to monitor web activity with research purposes and aren't mandatory to access the main functionality of the app in any case
The app can be installed locally by cloning this repo and accessing the project directory, using the following commands:
git clone https://github.com/UBIOESGD/classify-chagas.git
cd classify-chagas
If you wish to deploy a local version of the app, you can do so easily using the integrated PHP command:
php -S localhost:<PORT>
For development and validation purposes, you may navigate to the /tests folder (cd tests), where you will find an additional README.md file explaining how you can test the project and the internal algorithm classes.
Version control was introduced halfway through the project's development. An internal changelog has been used to keep track of changes since then. Even if it serves more of dev notes rather than a usual record of changes, if you want to check them they can be found here.
This project was developed by ISGlobal's UBIOESGD (Unitat de Bioestadística i Gestió de Dades) members' Susana Méndez Bartolomé and Carlos Carvajal Ramos in support of the doctoral work of Chagas disease researcher Irene Losada Galván.
Irene's doctoral research regarding the application is on its way of being published as a journal and will be available here when it becomes public.