Development of a web application to evaluate spirometric curve and clinical variables to support COPD diagnosis in primary care

• Published in: Biomédica 2024-05, Vol.44 (Sp. 1), p.160-170
• Main Authors: Maldonado-Franco, Adriana, Giraldo-Cadavid, Luis F., Tuta-Quintero, Eduardo, Bastidas, Alirio R., Moreno-Giraldo, Angélica, Botero-Rosas, Daniel A.
• Format: Article
• Language: English
• Subjects: data accuracy; diagnosis; Original; pulmonary disease, chronic obstructive; spirometry
• ISSN: 0120-4157; 2590-7379
• DOI: 10.7705/biomedica.7142

Introduction. Choric obstructive pulmonary disease (COPD) is the third mortality cause in the world, and the development of useful diagnostic tools is necessary to improve timely diagnostic rates in primary care settings.Objective. To develop a web application displaying spirometric and clinical information – including respiratory symptoms and risk factors– to facilitate a COPD diagnosis.Materials and methods. In this cross-sectional study, an expert consensus was carried out with three specialists using the Delphi method to choose the relevant variables for COPD diagnosis. We developed a Python-based web application to diagnose COPD, displaying the clinical variables deemed relevant by the experts along the spirometric curve. Results. Twenty-six clinical variables were included in the web application for the diagnosis of COPD. A fourth expert used the web application to classify a cohort of 695 patients who had undergone spirometry in a third-level centre and had answered at least one of five questionnaires for COPD screening. Out of the 695 subjects, 34% had COPD, according to the expert that diagnosed them using the web application. Only 42% of the patients in the COPD group had received a previous COPD diagnosis and 19% of the patients in the no COPD group had been misdiagnosed with the disease.Conclusion. We developed a web application that displays demographic and clinical information, as well as spirometric data, to facilitate the process of diagnosing COPD in primary care settings. Introducción. La enfermedad pulmonar obstructiva crónica (EPOC) es la tercera causa de mortalidad en el mundo y es necesario el desarrollo de herramientas diagnósticas útiles para mejorar las tasas de diagnóstico oportuno en los entornos de atención primaria.Objetivo. Desarrollar una aplicación web que muestre la información clínica y de la espirometría –incluyendo síntomas respiratorios y factores de riesgo– para facilitar el diagnóstico de la EPOC.Materiales y métodos. En este estudio transversal se realizó un consenso de expertos con tres especialistas usando el método Delphi para elegir las variables relevantes para el diagnóstico de EPOC. Se desarrolló una aplicación web basada en Python que muestra la información clínica relevante según los expertos, junto con la curva y los datos de la espirometría para el diagnóstico de la EPOC.Resultados. Se incluyeron 26 variables clínicas para el diagnóstico de la EPOC. Un cuarto experto utilizó la aplicación web para clasific