Adriana Maldonado-Franco, Luis F Giraldo-Cadavid, Eduardo Tuta-Quintero, Alirio R Bastidas, Angélica Moreno-Giraldo, Daniel A Botero-Rosas
{"title":"开发一款评估肺活量曲线和临床变量的网络应用程序,为初级保健中的慢性阻塞性肺病诊断提供支持。","authors":"Adriana Maldonado-Franco, Luis F Giraldo-Cadavid, Eduardo Tuta-Quintero, Alirio R Bastidas, Angélica Moreno-Giraldo, Daniel A Botero-Rosas","doi":"10.7705/biomedica.7142","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Objective: </strong>To develop a web application displaying spirometric and clinical information - including respiratory symptoms and risk factors- to facilitate a COPD diagnosis.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":101322,"journal":{"name":"Biomedica : revista del Instituto Nacional de Salud","volume":"44 Sp. 1","pages":"160-170"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373378/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development of a web application to evaluate spirometric curve and clinical variables to support COPD diagnosis in primary care.\",\"authors\":\"Adriana Maldonado-Franco, Luis F Giraldo-Cadavid, Eduardo Tuta-Quintero, Alirio R Bastidas, Angélica Moreno-Giraldo, Daniel A Botero-Rosas\",\"doi\":\"10.7705/biomedica.7142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Objective: </strong>To develop a web application displaying spirometric and clinical information - including respiratory symptoms and risk factors- to facilitate a COPD diagnosis.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":101322,\"journal\":{\"name\":\"Biomedica : revista del Instituto Nacional de Salud\",\"volume\":\"44 Sp. 1\",\"pages\":\"160-170\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373378/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biomedica : revista del Instituto Nacional de Salud\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7705/biomedica.7142\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomedica : revista del Instituto Nacional de Salud","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7705/biomedica.7142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of a web application to evaluate spirometric curve and clinical variables to support COPD diagnosis in primary care.
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.