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。

Adriana Maldonado-Franco, Luis F Giraldo-Cadavid, Eduardo Tuta-Quintero, Alirio R Bastidas, Angélica Moreno-Giraldo, Daniel A Botero-Rosas
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摘要

导言:慢性阻塞性肺病(COPD)是全球第三大死亡原因,因此有必要开发有用的诊断工具,以提高基层医疗机构的及时诊断率:目的:开发一款显示肺活量和临床信息(包括呼吸系统症状和危险因素)的网络应用程序,以促进慢性阻塞性肺病的诊断:在这项横断面研究中,三位专家采用德尔菲法达成了专家共识,以选择慢性阻塞性肺病诊断的相关变量。我们开发了一个基于 Python 的网络应用程序,用于诊断慢性阻塞性肺病,沿肺活量曲线显示专家认为相关的临床变量:结果:26 个临床变量被纳入慢性阻塞性肺病诊断的网络应用程序。第四位专家使用该网络应用程序对 695 名患者进行了分类,这些患者在一家三级中心接受了肺活量测定,并回答了五份慢性阻塞性肺病筛查问卷中的至少一份。在这 695 名受试者中,根据使用网络应用程序对他们进行诊断的专家的说法,34% 的受试者患有慢性阻塞性肺病。慢性阻塞性肺病组中只有 42% 的患者曾接受过慢性阻塞性肺病诊断,无慢性阻塞性肺病组中有 19% 的患者曾被误诊为慢性阻塞性肺病:我们开发了一款网络应用程序,可显示人口统计学和临床信息以及肺活量测定数据,为基层医疗机构诊断慢性阻塞性肺病提供便利。
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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.

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