Arostegui Inmaculada, Legarreta María José, Barrio Irantzu, Esteban Cristobal, Garcia-Gutierrez Susana, Aguirre Urko, Quintana José María
Departamento de Matemática Aplicada y Estadística e Investigación Operativa, The University of the Basque Country UPV/EHU, Leioa, Spain.
Research Institute, Basque Center for Applied Mathematics, Bilbao, Spain.
JMIR Med Inform. 2019 Apr 17;7(2):e10773. doi: 10.2196/10773.
Chronic obstructive pulmonary disease (COPD) is a common chronic disease. Exacerbations of COPD (eCOPD) contribute to the worsening of the disease and the patient's evolution. There are some clinical prediction rules that may help to stratify patients with eCOPD by their risk of poor evolution or adverse events. The translation of these clinical prediction rules into computer applications would allow their implementation in clinical practice.
The goal of this study was to create a computer application to predict various outcomes related to adverse events of short-term evolution in eCOPD patients attending an emergency department (ED) based on valid and reliable clinical prediction rules.
A computer application, Prediction of Evolution of patients with eCOPD (PrEveCOPD), was created to predict 2 outcomes related to adverse events: (1) mortality during hospital admission or within a week after an ED visit and (2) admission to an intensive care unit (ICU) or an intermediate respiratory care unit (IRCU) during the eCOPD episode. The algorithms included in the computer tool were based on clinical prediction rules previously developed and validated within the Investigación en Resultados y Servicios de Salud COPD study. The app was developed for Windows and Android systems, using Visual Studio 2008 and Eclipse, respectively.
The PrEveCOPD computer application implements the prediction models previously developed and validated for 2 relevant adverse events in the short-term evolution of patients with eCOPD. The application runs under Windows and Android systems and it can be used locally or remotely as a Web application. Full description of the clinical prediction rules as well as the original references is included on the screen. Input of the predictive variables is controlled for out-of-range and missing values. Language can be switched between English and Spanish. The application is available for downloading and installing on a computer, as a mobile app, or to be used remotely via internet.
The PrEveCOPD app shows how clinical prediction rules can be summarized into simple and easy to use tools, which allow for the estimation of the risk of short-term mortality and ICU or IRCU admission for patients with eCOPD. The app can be used on any computer device, including mobile phones or tablets, and it can guide the clinicians to a valid stratification of patients attending the ED with eCOPD.
ClinicalTrials.gov NCT00102401; https://clinicaltrials.gov/ct2/show/results/NCT02434536 (Archived by WebCite at http://www.webcitation.org/76iwTxYuA).
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/1472-6963-11-322.
慢性阻塞性肺疾病(COPD)是一种常见的慢性疾病。慢性阻塞性肺疾病急性加重(eCOPD)会导致疾病恶化以及患者病情进展。有一些临床预测规则可能有助于根据病情进展不佳或不良事件的风险对eCOPD患者进行分层。将这些临床预测规则转化为计算机应用程序将使其能够在临床实践中得以应用。
本研究的目的是创建一个计算机应用程序,以基于有效且可靠的临床预测规则,预测急诊科(ED)就诊的eCOPD患者短期病情进展相关不良事件的各种结局。
创建了一个计算机应用程序,即eCOPD患者病情进展预测(PrEveCOPD),以预测与不良事件相关的2种结局:(1)住院期间或ED就诊后一周内的死亡率,以及(2)在eCOPD发作期间入住重症监护病房(ICU)或中级呼吸护理病房(IRCU)。该计算机工具中包含的算法基于先前在慢性阻塞性肺疾病健康结果与服务研究中开发并验证的临床预测规则。该应用程序分别使用Visual Studio 2008和Eclipse为Windows和安卓系统开发。
PrEveCOPD计算机应用程序实现了先前为eCOPD患者短期病情进展中2种相关不良事件开发并验证的预测模型。该应用程序可在Windows和安卓系统下运行,并且可以作为本地应用程序或Web应用程序远程使用。屏幕上包含临床预测规则的完整描述以及原始参考文献。预测变量的输入会针对超出范围的值和缺失值进行控制。语言可以在英语和西班牙语之间切换。该应用程序可供下载并安装在计算机上、作为移动应用程序使用,或通过互联网远程使用。
PrEveCOPD应用程序展示了临床预测规则如何被总结为简单易用的工具,从而能够估计eCOPD患者短期死亡以及入住ICU或IRCU的风险。该应用程序可在任何计算机设备上使用,包括手机或平板电脑,并且可以指导临床医生对就诊于ED的eCOPD患者进行有效的分层。
ClinicalTrials.gov NCT00102401;https://clinicaltrials.gov/ct2/show/results/NCT02434536(由WebCite存档于http://www.webcitation.org/76iwTxYuA)。
国际注册报告识别号(IRRID):RR2-10.1186/1472-6963-11-322。