A Computer Application to Predict Adverse Events in the Short-Term Evolution of Patients With Exacerbation of Chronic Obstructive Pulmonary Disease

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.Fondo de Investigación Sanitaria (PI 06\1010, PI06\1017, PI06\714, PI06\0326, PI06\0664) Departamento de Salud del Gobierno Vasco (2012111008) Departamento de Educación, Política Lingüística y Cultura del Gobierno Vasco (IT620-13) Ministerio de Economía y Competitividad del Gobierno Español and FEDER (MTM2013-40941-P and MTM2016-74931-P) the Research Committee of the Hospital Galdakao the thematic networks -REDISSEC (Red de Investigación en Servicios de Salud en Enfermedades Crónicas) - of the Instituto de Salud Carlos III

Use of generalised additive models to categorise continuous variables in clinical prediction

13 P.Background: In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind. -- Methods: We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the outcome. The proposed method consists of creating at least one average-risk category along with high-and low-risk categories based on the GAM smooth function. We applied this methodology to a prospective cohort of patients with exacerbated chronic obstructive pulmonary disease. The predictors selected were respiratory rate and partial pressure of carbon dioxide in the blood (PCO2), and the response variable was poor evolution. An additive logistic regression model was used to show the relationship between the covariates and the dichotomous response variable. The proposed categorisation was compared to the continuous predictor as the best option, using the AIC and AUC evaluation parameters. The sample was divided into a derivation (60%) and validation (40%) samples. The first was used to obtain the cut points while the second was used to validate the proposed methodology. -- Results: The three-category proposal for the respiratory rate was 24, for which the following values were obtained: AIC=314.5 and AUC=0.638. The respective values for the continuous predictor were AIC=317.1 and AUC=0.634, with no statistically significant differences being found between the two AUCs (p = 0.079). The four-category proposal for PCO2 was 65, for which the following values were obtained: AIC=258.1 and AUC=0.81. No statistically significant differences were found between the AUC of the four-category option and that of the continuous predictor, which yielded an AIC of 250.3 and an AUC of 0.825 (p = 0.115). -- Conclusions: Our proposed method provides clinicians with the number and location of cut points for categorising variables, and performs as successfully as the original continuous predictor when it comes to developing clinical prediction rulesThis study was supported by grants UE+09/62, MTM2010-14913, GIU10/21, 2012111008, IT620-13 and UFI11/52. The work of IB was supported by grant GIU10/21 from the University of the Basque Country UPV/EHU and the CIBER en EpidemiologIa y Salud Publica (CIBERESP). The collection of the COPD data used for this study was supported in part by grants from the Fondo de Investigacion Sanitaria (PI 061010, PI061017, PI06714, PI060326 and PI060664), Basque Country Regional Health Authority, Galdakao Hospital Research Committee and the thematic networks-Red IRYSS (Investigacion en Resultados y Servicios Sanitarios)- of the Instituto de Salud Carlos III (G03/220). The authors declare that there were no conflicts of interest and, lastly, would like to thank Maria Xose Rodriguez-Alvarez for her invaluable help with the implementation of the R code, Michael Benedict for revising the English and the referees and the associate editor for providing thoughtful comments and suggestions which led to substantial improvement of the presentation of the material in this article

Determinants of change in physical activity during moderate-to-severe COPD exacerbation

BACKGROUND: Data are scarce on patient physical activity (PA) level during exacerbations of chronic obstructive pulmonary disease (eCOPD). The objective of the study was to evaluate the level and determinants of change in PA during an eCOPD. MATERIALS AND METHODS: We conducted a prospective cohort study with recruitment from emergency departments (EDs) of 16 participating hospitals from June 2008 to September 2010. Data were recorded on socioeconomic characteristics, dyspnea, forced expiratory volume in 1 second (FEV1%), comorbidities, health-related quality of life, factors related to exacerbation, and PA in a stable clinical condition and during the eCOPD episode. RESULTS: We evaluated 2,487 patients. Common factors related to the change in PA during hospital admission or 7 days after discharge to home from the ED were lower PA at baseline and during the first 24 hours after the index evaluation. Age, quality of life, living alone, length of hospital stay, and use of anticholinergic or systemic corticosteroids in treating the exacerbation were associated with the change in PA among hospitalized patients. Predictors of change among patients not admitted to hospital were baseline FEV1% and dyspnea at rest on ED arrival. CONCLUSION: Among the patients evaluated in an ED for an eCOPD, the level and change in PA was markedly variable. Factors associated with exacerbation (PA 24 hours after admission, medication during admission, and length of hospital stay) and variables reflecting patients' stable clinical condition (low level of PA, age, quality of life, FEV1%) are predictors of the change in PA during a moderate-to-severe eCOPD.This work was supported in part by grants from the Fondo de Investigación Sanitaria (PI 06/1010, PI06/1017,/nPI06/714, PI06/0326, PI06/0664); Department of Health of the Basque Country, Department of Education, Universities and Research of the Basque Government (UE09/62); the Research Committee of the Hospital Galdakao; and the thematic networks – Red IRYSS (Investigacion en Resultados y Servicios Sanitarios (G03/220) – of the Instituto de Salud Carlos III

Determinants of change in physical activity during moderate-to-severe COPD exacerbation

BACKGROUND: Data are scarce on patient physical activity (PA) level during exacerbations of chronic obstructive pulmonary disease (eCOPD). The objective of the study was to evaluate the level and determinants of change in PA during an eCOPD. MATERIALS AND METHODS: We conducted a prospective cohort study with recruitment from emergency departments (EDs) of 16 participating hospitals from June 2008 to September 2010. Data were recorded on socioeconomic characteristics, dyspnea, forced expiratory volume in 1 second (FEV1%), comorbidities, health-related quality of life, factors related to exacerbation, and PA in a stable clinical condition and during the eCOPD episode. RESULTS: We evaluated 2,487 patients. Common factors related to the change in PA during hospital admission or 7 days after discharge to home from the ED were lower PA at baseline and during the first 24 hours after the index evaluation. Age, quality of life, living alone, length of hospital stay, and use of anticholinergic or systemic corticosteroids in treating the exacerbation were associated with the change in PA among hospitalized patients. Predictors of change among patients not admitted to hospital were baseline FEV1% and dyspnea at rest on ED arrival. CONCLUSION: Among the patients evaluated in an ED for an eCOPD, the level and change in PA was markedly variable. Factors associated with exacerbation (PA 24 hours after admission, medication during admission, and length of hospital stay) and variables reflecting patients' stable clinical condition (low level of PA, age, quality of life, FEV1%) are predictors of the change in PA during a moderate-to-severe eCOPD.This work was supported in part by grants from the Fondo de Investigación Sanitaria (PI 06/1010, PI06/1017,/nPI06/714, PI06/0326, PI06/0664); Department of Health of the Basque Country, Department of Education, Universities and Research of the Basque Government (UE09/62); the Research Committee of the Hospital Galdakao; and the thematic networks – Red IRYSS (Investigacion en Resultados y Servicios Sanitarios (G03/220) – of the Instituto de Salud Carlos III

Predictors of Change in Dyspnea Level in Acute Exacerbations of COPD

<p>The aim of this study was to identify factors related to changes in dyspnoea level in the acute and short-term periods after acute exacerbation of chronic obstructive pulmonary disease. This was a prospective cohort study of patients with symptoms of acute chronic obstructive pulmonary disease exacerbation who attended one of 17 hospitals in Spain between June 2008 and September 2010. Clinical data and patient reported measures (dyspnoea level, health-related quality of life, anxiety and depression levels, capacity to perform physical activity) were collected from arrival to the emergency department up to a week after the visit in discharged patients and to discharge in admitted patients (short term). Main outcomes were time course of dyspnoea over the acute (first 24 hours) and short-term periods, mortality and readmission within 2 months of the index episode. Changes in dyspnoea in both periods were related capacity to perform physical activity as well as clinical variables. Short-term changes in dyspnoea were also related to dyspnoea at 24 hours after the ED visit, and anxiety and depression levels. Dyspnoea worsening or failing to improve over the studied periods was associated with poor clinical outcomes. Patient-reported measures are predictive of changes in dyspnoea level.</p

Predictive score for mortality in patients with COPD exacerbations attending hospital emergency departments

Background: Limited information is available about predictors of short-term outcomes in patients with exacerbation of chronic obstructive pulmonary disease (eCOPD) attending an emergency department (ED). Such information could help stratify these patients and guide medical decision-making. The aim of this study was to develop a clinical prediction rule for short-term mortality during hospital admission or within a week after the index ED visit. Methods: This was a prospective cohort study of patients with eCOPD attending the EDs of 16 participating hospitals. Recruitment started in June 2008 and ended in September 2010. Information on possible predictor variables was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up. Main short-term outcomes were death during hospital admission or within 1 week of discharge to home from the ED, as well as at death within 1 month of the index ED visit. Multivariate logistic regression models were developed in a derivation sample and validated in a validation sample. The score was compared with other published prediction rules for patients with stable COPD. Results: In total, 2,487 patients were included in the study. Predictors of death during hospital admission, or within 1 week of discharge to home from the ED were patient age, baseline dyspnea, previous need for long-term home oxygen therapy or non-invasive mechanical ventilation, altered mental status, and use of inspiratory accessory muscles or paradoxical breathing upon ED arrival (area under the curve (AUC) = 0.85). Addition of arterial blood gas parameters (oxygen and carbon dioxide partial pressures (PO2 and PCO2)) and pH) did not improve the model. The same variables were predictors of death at 1 month (AUC = 0.85). Compared with other commonly used tools for predicting the severity of COPD in stable patients, our rule was significantly better. Conclusions: Five clinical predictors easily available in the ED, and also in the primary care setting, can be used to create a simple and easily obtained score that allows clinicians to stratify patients with eCOPD upon ED arrival and guide the medical decision-making process.This work was supported in part by grants from the Fondo de Investigación Sanitaria (PI 06/1010, PI06/1017, PI06/714, PI06/0326, PI06/0664); Department of Health of the Basque Country, Department of Education, Universities and Research of the Basque Government (UE09/62); the Research Committee of the Hospital Galdakao; and the thematic networks- Red IRYSS (Investigacion en Resultados y Servicios Sanitarios (G03/220))- of the Instituto de Salud Carlos II