Predicting 6-minute walking test outcomes in patients with chronic obstructive pulmonary disease without physical performance measures

Background and Objective: Chronic obstructive pulmonary disease (COPD) requires a multifactorial assessment, evaluating the airflow limitation and symptoms of the patients. The 6-min walk test (6MWT) is commonly used to evaluate the functional exercise capacity in these patients. This study aims to propose a novel predictive model of the major 6MWT outcomes for COPD assessment, without physical performance measurements. Methods: Cardiopulmonary and clinical parameters were obtained from fifty COPD patients. These parameters were used as inputs of a Bayesian network (BN), which integrated three multivariate models including the 6-min walking distance (6MWD), the maximum HR (HRmax ) after the walking, and the HR decay 3 min after (HRR3 ). The use of BN allows the assessment of the patients’ status by predicting the 6MWT outcomes, but also inferring disease severity parameters based on actual patient’s 6MWT outcomes. Results: Firstly, the correlation obtained between the estimated and actual 6MWT measures was strong (R = 0.84, MAPE = 8.10% for HRmax ) and moderate (R = 0.58, MAPE = 15.43% for 6MWD and R = 0.58, MAPE = 32.49% for HRR3 ), improving the classical methods to estimate 6MWD. Secondly, the classification of disease severity showed an accuracy of 78.3% using three severity groups, which increased up to 84.4% for two defined severity groups. Conclusions: We propose a powerful two-way assessment tool for COPD patients, capable of predicting 6MWT outcomes without the need for an actual walking exercise. This model-based tool opens the way to implement a continuous monitoring system for COPD patients at home and to provide more personalized care

Breathing pattern estimation using wearable bioimpedance for assessing COPD severity

Breathing pattern has been shown to be different in chronic obstructive pulmonary disease (COPD) patients compared to healthy controls during rest and walking. In this study we evaluated respiratory parameters and the breathing variability of COPD patients as a function of their severity. Thoracic bioimpedance was acquired on 66 COPD patients during the performance of the six-minute walk test (6MWT), as well as 5 minutes before and after the test while the patients were seated, i.e. resting and recovery phases. The patients were classified by their level of airflow limitation into moderate and severe groups. We characterized the breathing patterns by evaluating common respiratory parameters using only wearable bioimpedance. Specifically, we computed the median and the coefficient of variation of the parameters during the three phases of the protocol, and evaluated the statistical differences between the two COPD severity groups. We observed significant differences between the COPD severity groups only during the sitting phases, whereas the behavior during the 6MWT was similar. Particularly, we observed an inverse relationship between breathing pattern variability and COPD severity, which may indicate that the most severely diseased patients had a more restricted breathing compared to the moderate patients.This work was supported in part by the Universities and Research Secretariat from the Ministry of Business and Knowledge/Generalitat de Catalunya under the Grant GRC 2017 SGR 01770, in part by the Agencia Estatal de Investigacion from the Spanish Ministry of Science ánd Innovation and the European Regional Development Fund, under the Grants RTI2018 098472-B-I00 and PID2021-126455OB-I00, and in part by the CERCA Programme/Generalitat de Catalunya.Peer ReviewedPostprint (author's final draft

Predicting 6-minute walking test outcomes in patients with chronic obstructive pulmonary disease without physical performance measures

Background and Objective Chronic obstructive pulmonary disease (COPD) requires a multifactorial assessment, evaluating the airflow limitation and symptoms of the patients. The 6-min walk test (6MWT) is commonly used to evaluate the functional exercise capacity in these patients. This study aims to propose a novel predictive model of the major 6MWT outcomes for COPD assessment, without physical performance measurements. Methods Cardiopulmonary and clinical parameters were obtained from fifty COPD patients. These parameters were used as inputs of a Bayesian network (BN), which integrated three multivariate models including the 6-min walking distance (6MWD), the maximum HR (HRmax) after the walking, and the HR decay 3 min after (HRR3). The use of BN allows the assessment of the patients’ status by predicting the 6MWT outcomes, but also inferring disease severity parameters based on actual patient's 6MWT outcomes. Results Firstly, the correlation obtained between the estimated and actual 6MWT measures was strong (R = 0.84, MAPE = 8.10% for HRmax) and moderate (R = 0.58, MAPE = 15.43% for 6MWD and R = 0.58, MAPE = 32.49% for HRR3), improving the classical methods to estimate 6MWD. Secondly, the classification of disease severity showed an accuracy of 78.3% using three severity groups, which increased up to 84.4% for two defined severity groups. Conclusions We propose a powerful two-way assessment tool for COPD patients, capable of predicting 6MWT outcomes without the need for an actual walking exercise. This model-based tool opens the way to implement a continuous monitoring system for COPD patients at home and to provide more personalized care.Peer ReviewedPostprint (published version

Physical status, symptoms and health-related quality of life during a severe exacerbation of COPD: Recovery and discriminative capacity for future events

Objective: Severe acute exacerbations of chronic obstructive pulmonary disease (AECOPD) can have a negative impact on functional capacity, symptoms and health-related quality of life (HRQOL). This study aimed to i) investigate the recovery of muscle strength, functional capacity, symptoms, and HRQOL in patients after a severe AECOPD; ii) compare with matched patients with stable COPD (SCOPD); and iii) assess whether these assessments at hospital discharge could discriminate patients’ risk for future events. Methods: This observational study assessed patients with AECOPD during hospital discharge (T1) and one month after discharge (T2). Patients with SCOPD were assessed once. Quadriceps force, handgrip strength, short physical performance battery (SPPB), 6-min walk distance (6 MWD), COPD assessment test (CAT), London chest activity of daily living (LCADL), modified medical research council, checklist individual strength-fatigue, patient health questionnaire, and physical activity (Actigraph) were measured. Exacerbation-related readmission and mortality within six months and 1-year were collected. Results: Forty-four patients with AECOPD were matched with 44 patients with SCOPD. At T2, a significant improvement was found for the SPPB total score, 6 MWD, CAT score, and LCADL score. Compared to patients with SCOPD, a worse LCADL score was found at T2 in patients with AECOPD. Patients with AECOPD that were readmitted or died had a worse SPPB classification and five-repetition sit-to-stand test at T1. Conclusion: Patients after severe AECOPD improved in functional capacity and HRQOL one month after hospital discharge, but ADL performance was still worse compared to SCOPD. Patients who were readmitted or died had significantly worse scores on functional tests at hospital dischargepublishe

An association of particulate air pollution and traffic exposure with mortality after lung transplantation in Europe

Air pollution from road traffic is a serious health risk, especially for susceptible individuals. Single-centre studies showed an association with chronic lung allograft dysfunction (CLAD) and survival after lung transplantation, but there are no large studies.13 lung transplant centres in 10 European countries created a cohort of 5707 patients. For each patient, we quantified residential particulate matter with aerodynamic diameter ≤10 µm (PM10) by land use regression models, and the traffic exposure by quantifying total road length within buffer zones around the home addresses of patients and distance to a major road or freeway.After correction for macrolide use, we found associations between air pollution variables and CLAD/mortality. Given the important interaction with macrolides, we stratified according to macrolide use. No associations were observed in 2151 patients taking macrolides. However, in 3556 patients not taking macrolides, mortality was associated with PM10 (hazard ratio 1.081, 95% CI 1.000-1.167); similarly, CLAD and mortality were associated with road lengths in buffers of 200-1000 and 100-500 m, respectively (hazard ratio 1.085- 1.130). Sensitivity analyses for various possible confounders confirmed the robustness of these associations.Long-term residential air pollution and traffic exposure were associated with CLAD and survival after lung transplantation, but only in patients not taking macrolides

Physical Tests Are Poorly Related to Patient-Reported Outcome Measures during Severe Acute Exacerbations of COPD

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) have a negative impact on patients’ health status, including physical function and patient-reported outcomes. We aimed to explore the associations between physical tests and patient-reported outcome measures (PROMs) in hospitalised patients for an AECOPD. Patients were assessed on the day of discharge. Quadriceps force, handgrip strength, short physical performance battery (SPPB), five-repetition sit-to-stand test (5STS), four-meter gait speed test (4MGS), balance test, six-minute walk test (6MWT), COPD Assessment Test (CAT), London Chest Activity of Daily Living scale (LCADL), modified Medical Research Council (mMRC) dyspnea scale, Checklist of Individual Strength (CIS)-fatigue subscale, and Patient Health Questionnaire (PHQ-9) were collected. Sixty-nine patients with an AECOPD were included (54% female; age 69 ± 9 years; FEV(1) 39.2 (28.6–49.1%) predicted). Six-minute walk distance was strongly correlated with mMRC (ρ: −0.64, p < 0.0001) and moderately correlated with LCADL total score, subscales self-care and household activities (ρ ranging from −0.40 to −0.58, p < 0.01). Moreover, 4MGS was moderately correlated with mMRC (ρ: −0.49, p < 0.0001). Other correlations were weak or non-significant. During a severe AECOPD, physical tests are generally poorly related to PROMs. Therefore, a comprehensive assessment combining both physical tests and PROMs needs to be conducted in these patients to understand their health status