Physical Activity and Symptom Burden in COPD: The Canadian Obstructive Lung Disease Study.

Background: The relationship between symptom burden and physical activity (PA) in chronic obstructive pulmonary disease (COPD) remains poorly understood with limited data on undiagnosed individuals and those with mild to moderate disease. Objective: The primary objective was to evaluate the relationship between symptom burden and moderate-to-vigorous intensity PA (MVPA) in individuals from a random population-based sampling mirroring the population at large. Methods: Baseline participants of the Canadian Cohort Obstructive Lung Disease (n=1558) were selected for this cross-sectional sub-study. Participants with mild COPD (n=406) and moderate COPD (n=331), healthy individuals (n=347), and those at risk of developing COPD (n=474) were included. The Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire was used to estimate MVPA in terms of energy expenditure. High symptom burden was classified using the COPD Assessment Test ([CAT] ≥10). Results: Significant associations were demonstrated between high symptom burden and lower MVPA levels in the overall COPD sample (ß=-717.09; 95% confidence interval [CI]=-1079.78, -354.40; p<0.001) and in the moderate COPD subgroup (ß=-694.1; 95% CI=-1206.54, -181.66; p=0.006). A total of 72% of the participants with COPD were previously undiagnosed. The undiagnosed participants had significantly higher MVPA than those with physician diagnosed COPD (ß=-592.41 95% CI=-953.11, -231.71; p=0.001). Conclusion: MVPA was found to be inversely related to symptom burden in a large general population sample that included newly diagnosed individuals, most with mild to moderate COPD. Assessment of symptom burden may help identify patients with lower MVPA, especially for moderate COPD and for relatively inactive individuals with mild COPD.

A machine learning approach to predict extreme inactivity in COPD patients using non-activity-related clinical data.

Facilitating the identification of extreme inactivity (EI) has the potential to improve morbidity and mortality in COPD patients. Apart from patients with obvious EI, the identification of a such behavior during a real-life consultation is unreliable. We therefore describe a machine learning algorithm to screen for EI, as actimetry measurements are difficult to implement. Complete datasets for 1409 COPD patients were obtained from COLIBRI-COPD, a database of clinicopathological data submitted by French pulmonologists. Patient- and pulmonologist-reported estimates of PA quantity (daily walking time) and intensity (domestic, recreational, or fitness-directed) were first used to assign patients to one of four PA groups (extremely inactive [EI], overtly active [OA], intermediate [INT], inconclusive [INC]). The algorithm was developed by (i) using data from 80% of patients in the EI and OA groups to identify 'phenotype signatures' of non-PA-related clinical variables most closely associated with EI or OA; (ii) testing its predictive validity using data from the remaining 20% of EI and OA patients; and (iii) applying the algorithm to identify EI patients in the INT and INC groups. The algorithm's overall error for predicting EI status among EI and OA patients was 13.7%, with an area under the receiver operating characteristic curve of 0.84 (95% confidence intervals: 0.75-0.92). Of the 577 patients in the INT/INC groups, 306 (53%) were reclassified as EI by the algorithm. Patient- and physician- reported estimation may underestimate EI in a large proportion of COPD patients. This algorithm may assist physicians in identifying patients in urgent need of interventions to promote PA.

Trends over time in COPD treatment choices by respiratory physicians: An analysis from the COLIBRI-COPD French cohort.

INTRODUCTION: Over the last decade, new evidence and many guidelines have been published on COPD pharmacological treatments; prescriptions are often not in accordance with guidelines. MATERIALS AND METHODS: Trends in physician treatment choices from February 2012 to November 2018 (Feb.2012/Nov.2018) were analyzed using data from COPD patients (spirometry-confirmed diagnosis) included in the COLIBRI-COPD cohort. Inhaled drug treatments (short- or long-acting ß2-agonist [SABA or LABA], short- or long-acting anticholinergic [SAMA or LAMA], or corticosteroid [ICS]) were classified into 5 treatment categories: "No initial maintenance treatment (IMT)" (untreated, or only SAMA or SABA); "1 long-acting bronchodilator (LABD)" (LABA or LAMA); "2 LABDs" (LABA + LAMA); "1 LABD + ICS" (LABA or LAMA + ICS); "2 LABDs + ICS" (LABA + LAMA + ICS). For the purpose of the study, 4 periods were defined to achieve balanced samples (T1-T4). RESULTS: Data from 4537 patients were collected. Over time, 3 major changes were observed: (1) an increase in treatment category "No IMT", mostly for GOLD 1 or GOLD A categories (GOLD A: from 19.1% at T1 to 41.2% at T4); (2) an increase in treatment category "2 LABDs" for GOLD 2 to 4 and GOLD A to D categories (GOLD B: from 15.4% to 29.7%); (3) a decrease in ICS use ("1 LABD + ICS" or "2 LABDs + ICS"), mostly for GOLD 1 to 3 and GOLD A categories (GOLD A, 2 LABDs + ICS: from 35.3% to 11.1%). CONCLUSION: Changes over time in therapeutic profiles suggest that new evidence from scientific publications and recommendations may have had a rapid impact on clinical practice.

Lymphangioleiomyomatosis and Tuberous Sclerosis Complex in Quebec: Prevalence and Health-care Utilization.

BACKGROUND: Lymphangioleiomyomatosis (LAM) is a manifestation of tuberous sclerosis complex (TSC) that causes destruction of the lung and chronic respiratory failure. Population-based estimates of demographics, clinical outcomes, and health-care utilization are lacking for TSC and LAM. METHODS: Data on demographics, clinical outcomes, and health-care utilization in the Quebec ministerial provincial health-care database were analyzed for their association with TSC and LAM. RESULTS: A total of 1,004 subjects with TSC were identified using International Classification of Diseases, Ninth and 10th Revisions, codes for a prevalence of one in 7,872 people. There were 38 subjects with LAM, nine of whom also had TSC. Mean ages as well as the mean age at death were lower in the LAM and TSC group than in the control group. Mortality rates were higher in subjects with LAM than in those with TSC or in control subjects. Subjects with LAM experienced more medical visits and hospitalizations than did those with TSC and control subjects; these were associated with higher health-care costs. Frequently prescribed drugs in TSC or LAM included anticonvulsants, antidepressants, and sedatives; the use of mammalian target of rapamycin inhibitors was uncommon. CONCLUSIONS: The prevalence of TSC in Quebec, Canada, is similar to estimates from previously published surveys. LAM is likely underreported, perhaps due to suboptimal case identification or referral. Health-care utilization and mortality for LAM are high, suggesting that timely diagnosis and therapy could be beneficial. Mental health disorders may be an unrecognized clinical feature of LAM. These results provide a population-based background for policymakers and researchers to better address the needs of patients with TSC and LAM.