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Record W2599506948 · doi:10.1111/resp.13031

COPD: Lessons learned, forging a fantastic future

2017· editorial· en· W2599506948 on OpenAlexaff
Don D. Sin, Gregory G. King

Bibliographic record

VenueRespirology · 2017
Typeeditorial
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of British ColumbiaProvidence Health Care
Fundersnot available
KeywordsCOPDMedicineDiseaseEconomic growthGerontologyIntensive care medicinePathologyPsychiatry

Abstract

fetched live from OpenAlex

A year ago, we asked 75 internationally renowned authors, representing four continents of the world, to highlight the most important lessons that we have learned over the past decade regarding the pathogenesis, diagnosis and management of COPD. We instructed them to focus in particular on the Asia Pacific region, where there are still major challenges to the diagnosis and treatment of COPD and to provide insights in these reviews that can translate to improved care of our patients and promote policies and research programmes to address its growing burden in our communities and throughout the world. They have delivered in a resounding way and through their efforts, we have been empowered. What were the key lessons from this series? We learned that by 2020, more than 200 million people worldwide will have COPD and every year, COPD will be directly responsible for the death of 4.7 million people.1 COPD is increasingly observed in marginalized communities including those of low socio-economic status and among patients with HIV/AIDS.2 While the pathophysiology of COPD is complicated, the main drivers of this disease are cigarette smoke in industrialized nations and air pollution in the developing world.3 The importance of early life events in the pathogenesis of COPD is beginning to be recognized. The two primary processes that lead to COPD are: (i) accelerated decline in lung function in adulthood and (ii) poor lung growth during childhood.4 While most patients with COPD have mild disease (forced expiratory volume in 1 s (FEV1) >80% of predicted with FEV1/forced vital capacity (FVC) ratio <70%), many of these patients are symptomatic (when challenged)5 and indeed, they have the greatest rate of FEV1 decline.4 For example, an incremental exercise test reveals that these patients are frequently ventilation-limited in their exercise tolerance and bronchodilators improve their exercise performance.5 It is thus important to encourage physical activity in COPD patients, even in the earliest stages of disease.6 It is important that when exercise targets are set, clinicians should set achievable goals by outlining initially a low-intensity programme that patients can perform as part of their ‘daily routine’.6 It should also be noted that while COPD is objectively defined by persistent spirometric airflow limitation, innovative application of advanced imaging modalities such as computed tomography (CT) and MRI scans demonstrate different phenotypes of disease (e.g. airway vs emphysema), define novel, clinically relevant disease features and provide new insights into pathogenesis, even in patients who have normal spirometry.7 Given that many patients with COPD have multiple co-morbidities, which impact their symptoms, morbidity and mortality, developing a multidimensional risk profile for established COPD patients as well as at-risk individuals is an urgent and high priority research goal. In more advanced stages, pharmacological strategies are needed. Therapeutic choices should be driven by patient symptoms and their risk of exacerbation.8 Patient preference should also be factored into this decision. For those with persistent symptoms, the initial choice in most cases should be a long-acting bronchodilator.8 However, some COPD patients also have a clear history of asthma (which we now label as ‘asthma–COPD syndrome’), in which case inhaled corticosteroids in combination with a long-acting bronchodilator may be considered.9 There is a pressing clinical need to better understand the asthma–COPD syndrome, particularly to develop biomarkers of risk and treatment response, which might include indices of inflammation, complex lung physiology and imaging.9 For example, airway hyperresponsiveness (AHR) is common in COPD but its mechanisms are complex and poorly understood in asthma and in COPD. AHR appears to be driven by perturbed airway geometry and increased airway wall stiffness whereas in asthma AHR is likely due to greater airway constriction related to greater airway smooth muscle mass, along with other pathophysiological factors.10 There are non-pharmacological therapies (including influenza and pneumococcal vaccination, smoking cessation and pulmonary rehabilitation) that should be provided for patients.11 The natural history of COPD is often punctuated by periods of exacerbations, which if severe enough, should be treated with a 5-day course of systemic corticosteroids (e.g. 40 mg/day of prednisone or equivalent).12 COPD is a complex disorder with many additional features including pulmonary hypertension (which is present in 20–30% of patients with FEV1 <50% of predicted),13 bronchiectasis and various co-morbidities (e.g. cardiovascular disease).14 In these complex patients, clinicians may wish to set up a ‘control panel’ to list the relevant features and align these features with possible therapeutic solutions for each of these co-morbidities.14 What is the future of COPD research? The omics revolution provides an exciting new chapter to unlock the mysteries in pathogenesis and enable discovery of new and more effective therapeutic solutions. The omics technology has already shown that our lungs are not sterile and that there is a rich lung microbiome that is perturbed in COPD.15 The relevance of the lung microbiome in health and disease will soon be revealed.16 Animal models provide valuable mechanistic insights to COPD and its importance will be enhanced with new molecular techniques (e.g. gene editing) that will accelerate translation.17 These advances will demand a high standard of clinical assessment; arguably new drugs and treatment strategies will work when applied in the right patient and clinical assessment of patients with airways disease will be more (rather than less) important in their future management. We are entering the golden age of COPD research and with the multi-omics revolution, we will expect new biomarkers for accurate phenotyping and precision health and novel therapeutic products that will fundamentally alter the ‘natural course of COPD’ and enable our patients to live longer and live better.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.378
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2017
Admission routes1
Has abstractyes

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