Chronic obstructive pulmonary disease (COPD): bridging the knowledge gap for early intervention and prevention of disease progression.
Bibliographic record
Abstract
Chronic Obstructive Pulmonary Disease (COPD) is a progressive respiratory disorder, the leading cause of non-parturition hospital stay in Canada and the third leading cause of death globally, known for heterogeneity in its development, presentation, and progression. Treatment planning targets prevention and management of exacerbations since these aggressively impact lung function deterioration even in mild-moderate disease severity stage.There are gaps in our knowledge, among those with mild-moderate COPD, to support the detection of rapid decliners and the development of targeted therapeutics. Prevalent knowledge has evolved mainly through studies in severely ill patients and is not generalizable to milder stages. The overarching goal of this thesis is to bridge some of these pressing knowledge gaps. The Canadian Cohort of Obstructive Lung Disease (CanCOLD) participants are reflective of patients at family medicine practices with mild-moderate COPD and, hence, were selected to study characteristics of those likely to experience rapid decline. Clinically important deterioration (CID), a composite measure; the recently recalibrated Acute COPD Exacerbation Prediction Tool (ACCEPT) 2.0; and the ratio of biomarkers Advanced Glycation Endproducts (AGE)/ soluble receptor for AGE (sRAGE) were assessed for the first time for use in this population.In Manuscript 1, short-term CID (2 definitions) was examined as an indicator of deterioration in disease and dyspnea in the following short-term period. This was assessed via suitable models adjusted for age, sex, BMI, and pack-years alongside a second set of models controlled additionally for comorbidity and biomarkers. The outcomes of a) ≥100 and 200 mL declines in forced expiratory volume in 1 second (FEV1), worsening health status [≥ 4 and 8 unit increases in St. George respiratory Questionnaire score, and ≥2 and 4 unit in COPD Assessment Test] and dyspnea (≥1 unit increase in Medical Research Council score) were analyzed using logistic regression models; b) new moderate/severe exacerbations using Cox Proportional Hazards models; and c) the incidence of such exacerbations using Poisson regression models. Results show that while composite CID definition will need to be adapted for this population, health status measure and exacerbation were informative components (third component: FEV1 decline). A study to validate the findings is underway using the United Kingdom primary care data (protocol included).In Manuscript 2, the ACCEPT 2.0 model was compared to the exacerbation history (last 12 months) in the CanCOLD cohort. The observed discrimination for the ACCEPT 2.0 model was superior to the adapted exacerbation definitions used in the study. Area under the time-dependent Receiver Operating Characteristic Curve was compared using the DeLong Test, and calibration plots were reviewed. The findings support a future study in a larger cohort to recalibrate the model for the mild-moderate COPD population. Biomarkers are clinically informative and included in prediction models to improve accuracy. The pathophysiology of AGE-RAGE stress and AGE/sRAGE ratio as a disease activity marker in COPD is reviewed in Manuscript 3. Manuscript 4 reports and discusses the serum concentrations and correlations of AGE, sRAGE, and AGE/sRAGE in a CanCOLD sub-cohort with clearly defined 3 groups: healthy controls excluding conditions and drugs known to influence the biomarker levels; non-COPD smokers; and those with COPD. The ratio was significantly higher in the at-risk and COPD groups (compared to the healthy group). The data suggests the potential for AGE/sRAGE as a promising new biomarker in mild-moderate COPD. However, further evaluations are needed to explore the correlations observed here and with other available markers of COPD.The gaps identified and studies conducted in this thesis add important knowledge that dovetails toward the goal of personalized care in mild-moderate COPD
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".