Comparative metabolic and obesity profiles of COPD and non-COPD controls in the CanCOLD population-based cohort
Bibliographic record
Abstract
<b>Rationale:</b> A high prevalence of metabolic syndrome and obesity in patients with chronic obstructive pulmonary disease (COPD) has suggested pathophysiological links between these disorders. However, whether differences in metabolic profiles and accumulation in ectopic adipose tissue exist between COPD and non COPD subjects remains unclear. <b>Objective:</b> To compare the metabolic profile (insulin resistance, adipokines, lipids), and visceral adipose tissue accumulation between subjects with COPD and controls in a population-based cohort. <b>Methods:</b> 263 subjects were randomly selected from the general population and prospectively classified according to the GOLD classification. Blood was collected and a computed tomography obtained to quantify insulin resistance (HOMA-IR), lipid and adipokine profiles, and visceral adipose tissue cross-sectional areas (VAT CSA) assessed at L4-L5. <b>Results:</b> 144 COPD (70 GOLD 1 and 74 GOLD 2+) and 119 non-COPD controls were included. No specific distributions of metabolic parameters and adipokines appears in graphical representations between COPD and controls. No increased Odds-Ratios for having pathologic profiles of HOMA-IR, lipids and VAT were observed in COPD subjects on multivariate analyses taking into account age, sex, body mass index, tobacco status and current medications. <b>Conclusion:</b> In a population-based population, no differences were found in metabolic profiles and ectopic fat accumulation between COPD and non-COPD subjects. Increased prevalence of abnormal metabolic profile and ectopic fat accumulation found in previous studies could be related to the inclusion of specific COPD phenotypes at higher risk of metabolic disturbances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".