Chronic Obstructive Pulmonary Disease (COPD) as a Risk Factor for Glucose Metabolism Perturbation and Insulin Resistance
Bibliographic record
Abstract
Background: High body mass index (BMI) is associated with better survival in COPD. However, increased BMI and especially waist circumference is associated with elevated pro-inflammatory systemic markers that might contribute to glucose intolerance. On the other hand, COPD is a chronic inflammatory disease that could be a risk factor for impaired glucose metabolism. The objective of this study was to compare the prevalence of glucose intolerance in COPD patients and control subjects with high waist circumference. Methods: Eleven patients with COPD (age:68±8 yr mean±SD; FEV1:49±17% pred) and 10 control subjects (C) (age:63±6 yr) underwent a 75g oral glucose tolerance test (OGTT). All subjects had a waist circumference >102cm and no previous history of diabetes. Height and weight were measured and each subject underwent dual-energy X-ray absorptiometry (DEXA) to evaluate fat-free mass (FFM) and fat mass (FM) and abdominal tomography to evaluate visceral fat (VF). Blood samples were taken to measure inflammatory markers (C-reactive protein (CRP), tumor necrosis factor (TNF), interleukin (IL)-6). Venous blood samples of glucose and insulin were taken while fasting and during OGTT. Insulin resistance was estimated with the fasting homeostasis model assessment (HOMA) index. Results: FM, FFM and VF were not different between groups. Diabetes was diagnosed in two subjects in both groups (2hr post OGTT glucose ≥11.1 mmol/l). Four COPD and 1 C had impaired fasting glucose (fasting glucose 5.6–6.9 mmol/l) while 1 COPD and 2 C had impaired glucose tolerance (2hr post OGTT glucose 7.8–11.1 mmol/l). In COPD patients a negative correlation was found between the HOMA index and FEV1 (r2:0.52, P < 0.05). Conclusions: COPD subjects with high waist circumference are similar to control subjects in term of FFM and FM, level of systemic inflammation and response to OGTT. In COPD, the severity of the disease is associated with an insulin resistance that may potentiate the risk for the development of type 2 diabetes in these patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".