Metabolic and inflammatory profile in obese patients with chronic obstructive pulmonary disease
Bibliographic record
Abstract
BACKGROUND: Overweight and obesity have been associated with better survival in patients with chronic obstructive pulmonary disease (COPD). On the other hand, excess body weight is associated with abnormal metabolic and inflammatory profiles that define the metabolic syndrome and predispose to cardiovascular diseases. This study was undertaken to evaluate the impact of overweight and obesity on the prevalence of the metabolic syndrome and on the metabolic and inflammatory profiles in patients with COPD. METHODS: Twenty-eight male patients with COPD were divided into an overweight/obese group [ n = 16, body mass index (BMI) = 33.5 +/- 4.2 kg/m(2)] and normal weight group (n = 12, BMI = 21.1 +/- 2.6 kg/m(2)). Anthropometry, pulmonary function and body composition were assessed. The metabolic syndrome was diagnosed according to waist circumference, circulating levels of triglyceride and high-density lipoprotein cholesterol levels, fasting glycemia and blood pressure. C-reactive protein, tumor necrosis factor-alpha (TNF-alpha), interleukin-6 (IL-6), leptin and adiponectin plasma levels were measured. RESULTS: Airflow obstruction was less severe in overweight/obese compared with normal weight patients (forced expiratory volume(1): 51 +/- 19% versus 31 +/- 12% predicted, respectively, P < 0.01). The metabolic syndrome was diagnosed in 50% of overweight/obese patients and in none of the normal weight patients. TNF-alpha, IL-6 and leptin were significantly higher in overweight/obese patients whereas the adiponectin levels were reduced in the presence of excess weight. CONCLUSIONS: The metabolic syndrome was frequent in overweight/obese patients with COPD. Obesity in COPD was associated with a spectrum of metabolic and inflammatory abnormalities.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".