0452 THE INTERACTION BETWEEN OBSTRUCTIVE SLEEP APNEA (OSA) AND OBESITY ON SERUM LEVELS OF INFLAMMATORY ADHESION MOLECULES
Bibliographic record
Abstract
Serum levels of adhesion molecules are associated with increased risk of cardiovascular disease (CVD). Obesity and OSA are associated with increased serum levels of adhesion molecules, but the interaction between them is unclear. Patients referred to the UBC Sleep Laboratory for a polysomnogram (PSG) for suspected OSA were recruited and provided a morning blood sample after PSG. 494 patients participated; mean age was 49.7 yrs, 323 were male, and mean AHI was 22.6/hr. In unadjusted analyses (Spearman’s coefficient), body mass index (BMI) was significantly associated with serum levels of the three adhesion molecules investigated (E-selectin, intracellular adhesion molecule ICAM, vascular cell adhesion molecule VCAM). AHI was significantly associated with E-selectin levels (Spearman’s= <.01) but not sICAM (Spearman’s= 0.31) or sVCAM (Spearman’s= .40). The relationships between E-selectin and BMI/AHI were further explored using linear regression. After adjusting for previous heart disease, smoking status, gender and age, both AHI (p=.01) and BMI (p=<.01) remained significant predictors. A multiplicative interaction between AHI and BMI was not found (p=.33). However, patients with both severe sleep apnea (AHI>30) and a BMI above the median (32 kg/m2) had elevated levels of E-selectin (55.43 ng/ml) compared to individuals who had either condition alone (50.39 ng/ml and 52.10 ng/ml), and ANOVA results suggest a significant difference between groups (F=<.01). BMI and AHI are significant predictors of E-selectin levels. Patients who were obese and had severe OSA had significantly higher E-selectin levels than those who had either condition alone. Further research is required to determine the clinical consequences of elevated levels of E-selectin associated with OSA and obesity. CIHR (Sleep Disordered Breathing Team Grant), VCHRI Scientist Award, BC Lung Association Operating Grant.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".