Abstract P382: Visceral Adiposity is a Stronger Correlate of Plasma C-Reactive Protein Levels than Liver Fat in the INSPIRE ME IAA Study.
Bibliographic record
Abstract
Although it is well established than plasma C-reactive protein (CRP) levels predicts cardiovascular events beyond traditional risk factors, the main drivers of elevated CRP in the population are still under investigation. Among those, obesity and body fat distribution have been suggested to be important correlates of circulating CRP concentrations. The present analysis explored the correlates of CRP in the INSPIRE ME IAA cohort, a large CT imaging cardiometabolic risk study involving 2262 men and 2093 women for whom complete CT imaging and cardiometabolic, as well as CRP data, were available. CRP>10mg/l were excluded (N= 327). Both visceral adiposity (Men r=0.41 p<0.0001; Women r=0.50 p<0.0001) and liver attenuation, inversely related to liver fat, (Men r=-0.24 p<0.0001; Women r=-0.27 p<0.0001) were significantly correlated with plasma CRP levels. When both liver fat and visceral adiposity were placed in a multivariate model including age, region and physician’s specialty, we found that visceral adiposity (Men: partial R2=17.4 p<0.0001; Women: partial R2=24.1 p<0.0001) was more strongly related to CRP level than liver attenuation (Men: partial R2=0.3 p<0.0001; Women: partial R2=2.0 p<0.0001). Further adjustment for BMI, smoking status and statin use yielded similar results. We then divided patients into six groups according to tertiles of visceral fat (VAT) and the median of liver fat (LF): 1) lowVAT-lowLF, 2) lowVAT-highLF, 3) midVAT-lowLF, 4) midVAT-highLF, 5) highVAT-lowLF, 6) highVAT-highLF. In both men and women, CRP levels were higher in the midVAT and highVAT groups compared to the lowVAT group; yet, there was no difference between low and high LF within each respective VAT tertile after adjustment for age, BMI, region and specialty. This pattern was similar when statin use, smoking status, and the presence/absence of type 2 diabetes or cardiovascular disease (CVD) or metabolic syndrome were included. Our results show that CRP is strongly related to visceral adiposity, independent of several other covariates including liver fat. Due to the role of CRP in the prediction and prognosis of CVD, the assessment/management of visceral adiposity, by its surrogate marker waist circumference, will provide clinicians and patients with valuable information regarding an important correlate of this key inflammation marker.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".