C-Reactive Protein and Gestational Diabetes: The Central Role of Maternal Obesity
Bibliographic record
Abstract
Acute-phase biomarkers such as C-reactive protein (CRP) and IL-6 have emerged as predictors of incident type 2 diabetes mellitus, implicating chronic subclinical inflammation as a factor in the pathophysiology of diabetes. Gestational diabetes (GDM) identifies a population of women at high risk of subsequent type 2 diabetes mellitus, representing an early stage in the natural history of the disease. In this context, we performed a cross-sectional study to determine whether markers of subclinical inflammation are elevated in patients with GDM. We studied 180 healthy pregnant women undergoing oral glucose tolerance testing in the late second or early third trimester. Based on oral glucose tolerance testing and prepregnancy body mass index (BMI), participants were stratified into four groups: 1) normal glucose tolerance (NGT) lean (BMI, <25 kg/m(2)) (n = 65); 2) NGT overweight (n = 28); 3) impaired glucose tolerance (n = 39); and 4) GDM (n = 48). Median CRP level was highest in overweight NGT subjects (8.8 mg/liter), followed by GDM (5.5 mg/liter), impaired glucose tolerance (4.4 mg/liter), and lean NGT (4.4 mg/liter) (overall P = 0.0297). CRP was significantly correlated with prepregnancy BMI (r = 0.38, P < 0.0001), followed by fasting insulin (r = 0.27, P = 0.0002) and fasting blood glucose (r = 0.18, P = 0.016). In multivariate linear regression analysis, prepregnancy BMI emerged as the most important determinant of CRP concentration, whereas glycemic tolerance status was not a significant factor. Furthermore, the observed stepwise increase in CRP per tertile of prepregnancy BMI was not significantly attenuated by glycemic tolerance status or factors known to be associated with GDM. In summary, we demonstrate that maternal serum levels of CRP are not related to GDM but rather correlate significantly with prepregnancy obesity. An independent contribution of CRP to risk of GDM could not be confirmed. These data suggest a model in which obesity mediates a systemic inflammatory response, with possible downstream metabolic sequelae, including insulin resistance and glucose dysregulation.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".