Do Postpartum Levels of Apolipoproteins Prospectively Predict the Development of Type 2 Diabetes in Women with Previous Gestational Diabetes Mellitus?
Bibliographic record
Abstract
AIMS: The risk of developing type 2 diabetes is greater in women with previous gestational diabetes mellitus (GDM). Apolipoprotein (Apo) species have been associated with the development of type 2 diabetes in the general population. The aim of this study was to determine if circulating levels of Apo species can predict development of type 2 diabetes in women with previous GDM. METHODS: Apo AI, Apo AII, Apo B, Apo CII, Apo CIII and Apo E levels were measured in 95 women with normal glucose tolerance, 12 weeks following an index GDM pregnancy. Women were assessed for up to 10 years for the development of type 2 diabetes. RESULTS: Postpartum Apo CIII levels, and Apo CIII/Apo AI, Apo CIII/Apo AII, Apo CIII/Apo CII, Apo CIII/Apo E and Apo E/Apo CIII ratios were significantly and positively associated with the development of type 2 diabetes. After controlling for age and BMI, these associations, except for the Apo E/Apo CIII ratio, remained significant. In a clinical model of prediction of type 2 diabetes that included age, BMI, and pregnancy and postnatal fasting glucose, the addition of Apo CIII levels, Apo CIII/Apo AI, Apo CIII/Apo AII, Apo CIII/Apo CII, and Apo CIII/Apo E resulted in a net reclassification improvement of 16.2%. CONCLUSIONS: High Apo CIII levels and the Apo CIII/Apo AI, Apo CIII/Apo AII, Apo CIII/Apo CII, and Apo CIII/Apo E ratios are all significant risk factors for the development of type 2 diabetes in women with a previous GDM pregnancy.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".