Impact of pregnancy on the trajectories of cardiovascular risk factors in women with and without gestational diabetes
Bibliographic record
Abstract
AIMS: The elevated lifetime risk of cardiovascular disease in women who develop gestational diabetes mellitus (GDM) has been attributed to adverse life-course trajectories of cardiovascular risk factors that arise before pregnancy and continue thereafter. We hypothesized that pregnancy may differentially affect these trajectories in women who develop GDM and those who do not. MATERIALS AND METHODS: With population-based administrative databases, we identified all nulliparous women in Ontario, Canada, who had singleton pregnancies between January 2011 and December 2016 and ≥2 measurements of the following analytes both before and after pregnancy: glycated haemoglobin (HbA1c), glucose, lipids and transaminases. In total, 39 581 women (4373 with GDM) had 3.9 ± 3.4 tests before and 4.6 ± 5.4 tests after pregnancy. RESULTS: Both before and after pregnancy, women who developed GDM had higher HbA1c, fasting glucose, low-density lipoprotein (LDL)-cholesterol and triglycerides than their peers, with lower high-density lipoprotein (HDL)-cholesterol (all p < .0001). Before pregnancy, women who went on to GDM had higher annual increases than their peers did in HbA1c, fasting glucose and triglycerides (all p ≤ .01); lesser annual decrease in LDL (p = .0003); and greater annual decrease in HDL (p = .0006). Compared with pre-pregnancy, the postpartum differences in annual rates of change in HbA1c and fasting glucose were 6.9- and 3.3-fold higher, respectively, in women with GDM. Conversely, the respective postpartum differences in annual rates of change in triglycerides, LDL and HDL were 1.2, 1.6 and 0.3 times lower than before pregnancy. CONCLUSION: After pregnancy, differences in pregravid trajectories of glycaemic measures are amplified between women with GDM and their peers. In contrast, pregravid differences in lipid measures persist but do not differentially worsen after 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".