Risks of Dysglycemia Over the First 4 Years After a Hypertensive Disorder of Pregnancy
Bibliographic record
Abstract
BACKGROUND: Women with the hypertensive disorders of pregnancy (HDP) (preeclampsia [PE] and gestational hypertension [GHTN]) have increased risks of future diabetes. Postpartum glycemic testing offers early identification and treatment of dysglycemia, but evidence-based recommendations for this high-risk population are lacking. The objective of this study was to describe the risks of developing dysglycemia in women with normotensive and hypertensive pregnancies over the first 4 years postpartum. METHODS: The Discharge Abstract Database was used to identify women who delivered singleton live-born infants in Calgary, Alberta, Canada, between January 2010 and December 2012 (N=27,300). This was linked with Calgary Laboratory Services (for glycemic tests) and the Pharmaceutical Information Network databases (for antidiabetes medication prescriptions) over the first 4 years postpartum. Logistic regression analyses compared glycemic testing and results were adjusted for maternal age, gestational age, parity and the Pampalon deprivation index. RESULTS: Women with HDP had more glycemic testing (GHTN 67.8% and PE 69.9% vs normotensive 60.9%; p<0.001) and significantly higher results for fasting plasma glucose (GHTN 4.82±0.51 mmol/L and PE 4.84±0.54 mmol/L vs normotensive 4.73±0.49 mmol/L; p<0.001), random plasma glucose (GHTN 5.20±0.96 mmol/L and PE 5.39±1.71 mmol/L vs normotensive 5.00±0.87 mmol/L; p<0.001) and glycated hemoglobin levels (PE 5.62±0.53% vs normotensive 5.49±0.32%; p<0.001). Women with HDP had a higher adjusted odds (95% confidence interval) of developing type 2 diabetes compared with normotensive women (GHTN: 2.26, 1.50 to 13.4; PE: 2.02, 0.91 to 4.46). CONCLUSIONS: The high prevalence of early dysglycemia highlights the importance of targeted postpartum glycemic testing in women after HDP. Further research on optimal glycemic testing (specific tests and timing) in these high-risk women is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".