Gestational Diabetes and Incident Heart Failure: A Cohort Study
Bibliographic record
Abstract
<b>Objective: </b>To assess whether gestational diabetes mellitus (GDM) is associated with an increased risk of heart failure (HF). <p><b>Research Design and Methods</b>: We conducted a population-based cohort study using information from the Ministry of Health and Long Term Care of Ontario (Canada) health-care administrative databases. We identified all women in Ontario with a GDM diagnosis with a livebirth singleton delivery between July 1, 2007 and March 31, 2018. Women with diabetes or HF before pregnancy were excluded. GDM was defined based on laboratory test results and diagnosis coding. The primary outcome was incident HF hospitalization, over a period extending from the index pregnancy until March 31, 2019. The secondary outcome was prevalent peripartum cardiomyopathy (PPCM) at index pregnancy. Estimates of association were adjusted for relevant cardiometabolic risk factors.</p> <p><b>Results</b>: Among 906,319 eligible women (mean age: 30 years [SD: 5.6], 50,193 with GDM [5.5%]), there were 763 HF events over a median 7 years. GDM was associated with a higher risk of incident HF (adjusted hazard ratio [aHR]: 1.62, 95% CI: 1.28, 2.05), compared to no-GDM. This association remained significant after accounting for chronic kidney disease, post-partum diabetes, hypertension, and coronary artery disease (aHR: 1.39, 95% CI: 1.09, 1.79). GDM increased the odds of PPCM (adjusted odds ratio: 1.83, 95% CI: 1.45, 2.33).</p> <p><b>Conclusions</b>: In a large observational study, GDM was associated with an increased risk of HF. Consequently, diabetes screening during pregnancy is suggested to identify women at risk of HF.</p> <br> <p> </p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".