Trends and Self-Management Predictors of Glycemic Control During Pregnancy in Women With Preexisting Type 1 or Type 2 Diabetes: A Cohort Study
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Bibliographic record
Abstract
Background: Because much of diabetes management during pregnancy occurs at home, self-management factors such as self-efficacy, self-care activities, and care satisfaction may affect glycemia. Our objective was to explore trends in glycemic control during pregnancy in women with type 1 or type 2 diabetes; assess self-efficacy, self-care, and care satisfaction; and examine these factors as predictors of glycemic control. Methods: We conducted a cohort study from April 2014 to November 2019 at a tertiary center in Ontario, Canada. Self-efficacy, self-care, care satisfaction, and A1C were measured three times during pregnancy (T1, T2, and T3). Linear mixed-effects modeling explored trends in A1C and examined self-efficacy, self-care, and care satisfaction as predictors of A1C. Results: We recruited 111 women (55 with type 1 diabetes and 56 with type 2 diabetes). Mean A1C significantly decreased by 1.09% (95% CI -1.38 to -0.79) from T1 to T2 and by 1.14% (95% CI -1.43 to -0.86) from T1 to T3. Self-efficacy significantly predicted glycemic control for women with type 2 diabetes and was associated with a mean change in A1C of -0.22% (95% CI -0.42 to -0.02) per unit increase in scale. The exercise subscore of self-care significantly predicted glycemic control for women with type 1 diabetes and was associated with a mean change in A1C of -0.11% (95% CI -0.22 to -0.01) per unit increase in scale. Conclusion: Self-efficacy significantly predicted A1C during pregnancy in a cohort of women with preexisting diabetes in Ontario, Canada. Future research will continue to explore the self-management needs and challenges in women with preexisting diabetes in pregnancy.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it