Impact of the Combined Diabetes Clinic on HbA1c Changes and Outcomes in Pre-existing Diabetics in Rural Saskatchewan [14A]
Bibliographic record
Abstract
INTRODUCTION: Pregnant women with pre-existing diabetes have increased risk for poor outcomes such as macrosomia, shoulder dystocia, still birth and intrapartum interventions. The Combined Diabetes Antenatal Clinic (CDAC) in Prince Albert (started in 2012) is a multidisciplinary clinic that serves rural northern Saskatchewan where the prevalence of diabetes in pregnancy is high. The goals of the CDAC are to improve euglycemia and pregnancy outcomes. METHODS: Retrospective cohort chart review to quantify the reduction in HbA1c after CDAC interventions and if the reduction in HbA1c improved pregnancy outcomes. Ethics approval was obtained from University of Saskatchewan. RESULTS: We identified 116 CDAC patients with pre-existing diabetes between 2012-2017. Majority of the population (52%) had to travel over 200 km to reach the CDAC clinic. There were high rates of obesity (71%) and high parity (28% Para 4 or more), majority were Type 2 diabetics and 87% of mothers were on insulin at the time of delivery. Women often (75%) presented to the CDAC after the first trimester. However, over 50% of patients who attended the CDAC reached the target of having an HbA1c below 6.5% prior to delivery. Mean change in HbA1c was -1.0% (SD 0.5-2.4) Mothers with HbA1c below 6.5% at the time of delivery had lower rates of shoulder dystocia (5.9% vs 2.3%) and still birth (11.8% vs 4.5%). CONCLUSION: The CDAC is effective in reducing the HbA1c and reductions below 6.5% is associated with improved pregnancy outcomes. We advocate pre-pregnancy counselling and booking early in pregnancy for pre-existing diabetes in this rural population
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".