Impact of a modified screening approach during the <scp>COVID</scp>‐19 pandemic on the diagnosis and outcomes of gestational diabetes mellitus: A population‐level analysis of 90,518 pregnant women
Bibliographic record
Abstract
AIMS: To provide real-world evidence on the uptake of and outcomes associated with the modified gestational diabetes mellitus (GDM) screening approach offered during the COVID-19 pandemic compared with the standard screening approach. METHODS: All pregnancies between 01 January 2020 and 31 December 2021, in Alberta, Canada, were included in the study. We examined GDM screening and diagnosis rates, and large-for-gestational-age (LGA) outcomes. RESULTS: Annual GDM screening rates were > 95% during the study time period. Overall, 84.7%, and 11.6% of the 92,505 pregnancies underwent standard and modified screening for GDM, respectively. The use of modified screening was the highest among deliveries in August 2020 (49.8%) which corresponded to the early first wave of the pandemic. GDM diagnosis rate was lower in the modified screening (7.4%) than in the standard screening (12.3%, p < 0.001) group. The LGA rates in the modified screening with GDM and the standard screening with GDM groups were 24.8% and 12.6%, respectively (p < 0.001). Women in the modified screening with GDM group were at a higher risk of having an LGA infant (adjusted odds ratio: 3.46; 95% confidence interval: 2.93, 4.08) compared to the standard screening with no GDM group. CONCLUSIONS: The COVID-19 epidemic had no impact on screening for GDM. Women who underwent modified screening, based on HbA1c/random plasma glucose, had lower rates of GDM cases.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".