Postpartum Glucose Monitoring in Pregnant Women with Gestational Diabetes Mellitus: A Dual Center Experience.
Bibliographic record
Abstract
OBJECTIVE: Gestational diabetes mellitus (GDM) is known to be a predisposing factor in the development of type 2 diabetes mellitus in affected mothers and their offspring. Current guidelines recommend a two-hour postpartum glucose tolerance test (OGTT) in patients with a history of GDM. However, compliance rates for ordering and completion has been reported as suboptimal. The COVID-19 pandemic has had significant impact on healthcare systems, requiring the adaptation of novel strategies to manage patients. So far, there is a paucity of data on how this impacts compliance rates for the oral glucose tolerance test. We aimed to compare the compliance rate and impact of the pandemic on OGTT ordering and completion between a women's hospital and a community health center. METHODS: A dual center retrospective cohort study was carried out to compare the compliance for ordering and completion of the two-hour postpartum OGTT in women diagnosed with GDM between a women's hospital and community health center two years pre-COVID-19 (2018-2019) and during the COVID-19 pandemic (2020-2021). RESULTS: 2569 pregnancies were included during these time periods. Prior to the pandemic, the test ordering compliance at the women hospital was 30.2% vs 79.3% for the community health center. During the pandemic, the test ordering compliance at the women's hospital dropped to 24.8%, while it remained steady at the community center (80.8%). Correspondingly, there was a drop in test completion compliance rate at both centers during the pandemic when compared to rate before the pandemic. CONCLUSION: Diagnosis of GDM increased during the pandemic, which may be attributed to factors like sedentary lifestyles, and restructuring of care models, among others. There was increased test ordering and test completion compliance at the community health center compared to the women's hospital, which can be attributed to routine follow-ups and other factors.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 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".