Missed opportunities for type 2 diabetes testing following gestational diabetes: a population‐based cohort study
Bibliographic record
Abstract
OBJECTIVES: Few women with gestational diabetes (GDM) are tested for type 2 diabetes in the postpartum period. Whether women are having physician visits that could be an opportunity to improve testing rates is unknown. This study sought to evaluate population-level trends in postpartum diabetes testing after GDM, and to evaluate postpartum physician care for these women. DESIGN: Population-based cohort study. SETTING: Ontario, Canada. POPULATION: Women who delivered between 1994 and 2008. METHODS: Using population-level healthcare databases, we identified 47,691 women with GDM. They were matched to women without GDM. MAIN OUTCOME MEASURES: An oral glucose tolerance test (OGTT) within 6 months postpartum, the specialty of the physician ordering the test, and ambulatory care visits with physicians from various specialties within 6 months postpartum were recorded. RESULTS: Most women with GDM did not receive an OGTT, although testing rates increased slowly over the 14 years of the study, compared with no change in testing for women who had not had GDM. Virtually all women with GDM had postpartum visits with a family physician or obstetrician, but few OGTTs were ordered by physicians from these specialties. CONCLUSIONS: Despite a slow increase in testing over time and high rates of postpartum visits to family physicians and obstetricians, few women with GDM received the recommended diabetes test. This represents a missed opportunity in a high-risk population. Interventions to change test ordering that target family physicians and obstetricians are most likely to increase the proportion of women with GDM who receive postpartum diabetes testing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".