A1c versus oral glucose tolerance test for chronic glycemic surveillance in women with previous gestational diabetes
Bibliographic record
Abstract
AIMS: Women with gestational diabetes (GDM) are advised to undergo an oral glucose tolerance test (OGTT) within 6 months postpartum, owing to their elevated risk of developing pre-diabetes/diabetes. However, the optimal approach to glycemic surveillance in the years thereafter is unclear. We thus sought to compare OGTT, fasting glucose and A1c for chronic monitoring of women with previous GDM. MATERIALS AND METHODS: At both 3-years and 5-years postpartum, 111 women with previous GDM had glucose tolerance assessed with A1c, fasting glucose and OGTT, with concomitant evaluation of insulin sensitivity/resistance (Matsuda index, HOMA-IR) and beta-cell function (Insulin Secretion-Sensitivity Index-2 (ISSI-2), insulinogenic index/HOMA-IR (IGI/HOMA-IR)). RESULTS: At 3-years postpartum, no women were identified with dysglycemia (pre-diabetes/diabetes) by fasting glucose alone. Instead, dysglycemia was diagnosed in 10 women by A1c alone, 24 women by OGTT alone and 16 women by both A1c and OGTT. Beta-cell function progressively worsened from those diagnosed by A1c alone to OGTT alone to those meeting both criteria (ISSI-2: p < 0.001; IGI/HOMA-IR: p = 0.01). At 5-years, dysglycemia was diagnosed in 13 women by A1c alone, 27 by OGTT alone and 21 by both measures. Beta-cell function again progressively decreased from A1c alone to OGTT alone to both (ISSI-2: p < 0.001; IGI/HOMA-IR: p < 0.001) but was now accompanied by worsening insulin sensitivity/resistance (Matsuda index: p < 0.001; HOMA-IR: p = 0.002) and rising fasting glucose (p = 0.008) across these groups. CONCLUSIONS: In women with previous GDM, dysglycemia on OGTT identifies a higher risk metabolic phenotype than when diagnosed by A1c, suggestive of more informative and robust glycemic surveillance by OGTT.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".